顾客旅程视角下品牌线上营销优化研究

本文通过系统文献综述,深入探讨了用户研究在增强电商独立站吸引力和用户偏好中的应用.重点分析了五种典型的用户研究方法在优化电商独立站界面布局,信息架构,内容可读性, ...

研究表明，通过构建统一的数据底座、以用户旅程为核心优化营销策略，并辅以跨部门协同的组织保障，能够有效打破数据孤岛与策略脱节，实现资源配置效率与市场响应能力的同步提升 ...

社交媒体平台的兴起，彻底重塑了旅游业的消费旅程与品牌建设模式。从灵感激发、行程规划到体验分享与事后评价，小红书、抖音、Instagram等平台已深度嵌入游客决策的全 ...

摘要: 在电子商务背景下，线上营销已经成为营销活动不可或缺的一部分。故宫博物院文创产品的线上营销不仅是保障其运营稳定、提高运营水平的现实需求，也是适应时代发展、 ...

在数字媒体环境下，顾客期望的形成机制变得更加复杂。社交媒体上的网红推荐、在线评论和评分、品牌社交媒体表现等都在塑造顾客期望方面发挥着重要作用。大部分消费者在购买 ...

用户旅程理论指出，顾客在早期认知阶段会通过多种触点接触品牌，其中社交媒体与口碑在新兴消费群体中扮演越来越重要的角色[5]。从访谈内容来看，部分重庆用户提到，其 ...

本项研究专注于电子商务领域，并构建了一个以客户全生命周期价值(CLV)为中心的数据驱动的营销策略框架。通过运用机器学习建模、多维度数据评估和归因分析，对客户价值的 ...

企业需构建动态迭代的用户画像体系,推进智能化的个性化内容推送,建立科学合理的营销效果归因模型,并对数据赋能的客户旅程进行优化.以此来解决企业在追求营销精准化过程中, ...

国外银行数字化转型以汇丰银行和摩根大通这样资产雄厚的顶尖商业银行为例，汇丰银行主打端到端的客户旅程再造的数字化战略，这里的客户旅程一般来说是指在客户首次接触到企业 ...

在跨境语境中，设计需优先化解信息不对称，通过用户旅程地图诊断痛点，如浏览阶段的视觉疲劳或决策阶段的犹豫阈值。实践路径包括A/B测试框架：对比纯技术场景与设计注入 ...

用户激活作为用户旅程的转化中枢，其本质是通过认知价值感知驱动用户完成从触点接触到核心行为转化的跃迁。在组织架构层面，这一环节常处于市场触达与产品运营的跨部门 ...

本文将盲盒消费过程划分为浏览,下单,开箱,分享与再购五个阶段,以可视化方式展现用户在各阶段的行为,触点和体验变化,识别出概率机制不透明,重复购入,开箱落差及社交反馈不足 ...

用户行为分析能够为网络保险营销的优化提供科学依据，针对传统营销所存在的识别能力不足、内容同质化、转化率低以及资源配置低效等问题，本研究设计出精准识别机制、个性化 ...

消费者浏览行为与购买行为之间匹配效应则研究的是：如何规避假性活跃陷阱，在消费者何种行为阶段采取何种匹配类型的信息多样性对其购买转化率效果更好。由于对 ...

通过不同算法对用户行为进行分析，可以获取相关数据参数，并将数据参数转化为可以执行的运行策略，提升转化率。 ... 虽然现在已经有很多学者提出了不同的通用分析模型和具体 ...

例如，针对频繁浏览但购买转化率较低的用户，优化商品推荐算法，提高推荐商品的精准度和吸引力；针对偏好简洁界面的用户，优化页面布局，减少冗余信息，提升页面加载速度。将优化 ...

通过个性化推荐和动态视觉内容的结合,平台能够即时响应用户需求,进而提升转化率和用户满意度. ... 因此,交互设计不仅是页面美观的体现,更是推动用户行为转化的有效工具.

电商短视频的时长作为影响用户完播率,互动率及转化率的关键因素,其最优区间的确定对内容创作者和商家至关重要.本文旨在基于从抖音平台采集的真实电商短视频数据,提出一种多 ...

点击率(CTR)预测是电子商务平台实现智能营销的关键技术，广泛应用于广告投放、商品推荐和用户行为分析等核心场景。随着线上交易规模扩大，精准、高效的CTR预测模型成为 ...

2023年,希音的个性化推荐系统的转化率比传统的展示广告高出约30% [13].具体而言,用户在浏览商品时,如果看到与自己兴趣相关的推荐商品,其购买转化率比没有个性化推荐 ...

利用消费者在网络留下的行为数据进行重复购买行为的预测对企业实现精准营销有着重要的意义.本文采用电子商务平台上的历史行为数据对消费者复购行为进行预测有助于提升用户 ...

通过行为分析和个性化内容推送，Chat-GPT能够根据用户偏好调整互动策略，增加用户的活跃度。信息化系统使企业能够实时监控用户反馈，从而及时优化用户体验，提升激活率。在内容 ...

随着电子商务在体育器材领域的深度渗透,消费者线上购买决策机制呈现复杂化特征.本研究通过国内各头部电商平台财报和文献综述的方式对消费者线上购买体育器材的现状进行 ...

In today’s digital world, delivering personalized customer experiences is paramount for businesses that are aiming to foster engagement and drive conversions. However, many organizations grapple with challenges such as data inconsistencies and outdated technologies. A report by Contentful highlights that 57% of senior marketing executives struggle with data inconsistencies when personalizing customer experiences, and only 24% of firms effectively invest in omnichannel personalization due to departmental silos and outdated technology1. Reinforcement Learning (RL), a subset of machine learning, offers a promising solution to these challenges by enabling systems to learn optimal strategies through trial and error interactions with the environment. In the context of marketing, RL can dynamically adapt customer journeys in real-time, optimizing for long-term customer value rather than short-term metrics . Salesforce Marketing Cloud serves as a solid platform for implementing RL-driven strategies, offering tools like Journey Builder and Audience Studio that facilitate the orchestration of personalized customer experiences across multiple channels . This whitepaper aims to explore the integration of Reinforcement Learning into Salesforce Marketing Cloud for dynamic customer journey optimization. It will explore the challenges of current personalization methods, elucidate the principles of RL, and provide guidance on implementing RL strategies within the Salesforce ecosystem to enhance customer engagement and business outcomes.

Digitalization and rising demand for branded content have reshaped Indonesia’s creative industry over the past decade. The post-pandemic shift toward digital content, social media marketing, and integrated creative solutions has pushed agencies to innovate continuously. Competition has grown not only among established agencies but also with the rise of large-scale freelance collectives, making client loyalty a critical differentiator. Agencies now need to prioritize long-term, meaningful relationships rather than focusing solely on acquiring new clients. Distrik Berisik, a Jakarta-based creative agency founded in 2021, operates within this dynamic environment and serves Indonesia’s youth market with end-to-end creative solutions. Although customer acquisition is strong, the agency faces retention challenges, maintaining only a 30–40% retention rate. At the same time, many business leaders believe overly digital approaches often fail to align with real customer needs. This study addresses these issues by optimizing the customer journey through a Design Thinking approach. The research is guided by three questions: mapping the current customer journey from the first interaction to post-program stages; identifying key pain points and opportunities; and developing an improved journey model to strengthen customer experience and loyalty. A qualitative method is used, with Design Thinking’s five stages—Empathize, Define, Ideate, Prototype, and Test—serving as the main framework. Data were collected through questionnaires and analyzed using Thematic and Descriptive Analysis to reveal patterns, satisfaction levels, retention potential, and repurchase intentions. Combining the concepts of Customer Journey, Customer Loyalty, and Design Thinking, the study proposes a practical, human-centered customer journey model tailored to the creative industry.

This paper aims to discuss the application of AI in digital marketing, its role in enhancing decision-making, personalization, and campaign performance along the customer's journey. This study employs a qualitative research approach to investigate the strategic application of AI in digital marketing, drawing on recent academic literature, industry reports, and case studies. Thematic coding was applied to identify key patterns and emerging themes such as predictive analytics, customer personalization, and performance optimization. The key applications are big data analytics, content personalization, omnichannel integration, automated content generation, and dynamic customer interaction. The evidence suggests that the strategic use of AI not only enhances customer satisfaction and conversion rates but also improves operating efficiency and fosters long-term brand loyalty. As digital ecosystems continue to evolve, AI emerges as a key driver of innovation and digital marketing competitiveness. The study leverages existing academic and practical knowledge to describe how AI equips organizations with the capacity to manage enormous datasets, automate marketing functions, and deliver hyper-personalized experiences.

As firms gather increasing amounts of data, the question of how future marketers can use these data to make their marketing more relevant and to make a strategic difference remains. However, students may feel uncomfortable about information systems and database technology, which they may perceive as complex and dry. This case describes how the development of a course on data-driven marketing makes use of service design methods. The experiential learning innovation is based on the optimization of customer journey mapping, which encompasses theoretical marketing concepts, modern database architecture and practical digital marketing knowledge. As a visualization of individual interactions with a product, service, or brand, customer journey mapping helps explain the way an interaction occurs in one moment and how it influences all other moments. By taking the “data as a service” perspective on the customer journey, students benefit from a more innovative and creative approach to data-driven marketing, which helps improve their attention and motivation.

The usual marketing funnel no longer safely reflects consumer behaviour in the modern era. Customers prefer to participate in the Consumer Decision Journey (CDJ), a more repetitive and straight- ahead decision- making method. This analysis examines how businesses can impact buyers from when a customer becomes aware of a product until the purchase. As a result of the expansion of digital marketing, strategies like social media marketing, personalized advertising, search engine optimization (SEO), influencer marketing, and user-generated content (UGC) have gained more and more attention. This research uses the CDJ of McKinsey to observe how businesses can improve digital marketing to improve user experience and build brand loyalty. Moreover, it examines the impact of word- of- teeth marketing and online reviews on developing consumer trust and offers suggestions for controlling myths. But this review advises businesses to improve their digital marketing strategies, improve customer relationships, and get a competitive advantage in an increasing market.

Abstract The paper explores the transformation of sales funnel levels under the influence of digital trends in marketing, emphasizing the relevance of optimizing customer interaction in a rapidly changing digital environment. The purpose of the study is to refine theoretical and methodological approaches to understanding the sales funnel and to justify the necessity of its transformation according to digitalization processes. The research applies system analysis, generalization, comparative and content analysis, as well as modeling methods to study customer movement through the sales funnel and to visualize key interaction stages. The Ukrainian market situation during 2022-2023, marked by increased demand for energy equipment, illustrates the need for adaptive marketing tools. The study proposes a Customer Journey Map model for an online wholesale company as a practical example of sales funnel optimization. The findings substantiate that digital tools and CRM systems enhance communication efficiency, adaptability, and sustainable business development under the conditions of global digital transformation.

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In today's digital landscape, businesses must allocate online resources efficiently. Data-driven AI methods are increasingly adopted for customer journey management. This study enhances existing frameworks with three key propositions, integrating deep learning and optimization to create a three-step revenue optimization model using online customer data. First, we apply K-means clustering to analyze online user data, constructing a behavior model. Then, convolutional neural networks (CNN) and long short-term memory (LSTM) networks predict user behavior and conversion values from sequential data. Finally, the heuristic algorithm optimizes revenue within budget constraints based on conversions. From an academic perspective, our study provides an empirical, theory-grounded model for service and marketing management. Technologically, we identify three key findings: stacking LSTM with CNN effectively processes sequential online user data, outperforming traditional machine learning methods; optimization methods and decision trees improve model interpretability and address marketing attribution challenges by understanding user behavior and channel impacts; and traditional integer programming models fall short in solving high-dimensional online channel planning problems, necessitating heuristic algorithms. Our model aids companies in setting online channel standards and budgets, offering valuable insights and practical guidance to decision-makers.

This study examines consumer behavior patterns through comprehensive search pattern analysis across three major e-commerce platforms. The research analyzed 127,543 search sessions from 12,847 unique users over six months using Latent Dirichlet Allocation (LDA) and K-means clustering. Data collection involved clickstream analysis, query pattern extraction, and behavioral tracking across mobile, desktop, and tablet devices. Statistical methods included hierarchical linear modeling, ANOVA, and chi-square tests. The analysis identified five distinct consumer segments: Exploratory Browsers (32.4%), Systematic Researchers (23.8%), Direct Purchasers (18.7%), Deal Seekers (15.3%), and Uncertain Seekers (9.8%). Results reveal significant behavioral variations across customer journey stages, with query length increasing from 2.84 to 4.89 words and brand mentions rising from 15.2% to 71.3% from awareness to retention stages. Mobile devices dominated usage (63.4%), with distinct behavioral patterns across demographics and temporal factors. These findings enable businesses to develop targeted marketing strategies, optimize user experience design, and implement personalized recommendation systems. This research contributes original insights by integrating quantitative behavioral analytics with qualitative thematic analysis, providing a comprehensive framework for understanding digital consumer decision-making processes in contemporary e-commerce environments.

This article analyzes the transformation of enterprise marketing activities in the context of economic digitalization, focusing on the role of information technology as a strategic resource for developing competitive advantages. Elements of digital marketing are examined through the lens of intangible asset management. The importance of digital tools in increasing a company’s market value, enhancing investment attractiveness and the sustainability of business models is substantiated. Based on the concept of the customer journey, the study reveals the operating mechanisms of analytical platforms, big data processing technologies, and artificial intelligence algorithms, interprets consumer digital footprints, and ensures the personalization of interactions and the optimization of management decisions at all stages of consumption. An analysis of scientific publications reveals a shift in research focus toward the communication and analytical aspects of marketing, while demonstrating the insufficient development of strategic issues of segmentation and positioning in the digital environment. It has been established that the integration of information technology into the marketing system, synchronizing the processes of research, planning, and strategy implementation, contributes to a reduction in transaction costs and an increase in the effectiveness of customer interactions. It is concluded that the digital transformation of marketing is the foundation for building a customer-centric business, ensuring enterprises’ adaptation to market dynamics and the creation of long-term cu stomer value.

: In the era of digital marketing, optimizing the consumer funnel in real-time has become a critical challenge for businesses seeking to maximize conversion rates and customer lifetime value. This paper presents a novel framework that leverages artificial intelligence (AI) and data science techniques to enhance the consumer funnel dynamically. By integrating machine learning algorithms, natural language processing, and real-time data analytics, our approach enables businesses to adapt their marketing strategies instantaneously based on consumer behavior and market trends. We introduce a multi-layered architecture that combines predictive modeling, sentiment analysis, and personalization engines to create a responsive and adaptive funnel optimization system. This research contributes to the growing field of AI-driven marketing automation and offers practical insights for implementing advanced analytics in consumer journey optimization

Bobrovnyk V.M., Andrushkevych Z.M. MICRO-MOMENTS IN THE DIGITAL TRANSFORMATION OF MARKETING: IMPACT ON THE CUSTOMER JOURNEY IN DIFFERENT BUSINESS MODELS Purpose. The aim of the article is to explore the practical aspects of the impact of short-term but meaningful interactions between a consumer and a brand in the digital environment, assess their role in shaping the customer journey in different business models, and generalize tools for measuring the effectiveness of such interactions in the context of modern marketing. Methodology of research. The study is based on an interdisciplinary approach that combines theoretical and practical aspects of analysing consumer behaviour in the digital environment in the context of the categories of “need” and “value”, and adapting marketing tools to the conditions of digital transformation. General scientific and specialized methods were used in the course of the research, which made it possible to comprehensively investigate micro-moments as a key factor in shaping the customer journey. To gain an in-depth understanding of current trends in the digital transformation of marketing, a review of current research was conducted, which allowed us to identify the most common practices of using micro-moments in marketing, identify gaps in theoretical and practical approaches to adapting marketing tools in the surrounding of digital change, and identify key aspects of using micro-moments in different contexts, including B2C, B2B, D2C, and C2C business models. This approach has provided a comprehensive understanding of the role of micro-moments in the modern marketing process, and allowed us to develop practical recommendations for brands on how to integrate micro-moments into their strategies in the context of digital marketing transformation. Findings. It has been proven that micro-moments are an important factor in shaping new brand interaction strategies with customers, and are formed at different stages of the customer journey. The key types of micro-moments and their connection with different stages of consumer decision-making were identified, which allows to accurately target marketing efforts at each stage of interaction. It was found that for the successful implementation of micro-moments in marketing strategies, it is necessary to better understand the needs and values of consumers, as well as to form a system of rapid brand response to changes in customer behaviour. The key aspects of the use of micro-moments in marketing strategies were identified. The key areas of measuring the effectiveness of interactions in different business models (B2C, B2B, D2C, C2C) were formed. Originality. The use of micro-moments in the context of digital marketing transformation and assessment of their impact on the formation of new consumer behaviour patterns characterized by nonlinearity and multi-vector nature was further developed. The practices of adapting marketing tools to the digital environment have been improved, allowing identifying micro-moments and using them to attract and retain customers in various business models. The main directions of influence of micro-moments on the formation of a personalized customer experience were substantiated, which, unlike the existing ones, determined their relationship with different stages of the customer journey in the context of four types of micro-moments and the effectiveness of interactions in different business models. Practical value. The results of the study contribute to improving communication processes with customers, optimizing the use of marketing resources, as well as creating competitive advantages and unique value propositions in various business models. The study can become an important resource for marketers, analysts, and digital communications professionals seeking to better understand consumer behaviour in the digital environment and effectively adapt marketing strategies to the conditions of digital transformation. It will also be useful for business managers and business owners interested in implementing innovative approaches to attract and retain customers, in particular through personalization of customer experience. Key words: micro-moments, digital transformation, customer journey, digital marketing, customer experience, personalization, business models, marketing strategies.

The research objectives is to identify critical touchpoint (s) of digital customer journey in PT BTC marketplace channel strategy, to discover the result of current PT BTC digital customer journey feedback, to give recommendation in digital marketing strategy to improve PT BTC digital customer journey, and to give supporting strategy to enhance PT. In this research, data collection methods will be using qualitative data from Primary Data and Secondary Data. This research found 5 critical touchpoints of digital customer journey in PT BTC marketplace channel strategy, like Awareness, Appeal, Ask, Act, Advocate. Current marketplace channel strategy is effective to catch new B2B customers but less effective to retain their consistency to buy via online transaction. From this finding research, the best suitable digital marketing strategy that fit to PT BTC customer journey is creating and establishing website and improving its system to become modify-website that enabled to e-commerce facilities. The supporting strategy to establishing website marketing strategy is purposing new company’s marketing division structure to delegate workload better, more effective and more efficient.

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This study investigates the influence of Voice AI capabilities and conversational marketing features on customer experience (CX), trust, satisfaction, and loyalty. Although prior research has emphasized the role of CX in shaping consumer outcomes, limited attention has been given to the combined effects of Voice AI and conversational marketing within a trust-centered framework. This research addresses this gap by clarifying when and how trust matters most in AI-mediated interactions. A quantitative, cross-sectional survey design was employed, collecting data from consumers familiar with AI-driven services. Using PLS-SEM in SmartPLS 4.0, the study tested direct, mediating, and moderating effects across a sample representative of digitally engaged users. Results reveal that Voice AI (β = 0.426, p < 0.001) and conversational marketing (β = 0.395, p < 0.001) significantly improve CX. CX strongly predicts satisfaction (β = 0.699, p < 0.001) and moderately predicts loyalty (β = 0.216, p = 0.006). Trust directly influences loyalty (β = 0.625, p < 0.001) but does not significantly affect satisfaction (p = 0.250). Moderation tests show trust strengthens CX → satisfaction but not CX → loyalty. The study contributes by extending Customer Experience Theory, showing that CX drives satisfaction, while trust sustains loyalty. Practically, it highlights the need for empathetic, transparent AI design to balance short-term and long-term consumer outcomes.

This study explores the transformative role of Artificial Intelligence (AI) in enhancing customer experience personalization (CEP) and optimizing marketing strategies (MSO) within digital marketing environments. Grounded in the Technology Acceptance Model (TAM), the research incorporates ethical and privacy concerns (EC) as moderating factors influencing AI adoption and its effectiveness. Using survey data from marketing professionals across diverse industries, the study employs Structural Equation Modeling (SEM) to analyze complex relationships among AI use, CEP, MSO, and marketing outcomes. The findings reveal that AI significantly improves customer engagement and marketing performance by enabling tailored interactions, data-driven segmentation, and campaign optimization. Moreover, ethical and privacy concerns positively moderate these effects, underscoring the necessity of responsible AI practices in sustaining consumer trust and regulatory compliance. By offering empirical insights into the interplay between AI, personalization, strategy, and ethics, this study contributes to both theoretical development and practical guidance for businesses navigating digital transformation. The research highlights AI’s strategic potential in creating sustainable competitive advantage while advocating for ethical safeguards in technology-driven marketing.

In recent years, the integration of sustainability principles into digital marketing strategies has become increasingly important, particularly within the textile and fashion sectors. However, conventional machine learning approaches often treat input features as black-box predictors, neglecting their causal relevance. In this study, a novel framework called CATE-Informed Engagement Prediction Framework (CIEPF) is proposed. This framework enhances predictive models by incorporating estimated CATE (Conditional Average Treatment Effects) as auxiliary features. By embedding individualized causal estimates into the feature space, models capture nuanced treatment response heterogeneity often overlooked by standard descriptive variables. To validate the framework, a dataset of Instagram© posts related to textile circularity has been analyzed across three treatment conditions: positive sentiment, afternoon posting, and weekend posting. A comparative evaluation was conducted using Random Forest and Decision Tree models, both with and without CATE integration. The empirical findings demonstrate that models enriched with CATE consistently outperformed their baseline counterparts, achieving lower RMSE and higher R2 values. These results confirm that the inclusion of causally informed features significantly enhances predictive accuracy in engagement modeling. The proposed methodology bridges the gap between causal inference and supervised learning, offering valuable implications for personalized digital marketing and sustainable communication strategies.

This research examines the interplay between Business Intelligence tools and digital marketing strategy optimization, with a focus on the moderating role of customer orientation. Utilizing a quantitative research design, the study explores how BI tools enhance digital marketing strategies and how customer orientation amplifies this effect among 207 respondents from the Jordanian telecommunications sector, reflecting a diverse range of experiences and perceptions within the industry. Through Structural Equation Modeling - Partial Least Squares (SEM-PLS), based on a stratified sample of these employees, the results confirmed that BI tools positively influence digital marketing strategy optimization. Additionally, customer orientation was found to significantly moderate this relationship, highlighting the importance of aligning technological capabilities with a customer-centric approach. The findings contribute valuable insights to marketing and business intelligence fields, suggesting strategies for organizations to enhance their market competitiveness and customer satisfaction, underpinned by a substantial engagement rate from the targeted demographic.

The internet is used by the majority of the world’s population. Many of its contents are free for consumers, supported by digital marketing investment. The current large online population can render digital marketing campaigns inefficient for brands buying ads if the right message is not reaching the right audience. Customer Data Platforms (CDPs) enables brands to collect first-party data about their customers and leverage it to reach the right audience, without sharing private customer data with third parties. This paper documents how CDPs work, by detailing their main components as patterns and relating them as a pattern language. The language is composed of five patterns: Event Tracking, ID Matching, User Profile Storage, Segmentation, and Activation. The pattern language can be used by marketeers and engineers in digital marketing as an introduction or reference to how CDPs are designed and work.

Nowadays, while most machine learning research on customer journey optimization has focused on short-term success metrics such as click-through rates and optimal ad placement, there has been little consideration given to developing a coherent system for end-to-end customer journey optimization. Such a system would encompass all aspects of the customer experience, from presenting the right product value to the right users, to understanding a user's likelihood of conversion and long-term value to the platform, as well as their propensity for cross-selling and risk of churning. Currently, models and algorithms for customer journey optimization are often developed in isolation, leading to inefficiencies in modeling and data pipelines. Furthermore, the customer is often viewed as a collection of different entities by different organizational departments (such as marketing, sales, and finance), which can lead to additional friction in the customer experience. This workshop seeks to bridge the gap between academic researchers and industrial practitioners who are interested in building holistic solutions for end-to-end customer journey optimization. In addition, with the rising popularity of generative AI and LLM, we want to use this venue to exchange ideas regarding their applications in different stages of customer journey, and how the new technologies could help businesses achieve their objectives.

The article investigates the adoption of real-time customer journey orchestration using Microsoft Power Platform CRM with minimal coding. It looks at the enhancements to Dynamics 365 Marketing and Customer Insights made in 2025 and shows how these have empowered marketers to implement AI-driven personalization at scale. Key components of the research include a technical architecture that integrates Dynamics 365 Customer Insights, Power Automate Flows, AI Builder Models, Dataverse, and Power Apps Canvas Applications. A four-phase implementation methodology provides a structured approach to deploying customer journey orchestration through clearly demarcated focus areas in data foundation, journey design, trigger implementation, and enhancing with AI. Those discussed above are several of the key technological challenges: state management, performance optimization, and integration complexity; this paper outlines relevant solutions. Ethical considerations focus on privacy compliance, algorithmic transparency, and personalization boundaries. The article concludes by providing future directions; conversational journey orchestration, extended reality integration, and edge computing capabilities provide direction for organizations seeking sophisticated approaches toward engaging their customers in an increasingly competitive landscape.

Optimizing customer journeys is a critical challenge in e-commerce and financial services, attracting attention from marketing, operations research, and business analytics. Traditional customer analytics models, such as rule-based segmentation and regression models, rely heavily on structured transactional data, limiting their ability to capture latent behavioral patterns and adapt to multi-channel dynamics. These models often struggle to integrate unstructured data sources, failing to provide adaptive, personalized insights. To address these limitations, this study proposes a multi-stage data-driven framework integrating latent Dirichlet allocation (LDA) for behavioral insights, deep learning for predictive modeling, and heuristic algorithms for adaptive decision-making. Empirical validation using Taiwanese financial institution data shows a 15% improvement in predictive accuracy compared to traditional machine-learning models, significantly enhancing customer lifetime value (CLV) predictions and multi-channel resource allocation. This research highlights the practical value of integrating structured and unstructured data for improving customer analytics. Our framework leverages LDA to extract behavioral patterns from customer interactions, enriching predictive models and enhancing real-time decision-making in financial services. Robustness checks confirm the scalability and adaptability of this approach, offering a data-driven strategy for long-term value optimization in dynamic digital ecosystems.

In Africa's digital real estate market, traditional marketing no longer suffices. This study uses the Technology Acceptance Model to explore how Nigeria's Realvest can enhance customer acquisition and retention through better digital marketing. Based on data from 280 Nigerian proptech professionals, it identifies gaps in Realvest's use of data mining, audience targeting, and customer relationship management. The research surveys digital marketing tactics like SEO, email automation, content marketing, and customer journey mapping, comparing Realvest to leading African firms such as Kenya's Optiven, South Africa's Pam Golding, and Nigeria's Adron Homes. Findings reveal how digital tools can improve customer experience and brand loyalty, guiding Realvest to align marketing with evolving consumer behavior and technology.

A revolutionary chance to improve consumer engagement exists with the incorporation of AI. This proposed delves at the various ways generative AI may be used in digital marketing campaigns, highlighting how it can change the way customers engage and content is made. Personalized content, made possible by AI's capacity to sift through mountains of customer data, is the main emphasis. Chatbots and virtual assistants powered by artificial intelligence are also investigated in the study for their potential to offer real-time assistance and interactivity. By improving the user experience and keeping their attention, this technology encourages more in-depth brand involvement. The article also assesses how well AI-powered social media strategy optimization works. Increased conversion rates, better engagement, and fine-tuned marketing tactics are the results of this automation. Finally, the article takes into account the growing significance of optimizing digital marketing campaigns for voice and visual searches, where artificial intelligence improves content visibility and accessibility through these new search methods. In this proposed to show that generative AI is essential to developing marketing tactics that are more tailored to each individual, creative, and responsive than ever before. Generative AI is a game-changer for digital marketing efforts because it combines creativity, efficiency, and personalization to increase client engagement.

This study aims to analyze the implementation of Search Engine Optimization (SEO) as part of digital marketing strategies to enhance online visibility in the hospitality industry. In response to rapid developments in digital technology, hospitality businesses are required to adapt to modern marketing practices that are more measurable and customer-oriented. One of the key strategies in this transformation is SEO, which plays a pivotal role in improving website rankings on search engine result pages, thereby attracting potential customers organically. This research employs a qualitative approach using data collection methods such as direct observation, in-depth interviews, and documentation. Data sources include digital marketing personnel, analytics dashboards, and supporting literature. The primary focus is on evaluating how SEO initiatives—such as keyword optimization, content enrichment, and structural enhancements—contribute to measurable performance improvements. Findings indicate that the implementation of SEO, which began in December 2023, had a significant positive impact. The number of unique visitors increased by 68%, total visits grew by 101%, and page views surged by more than 624% in 2024 compared to the previous year. These improvements are closely linked to the systematic application of SEO techniques, including content relevancy, keyword alignment, and the use of analytical tools such as Google Analytics for ongoing evaluation. The conclusion drawn from this study is that consistent and well-executed SEO implementation significantly enhances online visibility and strengthens competitiveness in the digital hospitality landscape. The study emphasizes the importance of maintaining continuity in SEO practices to ensure long-term benefits. It also serves as a reference for digital marketing practitioners seeking to optimize their web presence in a highly competitive market.

The financial institutions nowadays increasingly depend on digital marketing tools to attract and retain customers. The paper examines the role of digital channels - social media, Search Engine Optimization, and personal email campaigns among others - in customer engagement. This is a highly competitive industry; therefore, there exists a drastic need for developing data-driven and targeted approaches to attract and retain customers. This paper proposes a novel Sugeno Ranking Fuzzy Digital Marketing (SRFDM) model to evaluate and enhance digital marketing strategies in financial institutions, with a focus on customer acquisition and retention. The model incorporates fuzzy logic to assess three key factors: Keyword Relevance, Content Quality, and User Engagement, which are essential for optimizing digital marketing efforts. Through the application of fuzzy rule-based outputs, the SRFDM model ranks the effectiveness of various strategies, providing insights into their performance and areas for improvement. The findings demonstrate that strategies with high levels of keyword relevance, content quality, and user engagement consistently achieve superior rankings, resulting in higher effectiveness in acquiring and retaining customers. This research highlights the importance of balancing these factors for optimal marketing performance, offering financial institutions a practical tool to refine their strategies, improve customer targeting, and enhance overall digital marketing outcomes. The SRFDM model serves as a valuable framework for financial institutions seeking to improve their competitive edge in the evolving digital landscape.

This study examines the effectiveness of digital marketing strategies in enhancing branding and customer engagement at PT KB Valbury Sekuritas. Using a qualitative approach with interviews, observation, and documentation, this research analyzes the company's digital marketing strategy implementation through social media platforms, particularly, Instagram and TikTok. The results show that the key indicators of success include engagement rate, conversion rate, and customer feedback. However, several challenges were identified, such as maintaining content relevance, increasing audience engagement, and addressing human and technical resource limitations. To overcome these challenges, the recommended optimization strategies include improving content consistency, using paid advertisements, and decentralizing digital marketing at the branch levels. These findings are expected to help PT KB Valbury Sekuritas develop more effective digital marketing strategies to strengthen brand identity and increase customer loyalty

In today's digital world, businesses engage in what is known as digital marketing, which encompasses a range of strategies for interacting with customers online. All of these all-encompassing plans aim to attract, retain, and delight customers via a variety of means, including search engine optimization and social media marketing. The effectiveness of these strategies hinges on the concept of customer experience, which encompasses the entirety of a consumer's interactions with a brand across many touchpoints. From the initial stage of browsing to the help provided after the purchase, every interaction shapes the customer's impression of the firm. It is essential to prioritize great client experiences in order to increase loyalty and encourage repeat business, as satisfied consumers are more inclined to suggest the firm and remain loyal over time. Customers are loyal to brands because those brands consistently provide them with exceptional experiences that surpass their expectations and help them develop a personal connection to the brand. Digital marketing has a significant impact on these connections because it allows organizations to personalize content, deliver personalized messages, and facilitate seamless cross-channel engagements.

Digital transformation has reshaped the banking industry, including the implementation of digital marketing strategies to enhance customer loyalty. This study analyzes the effectiveness of digital marketing strategies in green banking services, focusing on factors contributing to customer retention. Using a qualitative descriptive approach, this research explores various strategies such as service personalization, digital education, and user experience optimization. The findings indicate that social media, email marketing, SEO, and digital-based loyalty programs enhance customer engagement and trust. However, challenges such as low public awareness and limited digital infrastructure still need to be addressed. By leveraging data-driven technologies and digital innovation, banks can strengthen their commitment to sustainability and attract more environmentally conscious customers.

The hasty expansion of e-commerce in the marketplace has led to heightened competition, making it essential for businesses to ensure customers remain satisfied and loyal over the long term. This study examines the influence of various elements of the digital marketing mix on consumer satisfaction and loyalty within the online environment. A survey involving 1,000 online shoppers was conducted to gain insights into how digital interactions between customers and companies can be improved. Specifically, the study focused on four strategic approaches: social media engagement, email communication, search engine visibility enhancement, and mobile commerce optimization. The findings revealed that social media interactions and email campaigns had the most significant impact on customer satisfaction and retention. The study strongly recommends that e-commerce firms adopt more innovative digital engagement practices to enhance customer experiences and support sustained business growth.

Big data analytics is becoming more important in marketing today. This tool helps companies understand market trends so that they can develop targeted campaigns. In this assignment, we are required to examine how the application of big data analytics can help marketers understand the behavior of their customers and develop an effective marketing campaign. This research paper contains a detailed analysis of consumer interactions on digital platforms using advanced machine learning algorithms like Gradient Boosting Machines and Random Forests. The author employed these models to derive insights from large data sets. The goal is to understand how the use of large amounts of data in tracking customer behavior can improve marketing strategies. The research of this study included an in-depth examination of both the organized and disorganized consumer information data. By utilizing predictive models, the research can accurately forecast customer behavior. The GBM model showcased remarkable performance in foretelling customer’s purchase behavior, realizing a phenomenal accuracy rate of 94.39%. Furthermore, by using K-means clustering to group consumers based on their behavior, marketers could develop better marketing strategies. This article provides a lot of useful information about digital marketing and the use of vast amounts of data to analyze it. This statement means that companies give great importance to data analytics to make better marketing decisions. This research serves as a foundational element for subsequent investigations and provides an avenue for further scrutiny regarding the integration of additional data and the enhancement of machine learning algorithms.

This study explores the potential of digital data-based customer profitability analysis in optimizing marketing strategies for Small and Medium Enterprises (SMEs) in the former Surakarta Residency, Indonesia. Using a mixed-method approach, including semi-structured interviews with 15 SME owners/managers, direct observations, document analysis, and an online survey of 250 customers, the research investigates the current state of digital data adoption, challenges in implementation, and the impact of customer profitability analysis on marketing effectiveness. The study employs RFM (Recency, Frequency, Monetary) analysis for customer segmentation and calculates Customer Lifetime Value (CLV) to identify key profitability drivers. Findings reveal limited awareness and implementation of digital data-based customer profitability analysis among SMEs, primarily due to resource constraints and technical expertise limitations. The research identifies four customer segments, with 15% (Platinum customers) contributing significantly to profitability. Purchase frequency and average transaction value emerge as primary profitability drivers. The study concludes that while digital data-based customer profitability analysis offers significant potential for optimizing SME marketing strategies, realizing this potential requires collaborative efforts from SME stakeholders, policymakers, and support institutions to address implementation challenges and build a supportive ecosystem for data-driven marketing practices.

Increasingly intense competition and advances in IT are significantly impacting the way we manage both company-customer interaction and business relationships. In today's reality, huge amounts of information are generated, managed and analyzed via multiple channels and touchpoints. In this article, we wish to illustrate the importance of mapping the set of critical and secondary interactions with a view to enhance customer journey management. This article takes the case of the multinational insurance company Aon as a reference. Our methodological approach is based on a secondary database, information provided by the company itself and interviews with Aon key informants. We propose a general map of the customer journey in the B2B insurance sector. Moreover, we take one of the most critical moments in insurance interactions—claim management—as a reference, with a view to provide further, more specific, mapping. Our objective is two-pronged: on one hand, to underscore the importance of visualizing and managing such moments of truth effectively; on the other, to highlight the need to maintain a holistic vision of the company-customer relationship and the key role all touchpoints play throughout. When mapping the customer journey, we emphasize the importance of considering all value-creating interactions—not only critical interactions. Moreover, we suggest carrying out second-level mapping for all key, most-relevant activities. This article makes a series of key contributions aimed at enhancing touchpoint management, improving the customer experience and maximizing satisfaction. To increase the efficacy of customer portfolio management, we recommend holistic strategies and specific guiding actions tailored to each moment of the company-customer relationship.

An enhanced online purchase journey map for VIP (Very Important Person)/hospitality packages is proposed where customisation is advocated to improve customer purchase experiences and mitigate frustrations. Marketing premium experiences with higher prices vs face-value tickets increases consumer expectations which may result in reputational consequences for organisations via reviews. Exploratory mixed methods were initiated by a qualitative analysis of online reviews of two hospitality event ticketing companies. The most common themes established were customer service, expectations, booking/payment process, pricing and value for money. Online survey findings (n=312) of sports and entertainment consumers established the main ticketing frustrations as additional fees, online queuing and time to complete the order. The first managerial implication is that event organisations could adopt the methodology of linking online review analysis with journey mapping and enhance with consumer focus groups regarding proposed changes. Secondly, organisational internal ownership measures within the journey map could be implemented.

Ride-hailing services have afflictive «monopolized» regions of North Africa and changed the nature of interaction cities and various digital platforms. Yassir — which provides a mobile-based alternative to standard taxi services — has rapidly established itself among Algeria's dominant VTC service providers. But this increasing visibility brings up critical questions about the real quality of the user experience. The company touts the affordability, efficiency, and convenience of its service, but user reviews from the web paint a more complex and, at times, contradictory portrait. By investigating the digital footprints present in comments made publicly by users as well as reviews found on platforms, this study aims to shed light on the various user stages in order to better comprehend the journey customers undergo when engaging with Yassir. The aim really is to find those key friction and satisfaction moments and how that influences their engagement and loyalty. We employed a qualitative netnographic methodology where we compiled and thematically analyzed user generated content on social media and mobile app platforms. Data were coded according to the four key phases of the customer journey: awareness, consideration, decision and post-experience. The results suggest that Yassir customer experience is an assemblage that is constituent by a variety of cognitive, and emotional factors that changes over time. Users usually find out about the app in the initial awareness stage when it is shown in the form of a sponsored ad or via a friend or an influencer. This phase is critical because it sets first impressions. The right pricing models will attract some users, a cross-section will be drawn in by competitive prices and the promise of convenience, while others express initial reluctance based on unclear pricing models and negative word-of-mouth. Those early concerns suggest a perception gap between the promotional promise and the perceived reliability of the service. In the consideration stage, users are actively comparing Yassir against their competitor apps (TemTem and Heetch). Online ratings, reviews and anecdotal experiences all serve as social proof, which is a critical driver of perceptions. While promotional codes and referral incentives boost engagement, cyclical pain points — such as pricing, sudden cancellations, and lack of clear route tracking — are frustrating users. This again points to the need to ensure they can maintain transparent communication and information flow. During the decision-making stage, for example, users tend to prefer availability and price first, since time pressures can influence a booking. Hip at this stage everyone, the app interface, driver ratings, and estimated arrival times, play a huge role in your choice. Yet that experience is often muddied by unpredictable fare fluctuations, delays and unresponsive customer service, all of which erodes trust and pushes some users to competitors. Once they are done with an experience, this post-experience stage will provide important insights into their long-term involvement. They can also serve up satisfied users, who turn into active promoters sharing positive reviews and encouraging others to install the app. By contrast, users who experience recurring problems — like overcharging, impolite or unprofessional drivers, or problems with complaints going unanswered — are more likely to vent publicly about their frustrations. Such negative narratives have a multiplicative effect on brand goodwill and highlight systemic failures in service recovery processes. The analysis finds that even though Yassir manages to attract a wide range of users with high visibility and low-price posting offers, it fails to provide a consistently reliable and transparent service. To improve the end-user experience and gain user loyalty, the platform needs to take some tangible actions: clear pricing structures, increased driver accountability, faster response to user complaints and effective loyalty programs targeting users with consistent usage. They're not just important for addressing the gap between promise and performance, but also for turning transactional interactions into deep and durable customer relationships. By adapting, Yassir stands to further consolidate its competitive edge while building deeper levels of trust and satisfaction among its users.

This study examines the possibilities of enhancing relationship between external factors and five main steps of the customer journey influence on brand trust. Our aim is to fill a gap of empirical studies on the online channel in Thailand. We identify four external factors that contribute to each step of customer journey base on customer journey map theory. Data collected from 400 respondents was tested against the research model using a partial least squares (PLS) approach. Our hypotheses testing the determinants set of the customer journey with a statistical inferential analysis that, show the results support 7 of the 9 hypotheses, with a significant relationship between analysed constructs (Social influencer, eWom, and Marketing campaign) which are the factors that might contribute to online customer journey at the present.

The growing role of digital platforms in educational marketing has transformed how parents engage with schools before making enrollment decisions. Previous studies have examined social media as a tool for branding and communication, yet few have explored its function as structured touchpoints within the customer journey of parents. This study introduces the ACDAL framework (Awareness, Consideration, Decision, Action, and Loyalty) to map parental engagement across different stages of school choice. Using a qualitative case study approach, data were collected from seven parents and documentation of Facebook and Instagram content published by a private junior high school in Tasikmalaya, Indonesia. Data were analyzed through content analysis to identify patterns of interaction between parents and school-generated content. The findings suggest that awareness is primarily stimulated by academic achievements and visually appealing content; consideration emerges through testimonials and program highlights; decision-making is influenced by responsive communication and transparent information; action is reflected in online and offline enrollment; and loyalty is strengthened by continuous publication of student activities and achievements. These results indicate that social media content functions as critical digital touchpoints along the parental customer journey. The study contributes to the literature by extending the customer journey model to educational settings using ACDAL and offers practical insights for schools seeking to design effective social media strategies to attract and retain parental trust.

Technological developments accompanied by increasing population growth rates in Indonesia affect people's lives in meeting their daily needs. With e-commerce that is present as an innovation in the use of technology and internet network assistance, it makes it easier for people to buy and sell goods online. Shoppe is one of the e-commerce with the most sales and visitors in Indonesia as of 2022 according to a national survey conducted by BOI Research. This research was conducted to analyze and provide information about the influence of the customer journey map consisting of the stages of discovery, use, and loyalty with 5 dimensions of service quality Service Quality Method which includes reliability, responsiveness, assurance, empathy, and tangibles on customer strategy design retention on Shopee e-commerce. The results of this study obtained the results that there is a positive relationship between the discovery and use process on customer loyalty in making purchases. Companies can evaluate this stage in designing strategies to gain customer trust and loyalty in order to make repeat purchases.  

The rapid growth of online fashion makes live-streaming essential, yet research often overlooks the impact of the streamer’s “try-on” service on the viewer’s purchase journey. Grounded in information foraging theory, this study explores how the try-on services facilitate viewers’ transition from product search to evaluation, ultimately shaping their shopping behavior. Data were collected from 466 Chinese fashion live-streaming viewers and analyzed using partial least squares structural equation modeling (PLS-SEM). Additionally, importance-performance map analysis (IPMA) was employed to derive practical implications from the findings. This study reveals that while streamer attractiveness has an indirect effect on purchase intentions through emotional engagement, co-viewer involvement directly influences both emotional engagement and purchase intentions during the search phase. Furthermore, the ability to virtually examine products proves more influential than social pricing in determining how viewers evaluate product information. This research advances the theoretical understanding of live-streaming commerce by illuminating the complex interplay between streamer characteristics, viewer dynamics and purchase behavior. For practitioners, it offers evidence-based guidelines for fashion streamers to enhance viewer engagement and conversion rates through optimized try-on demonstrations and co-viewer interaction strategies.

This study aims to provide a comprehensive understanding of the needs, preferences, and behaviors of its target market in the Indonesian full-service restaurant (FSR) sector. Firstly, it seeks to map the customer journey of FSRs in the food supplies purchasing process, identifying key touchpoints, brand awareness levels, information sources, and factors influencing brand choice. Secondly, it evaluates the effectiveness of various digital marketing channels, such as social media advertising, search engine marketing, and email marketing, by analyzing cost-per-lead and conversion rates to identify the most efficient channels for acquiring new FSR customers for PT MBI. Finally, the research intends to develop a data-driven digital marketing strategy that optimizes customer interactions, enhance brand visibility, and improve lead generation at each decision-making stage to drive sales conversions and increase customer lifetime value. The results of this study show that the current focus of PTXYZin the FSR segment lies between two segments: Relationship-Driven Traditionalists and Hybrid Decision-Makers.

Observing customers is one of the methods to uncover their needs. By closely observing how customers use products, we can indirectly experience their interactions and gain a deep understanding of their feelings and preferences. Through this process, companies can design new products that have the potential to succeed on the market. However, traditional methods of customer observation are time-consuming and labor-intensive. In this study, we propose a method that leverages the analysis of online customer reviews as a substitute for direct customer observations. By correlating a customer journey map (CJM) with online reviews, this research establishes a verb-centric analysis that produces a CJM based on online review data. Various text analysis techniques were utilized in this process. When applying online retail site review data, our method of customer observation required one week. This proved to be more efficient in comparison with traditional customer observation methods, which typically need at least one month to complete. Additionally, we observed that the customer behavior-based VOC (voice of customer) identified during the CJM mapping process offers broad insights that are distinct from traditional product feature-centric review analyses. This behavior VOC can be effectively utilized for product improvement, new product development, and product marketing. To verify the usefulness of the behavior VOC, we asked product development experts to evaluate the quantitative analysis results of the same reviews. The experts evaluated the CJM as useful for product conceptualization and selecting technology priorities.

Understanding customer journal is so important for all the enterprises, especially for the servcie sector such as education, medical or others. The main content of the current paper is to analyze the case of website tuyensinh247.com through aidasra model and customer journey map of tuyensinh247.com with the qualitative research methodology by observing. And the application lessons are also mentioned in the final part of the paper.

We investigate how the perceived quality influences touchpoint performance to provide a more nuanced understanding for analysing customer journeys. To answer the research questions, a survey in a real life online setting was carried out. The setting contained complex service solutions that were offered in a business-to-business context. The quantitative study shows that the perceived quality of a website has an influence on consumers’ buying intention. This correlation increases as the customer journey progresses. The perceived quality influences the website’s impact on visitors’ buying intention with a medium to strong effect size and the influence of a website’s quality on the impact on visitors’ buying intention varies significantly at different customer journey phases. While extant research focusses either on customer experience at touchpoints or touchpoints’ effects on buying behavior, we combine insights from both streams of research to highlight the role of website quality in determining touchpoint performance along the customer journey. Practitioners can use these insights to allocate resources in marketing and sales more efficiently.

The rapid shift toward social commerce and omnichannel retailing has reshaped how consumers discover, evaluate, and purchase silver products, particularly 925 silver jewelry and gift-oriented accessories. Uncertainty related to authenticity, finishing quality, sizing, and maintenance increases perceived risk and makes trust a critical mechanism for conversion and loyalty. Objective: This study aims to formulate and empirically test an integrated marketing strategy for silver sales by (1) mapping the customer journey, (2) identifying key drivers of trust formation in social commerce, and (3) examining how trust translates into purchase and repurchase intentions under conditions of perceived price fairness. Methodology: A quantitative explanatory design was applied using an online survey of 200 valid respondents who had interacted with or purchased from a Jakarta-based silver brand (SilverLine Jewelry) through Instagram/TikTok, Shopee, and WhatsApp Business. Data were analyzed using SEM-PLS to evaluate measurement quality and test relationships among information quality, seller communication, eWOM/UGC exposure, live streaming experience, transaction security perception, trust, purchase intention, repurchase intention, and perceived price fairness. Findings: The silver customer journey is video-led at awareness (TikTok and Instagram dominate discovery), trust-led at consideration (reviews/UGC and direct chat are pivotal), and marketplace-led at conversion (marketplace checkout is most preferred), with after-sales requests forming a meaningful post-purchase touchpoint. Trust is strongly explained by controllable social commerce factors, with seller communication and information quality as the most influential drivers, followed by transaction security, while eWOM/UGC and live streaming provide significant incremental effects. Trust is the strongest predictor of purchase intention; purchase intention predicts repurchase intention; and trust also has a smaller direct effect on repurchase, indicating partial mediation. Perceived price fairness strengthens the effect of trust on purchase intention. Implications: The findings support a “trust-bundle” strategy combining transparent product specifications, responsive interaction, secure checkout options, structured social proof (UGC/reviews), live demonstrations, and standardized after-sales services (polishing/resize), reinforced by consistent fairness-oriented value communication. Originality: This research operationalizes the customer journey into a silver-specific configuration and integrates trust formation, conversion, loyalty, and price fairness within a single tested model, offering category-tailored guidance beyond generic social commerce studies.

The purpose of this article is to verify the impact of missing the earned media and category media in multichannel conversion attribution models on digital media budget allocation. The analysis is based on a very unique approach: 532 users who declared their will to purchase a selected product in the next 3–5 months agreed to install special addons on all their devices connected to the Internet. These devices will register all the users’ activities throughout three months. All user activities on the path to purchase were extracted by means of text mining (URL analysis) techniques. Finally, 5171 activities were found and assigned to particular media areas and media channels. The average user spends 20 per cent of his time in the paid media and owned media areas. However, from the point of view of the number of touchpoints, 29 per cent of the activities occur in these two areas. The obtained results clearly show how much of consumers’ activity in the decision-making process is beyond the control of marketers who, on the basis of this partial data, have to make daily decisions about allocating advertising budgets. The study compared the results of conversion attribution for the full funnel (paid media, owned media, earned media, category media) with the conversion attribution based only on paid media and owned media. The results indicate that not all attribution models lead to similar conclusions in both approaches.

No abstract available

This study explores the development of a comprehensive customer journey framework within the context of immersive virtual reality (iVR) shopping environments. The research question focuses on recommending an effective customer journey that encompasses various touchpoints and purchase phases in iVR retail. A thorough literature review was conducted to identify existing touchpoints in the literature and to recognize additional touchpoints relevant to physical and online retail contexts. The findings led to the formulation of a novel customer journey framework specifically tailored for iVR shopping experiences. The framework emphasizes the integration of diverse touchpoints and purchase phases, enabling retail businesses to enhance customer experiences (CX) and make informed decisions. The practical implications of the customer journey framework lie in its ability to guide retail businesses in optimizing the customer experience in iVR environments. Furthermore, the study contributes to the theoretical discourse surrounding human-computer interaction and customer-centric design. By embracing this customer journey framework, businesses and researchers can collaborate to drive innovation and create more immersive and engaging iVR retail experiences. Overall, this study provides valuable insights and guidance for designing a comprehensive customer journey in the emerging domain of iVR shopping.

: With the rapid increase in international trade, research on the factors influencing customer satisfaction in cross-border e-commerce is essential to improve the online shopping experience. This article presents a literature review on cross-border e-commerce customer satisfaction and uses the Customer Journey Map to analyse the entire purchase process of cross-border businesses. It then puts forward hypotheses and creates an empirical model of customer satisfaction in cross-border e-commerce based on these findings. Next, data is collected through a questionnaire survey of 327 overseas consumers, and SPSS is used to analyse the data. The study concludes that five factors affect customer satisfaction in cross-border e-commerce: the reputation of cross-border platforms, services, cross-border payment convenience and safety, logistics, and perceived value.

No abstract available

Consumer journey analysis led to efficient marketing implementation. A journey represents a path of steps and interaction between consumer and service units at each touchpoint. Dissatisfaction in the touchpoint, causes a negative effect to retain a customer. Previous studies always constructed the journey maps relied on the narrative approach. According to use Google, consumers always face massive websites to access, which is a pain point in the journey. Improving consumer buying, led to the research aims: identifying consumer needs, and reducing SEO pain-point using content relevance indexing. The data (social media posts from the Thai beauty communities in the year 2020) is analyzed and has found that there are two need types: curative and preventive. The study can segment the 150 websites into four groups which reduce the search space. Moreover, the significant words from the wrapping technique can use to create keywords in the homepage introduction that are matching the products to consumer needs.

In the digital age, retailers face umpteen challenges, finding it increasingly difficult to fulfil the customer requirements. Studying the most trusted online stores in Romania, the authors aimed to identify the opportunities and the challenges for retailers in the connected consumer’ journey, analyzing the page load speed of the in-between touchpoints in the pre-check-out phase on smartphones. In this regard, comparative analysis and content analysis were performed, taking into consideration eight performance indicators, namely, first content paint, first input delay, largest contentful paint, cumulative layout shift, performance score, speed index, time to interactive, and total blocking time. Three platforms were used to run the tests, the generated data allowing the identification of the necessary enhancements to ensure a continuous consumer journey. The study revealed that the selected in-between touchpoints need major improvements to provide a satisfying consumer experience on a smartphone. The scientific contribution of this article consists of presenting 14 opportunities designed for retailers. By implementing them, for every 0.1 s saved, the conversion rate can increase by 8% due to emotional mitigation with technological performance improvements. The page speed shapes the customer journey, the retailers gaining the users’ trust by avoiding a long waiting time between the touchpoints.

Purpose The aim of the paper is to address the persistent uncertainty surrounding the effectiveness of chatbot-led service failure recovery (SFR) in delivering a satisfactory online customer experience. Prior studies have not explored how chatbot-led SFR processes influence customers’ actual experiences. This gap in the literature may exist because current understanding of chatbot–customer interactions obscure how individuals’ adoption of chatbot-led SFR shape their experiences. Design/methodology/approach Drawing on frustration–aggression theory and signaling theory, and building on a social constructivist philosophical paradigm, this paper interprets participants’ narratives on chatbot-led interactions and online experiences. Empirical data was generated through 52 in-depth interviews conducted with participants from the USA, France, Italy, and the UK. Findings Through thematic analysis of interview data, the study presents two key contributions. First, this paper elucidates the dynamics unfolding between customers and chatbots in a service recovery journey, encompassing customers’ priorities and expectations. Second, this paper delineates three customer typologies based on their interactions with chatbots during chatbot-led SFR, including their emotional responses. These interactions could either positively or negatively signal future patronage of chatbots. The identified three customer types can assist managers to reshape their strategies to effectively turn negative customer experiences into opportunities for enriching online customer experiences. This could involve providing multiple touchpoints, including human-led and chatbot-led interactions in the SFR process. Originality/value This study proposes that chatbots are not just technological tools that support customers during service failures and facilitate connection with the brand, but also function as signals that trigger emotional and cognitive responses, thereby influencing the customer experience.

Customer journey analysis aims at understanding customer behavior both in the traditional offline setting and through the online website visits. Particularly for the latter, web analytics tools like Google Analytics and customer journey maps have shown their usefulness, by being widely used by web companies. Nevertheless, they provide an oversimplified version of the user behavior in addition to other limitations related to the narrow scope over the cases. This paper contributes a novel approach to overcome these limitations by applying process mining and recommender systems techniques to web log customer journey analysis. Through our novel approach we are able to (i) discover the process that better describes the user behavior, (ii) discover and compare the processes of different behavioral clusters of users, and then (iii) use this analysis to improve the journey by optimizing some KPIs (Key Performance Indicators) via personalized recommendations based on the user behavior. In particular, with process mining it is possible to identify specific customer journey paths that can be enforced to optimize some KPIs. Then, with our novel, sequence-aware recommender system, it is possible to recommend to users particular actions that will optimize the selected KPIs, using the customer journey as an implicit feedback. The proof of the correctness of the introduced concepts is demonstrated through a real-life case study of 10 million events representing the online journeys in 1 month of 2 million users. We show and evaluate the discovered process models from this real web log, then use the extracted information from the process models to select and optimize a KPI via personalized recommendations.

This study investigates the main touchpoints customers value most when shopping online and their attitudes towards them, using Ocado’s customer reviews as a case study. The analysis identified seven critical touchpoints across pre-purchase and post-purchase stages by employing machine learning and deep learning methods, such as word2vec, CNN-based sentiment models, and embedding-based topic models. Recommendations were provided regarding promotional opportunities, technology utilization, and customer experience creation, highlighting the need for different strategies based on customer stages in their journey. The findings offer valuable insights for retail companies transitioning to digital platforms, emphasizing the importance of understanding customer needs and prioritizing touchpoints. Future research could explore additional retail companies with various channels and incorporate different types of customer views to provide a broader perspective on touchpoints.

No abstract available

The article examines digital marketing as a tool for building sustainable consumer loyalty in the digital economy. The purpose of the study is to substantiate scientific and methodological approaches to the use of digital communication channels in the process of increasing customer engagement, quantify their impact on the main indicators of interaction and develop recommendations for the creation of adaptive loyalty programs. To achieve this goal, we analyzed modern digital marketing tools, including social networks, content marketing, push notifications, omnichannel solutions and CRM systems, and studied the quantitative effects of their use in Russian practice. The results of the study showed that the integrated use of digital tools ensures a 20-30% increase in conversion, an 11-15% increase in the average receipt, a decrease in customer churn and an increase in LTV. Based on the analysis, a KPI system is proposed for monitoring the effectiveness of marketing campaigns and a loyalty model that includes personalization of offers, gamification, and the use of big data analytics. The scientific novelty of the work consists in the systematization of quantitative indicators of the impact of digital marketing and the development of recommendations for the integration of loyalty programs into the strategy of companies. The practical significance of the research lies in the possibility of applying the developed approaches in order to increase business competitiveness, improve customer experience and ensure long-term growth.

In the rapidly shifting landscape of digital marketing and tailored services, identifying and responding to high-intent user micro-moments has become a necessity for user activation and conversion maximization. Existing deep learning techniques such as single CNNs, LSTMs, and transformer models are promising but are either temporally weak, non-interpretable, or resource-intensive. This paper proposes a novel Attention-Augmented LSTM for Micro-Moment Detection (AALSTM-MM) that integrates behavioral clustering, sessional temporalization, and attention-augmented LSTM network to effectively learn sequential dependencies and intent signals of user browsing sessions. The designed model was experimented and verified against a benchmark e-commerce user session dataset with 92.3% accuracy, 91.7% precision, 90.8% recall, 91.2% F1-score, and an AUC of 0.948. Above all, it posed a low inference latency of 42 milliseconds and therefore was feasible for real-time application. In addition, attention visualizations and behavior clustering ensured interpretability and pattern insights to make decision-making more transparent. This paper delivers a robust, scalable, and interpretable model capable of inferring micro-moment behavior at scale with high accuracy and low latency. Its use cases are in real-time user intent prediction industries such as advertising, recommender systems, and intelligent customer service. The strengths of modeling accuracy, efficiency, and interpretability merge to make AALSTM-MM a significant step toward human-centered, smart digital interaction systems.

Recent studies investigate the fundamental influence of Artificial Intelligence on UAE digital marketing practices designed to maximize customer acquisition. The rising dependence on automated systems and learning models and data-driven automation has led businesses in the UAE to implement AI systems to build personalized consumer transactions and optimize promotional activities along with demand forecasting. AI achieves confirmed benefits with its own methods yet its power to transform real customer acquisitions depends on predictive analytics as an intermediary solution. The present research evaluates predictive analytics because it functions as an essential interconnection between AI systems and improved customer conversion rates. A survey research design involving 287 marketing leaders and digital strategy experts operating in different industries throughout the UAE will be utilized for data collection. The SEM modeling analysis will evaluate the direct relationships as well as the mediating relationships present in the dataset. This research will deliver extensive evidence regarding how AI systems unite with predictive analytics to generate loyal customers in the UAE digital marketplace.

This research decisively establishes the influence of digital marketing on the marketing performance of Small and Medium Enterprises (SMEs) in the food sector of Jepara Regency, underscoring the critical mediating roles of customer engagement and relationship marketing. Employing a robust quantitative methodology with Structural Equation Modeling (SEM), analyzed through SmartPLS version 4.0, questionnaires were distributed to 150 SME owners in the food sector. The results indicate that while digital marketing does not directly enhance marketing performance, customer engagement and relationship marketing are vital mediators that significantly strengthen this connection. This reinforces the notion that cultivating high levels of customer engagement and fostering strong relationships are essential for maximizing the effectiveness of digital marketing strategies. Consequently, this research provides crucial insights for SMEs, highlighting the challenges inherent in digital marketing implementation and the urgent need for a comprehensive approach to elevate their marketing performance.

The evolution of digital marketing has been significantly influenced by advancements in Artificial Intelligence (AI) and Social Media Analytics (SMA). Businesses are leveraging AI-driven solutions to enhance customer engagement, optimize ad spending, and improve campaign effectiveness. This paper presents a comparative study of various Machine Learning (ML) algorithms applied in digital marketing campaigns. The study explores their predictive accuracy, scalability, and efficiency in processing social media data to generate actionable insights. By examining AI-driven methodologies, this research highlights the most effective strategies for optimizing digital marketing efforts and provides a framework for businesses to enhance their marketing performance through intelligent automation and data-driven decision-making.  This research paper explores the role of Artificial Intelligence (AI) in optimizing digital marketing campaigns using social media analytics. The study compares various machine learning algorithms to determine their effectiveness in enhancing marketing strategies, improving customer engagement, and increasing conversion rates. By leveraging AI-driven insights, businesses can make data-driven decisions to maximize their marketing impact. The research aims to identify the most efficient algorithms for predictive analytics, sentiment analysis, and customer segmentation in digital marketing. In the era of digital transformation, Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing digital marketing (DM) campaigns by leveraging big data and advanced analytics. The vast availability of big data from social media platforms provides businesses with valuable insights into consumer behavior, preferences, and engagement patterns. The importance of AI-driven tools in DM campaigns lies in their ability to enhance targeting, personalization, and automation, leading to more effective marketing strategies. ML algorithms play a crucial role in forecasting campaign success by analyzing historical data and identifying (KPIs) that influence outcomes. Through predictive analytics, businesses can optimize their strategies, improve campaign efficiency, and maximize (ROI). This study explores the impact of AI and ML in digital marketing, comparing different algorithms and their effectiveness in campaign optimization. By utilizing AI-powered analytics, organizations can make data-driven decisions, refine their marketing efforts, and stay competitive in an evolving digital landscape.

The incorporation of Artificial Intelligence (AI) is rapidly advancing and significantly shaping consumer purchasing behavior and marketing approaches. This research examines AI's role in increasing the understanding of consumer preferences and digital marketing performance within Pakistan. Despite the potential of technologies such as analytics, machine learning, and recommender systems to enhance personalization, process automation, and user engagement, their application in moderating social media platforms remains underexplored. This study examines the effect and role of Artificial Intelligence (AI) on consumer‐buyer behavior and digital marketing, with a key moderating variable being social media. The study, based on the Technology Acceptance Model (TAM), aims to investigate the impact of AI‐based technologies on consumer decision‐making, which promotes personalization and effectiveness in marketing. Data was collected from 658 Foodpanda users in Pakistan to complete a structured online survey with some standard Likert‐scale measurement items. The findings indicate that significant and positive relationships exist among AI, consumer purchasing behavior, digital marketing, and social media engagement. The consumer's purchasing behavior to purchase a product mediates the connection between AI and digital marketing, and social media amplifies the effects of consumer behavior on marketing performance. This study is beneficial to both theory and practice since it validates the theory of TAM in an AI‐driven marketing setting and provides practical steps targeted towards those marketers who want to maximize campaigns via AI and social media. There are also limitations and areas of future research discussed.

In this empirical study, we delve into engineering hyper-personalization within AI-driven digital marketing management. We focus specifically on the software challenges encountered and their impact on brand performance. AI technologies are truly transforming marketing, offering capabilities like precise customer segmentation, personalized content delivery, and real-time analytics – essential tools for achieving hyper-personalization. While AI holds significant promise for creating highly relevant and effective campaigns, implementing it for hyper-personalization brings distinct software-related challenges. These include navigating data privacy, ensuring algorithmic transparency, and addressing biases. Overcoming these engineering obstacles becomes essential for leveraging AI effectively to enhance customer experiences, optimize campaign results, and ultimately build stronger brand loyalty and visibility. Our study offers insights into these specific challenges and their implications for businesses aiming to maximize brand performance through advanced AI personalization.

This research analyzes the comparative effectiveness of digital marketing through Instagram and TikTok platforms in the food and beverage retail sector using a quantitative survey-based approach involving 50 business owners. The research objective is to identify the strategic advantages of each platform based on three key indicators: Engagement Rate, Reach, and Conversion Rate. Descriptive analysis results demonstrate TikTok's superiority in Engagement Rate (8.7% vs 5.2%) and Conversion Rate (3.8% vs 2.1%), while Instagram excels in Reach (12,000 vs 9,500). Multiple linear regression analysis confirms the significant influence of all three indicators on digital marketing effectiveness, with Conversion Rate as the dominant predictor (β=0.41), followed by Engagement Rate (β=0.38) and Reach (β=0.29). The constructed model shows substantial predictive power (R²=0.72). The findings suggest differentiated marketing strategies based on each platform's unique characteristics, with TikTok optimized for interaction and conversion through interactive and trend-responsive content, while Instagram focused on maximizing reach through premium visual content and e-commerce integration. The implications of this research contribute to the development of a data-driven strategic framework for optimizing digital marketing resource allocation.

This study aims to analyze the influence of digital marketing strategies through social media on consumer purchase decisions. The research method used is a quantitative approach with survey techniques. Data was collected through an online questionnaire from 200 respondents who actively used social media. The results of the study show that content elements, interaction and consumer trust have a significant influence on purchase decisions. This finding provides important implications for the Company to maximize the use of social media as the main marketing platform.

IntroductionBig data analytics and machine learning have transformed digital marketing by enabling data-driven insights for personalization. This study investigates the role of engagement metrics, sentiment analysis, and consumer segmentation in enhancing marketing effectiveness. Specifically, it examines how these technologies process consumer interaction data to uncover actionable insights, segment audiences, and drive purchase conversions.MethodThe study employed a mixed-methods approach, integrating big data analytics and machine learning techniques. Descriptive statistics highlighted engagement patterns, while k-means clustering segmented consumers based on behavioural and emotional data. Sentiment analysis, conducted using Natural Language Processing (NLP), captured consumer emotions as positive, neutral, or negative. Regression analysis evaluated the influence of social media activity, click-through rates, session duration, and sentiment scores on purchase conversion rates.ResultsDescriptive analysis revealed significant variability in consumer engagement and sentiment, with 37.5% of consumers expressing positive sentiment. Clustering identified three distinct consumer segments, reflecting differences in engagement and sentiment. Regression analysis showed that sentiment had a positive but statistically insignificant relationship with purchase conversions, while other metrics, such as click-through rates and session duration, exhibited minimal impact. The overall explanatory power of the regression model was low (R-squared = 0.001), indicating the need for additional factors to understand purchase behaviour.ConclusionThe findings emphasize the potential of big data analytics and machine learning in consumer segmentation and sentiment analysis. However, their direct impact on purchase conversion is limited without integrating broader variables. A holistic, adaptive framework combining behavioural, emotional, and contextual insights is essential for maximizing marketing personalization and driving outcomes in dynamic digital environments.

This present study dwells on the effectiveness of digital marketing campaigns on social networks in Saudi Arabia, focusing on user sentiment, metrics of engagement, and the role of local influencers. The research study focuses on the content of the posts from platforms such as Facebook, Instagram, Twitter, and YouTube by combining sentiment analysis, text mining, and NLP. The results show that from the sentiments, engagement is highly positively correlated; hence, posts that trigger positive emotions have drastically higher interaction rates. Facebook and Instagram are the most engaging channels, while Twitter presented more critical sentiment that requires another way of engaging. This analysis has identified Saudi influencers and the cultural aspect as very important in setting the success of any campaign. On the other hand, the posts of local influencers were more positive in sentiment and ensured higher engagement, indicating the importance of culturally relevant marketing. Temporal engagement, however, was different over time, reaching its peak on events such as the launch of a product and promotion by an influencer. The study concludes that the brands targeting Saudi audiences should employ content most likely to yield positive sentiment, partner with local influencers, and monitor the campaign performance in real time to maximize engagement and guarantee success.

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In digital marketing, optimizing advertisements (ads) to drive engagement and revenue requires creative, adaptive strategies. Despite numerous deterministic methods, accurately placing ads based on user-specific searches remains challenging. Thus, this paper evaluates Multi-Armed Bandit (MAB) algorithms for ad selection, focusing on the Upper Confidence Bound (UCB) and $\boldsymbol{\varepsilon}$-Greedy algorithms to optimize click-through rates and engagement by balancing exploration and exploitation to maximize rewards. To assess the algorithm’s use under different epsilon values, key metrics such as total rewards, regret, and selection accuracy are checked. Over 10,000 iterations, UCB achieved the highest average reward of 0.08 and the lowest total regret of 114, with a selection accuracy of 81.15%. In comparison, Random Selection and EpsilonGreedy methods yielded average rewards of 0.053 and 0.067, regrets of 304 and 175, and selection accuracies of 19.58% and 60.09%, respectively. The results indicate that UCB offers the best exploration-exploitation trade-off. With practical insights for real-time ad placement optimization, this all-encompassing method highlights the revolutionary potential of reinforcement learning in digital advertising.

In the era of globalization and digital transformation, many businesses face challenges in maximizing the potential of digital marketing, including CV. Hayat Handayani, which previously experienced limited market reach and stagnant customer interactions. This situation prompted the need to evaluate the effectiveness of the company's digital marketing implementation. This study aims to assess the extent to which digital marketing strategies can support improved business performance. The research method used a qualitative approach through in-depth interviews with three informants. The results showed that digital marketing provided significant improvements in several indicators, such as sales growth in the first three months, expanding audience reach outside the region, and increasing social media interactions. Analysis based on the AIDA model showed that the Awareness and Interest stages were the most dominant aspects, driven by the use of visual content, paid advertising, and collaboration with local influencers. Meanwhile, the Action stage still requires strengthening the consistency of purchase calls and optimizing transaction features. This study concluded that digital marketing implementation has been effective, but still requires strategic improvements to achieve more optimal results. These findings are expected to serve as a reference for companies in developing more targeted digital marketing strategies.. Keywords —Effectiveness, Implementation, Digital Marketing

With the continuous development of technology, traditional marketing methods no longer meet the needs of the main forces of social consumption, and people urgently need more innovative and personalized marketing strategies. E-commerce companies must develop a comprehensive customer-oriented marketing strategy based on big data and multi-channel to achieve their long-term healthy development. This paper first investigated the impact of the digital economy on e-commerce enterprises, focused on the transformation of the digital economy on the marketing model, expounded the development analysis of e-commerce in the digital economy era, and described the development trend of e-commerce marketing in the digital economy era. Then, this paper expounded the current problems faced by e-commerce enterprises, and discussed the lack of integrity, homogeneity, large-scale marketing strategies, and the lack of analysis and application of big data. After that, this paper put forward the marketing strategy of e-commerce enterprises in the digital economy era, and studied it from three aspects, namely, building a reasonable product management structure, marketing strategy based on customized marketing content, and social media marketing strategy based on information sharing. Then this paper proposed to use genetic algorithm to strengthen the marketing strategy of e-commerce enterprises. Finally, based on experiments and surveys, this paper used genetic algorithms to strengthen the construction of e-commerce enterprise marketing strategy in the digital economy, and concluded that the new e-commerce enterprise marketing strategy was 21% more satisfactory than the traditional new e-commerce enterprise marketing strategy. Through comparison, it can see that the integrity of the marketing plan of the new e-commerce enterprise's marketing strategy was 0.33 higher than that of the traditional e-commerce enterprise's marketing strategy, and the integrity of the promotion strategy was 0.34 higher than that of the traditional e-commerce enterprise's marketing strategy. After using the new e-commerce enterprise marketing strategy, the improved management structure was 0.29 higher than that of the traditional monitoring system, and the high quality of products was 0.18 higher than that of the traditional system.

Digital strategy represents an inevitable requirement for superiority in a digital world (Menz et al., 2021; Turuk, 2020). More precisely, this study aimed to determine the key success factors (KSFs) of the digital marketing strategy that have an influential effect on the marketing performance of small enterprises (SEs) in Jordan. A theoretical framework has been proposed based on an extensive review of the related literature and the assumptions of the technology acceptance model (TAM). The study followed the quantitative approach, where intended data were gathered from 370 valid e-questionnaires based on the convenience sampling technique. Then, the collected data was statistically analyzed using the AMOS V.23 program. The findings of the research pointed out e-marketing orientation as a prominent KSF for SEs and recommended that such orientation deserves to be positioned at the heart of the digital strategy to drive success. In addition, the findings confirmed the indirect effect of customer awareness and consideration in the relationship between digital marketing applications and performance. Customer awareness and consideration need to be given more attention while developing SEs’ digital marketing model, as it plays a pivotal role and constitutes a crucial mediating variable between each of the digital strategy variables and the targeted performance of small enterprises (PSEs).

This study examines the impact of digital marketing strategies through e-commerce, social media, and influencer marketing on emotional resonance and customer loyalty among Generations Z and Y, as well as the moderating role of digital literacy. A quantitative approach was employed using an online survey of 300 respondents from Generations Z and Y. Data were analyzed using structural equation modeling–partial least squares (SEM-PLS). The findings indicate that digital marketing strategies across the three channels significantly enhance emotional resonance and customer loyalty. Furthermore, digital literacy is shown to strengthen the relationship between digital marketing strategies and both emotional resonance and customer loyalty. These results offer practical implications for micro, small, and medium enterprises (MSMEs) in designing effective digital marketing strategies aligned with the characteristics of Generations Z and Y, while also emphasizing the importance of improving customer digital literacy to foster trust and emotional attachment to brands. This study contributes to the literature by proposing a framework that positions digital literacy as a moderating variable in the relationship between digital marketing strategies, emotional resonance, and customer loyalty, providing insights for MSMEs, digital marketers, and policymakers in promoting sustainable customer engagement in the digital era.

During digital transformation, AI-powered marketing plan optimization gives the organization a competitive edge. Machine learning models improve consumer targeting, campaign targeting, ROI, and campaign likelihood in this study. We tested these methods using two real-world datasets and supervised learning algorithms like Logistic Regression, Decision Trees, Random Forest, and XGBoost. The data was imputed, one-hot encoded, normalized, and feature-selected to improve model accuracy and relevance. With an accuracy of 90.3% and an AUC-ROC score of 0.927, XGBoost surpasses all models in high-dimensional, difficult-to-characterize marketing data. The report also examines AI adoption's ethical issues, including data protection and model interpretation.

The development of digital technology is driving a major transformation in marketing strategies, one of which is through the integration of Artificial Intelligence (AI)-based chatbots in the e-commerce sector. This research is motivated by the need for skincare e-commerce to increase customer engagement, accelerate sales conversion, and build loyalty through a more personalized and efficient approach. This study aims to analyze the effect of AI chatbot integration in digital marketing strategies on customer engagement, sales conversion, and customer loyalty in the skincare e-commerce industry. The research method uses a descriptive qualitative approach with data collection techniques through in-depth interviews, observation, and documentation on several skincare e-commerce in Indonesia. Data were analyzed using the Miles and Huberman interactive analysis model, which includes data reduction, data presentation, and conclusion drawing. The results showed that the integration of an AI chatbot was able to increase the average duration of customer interactions, accelerate the buying process by increasing the conversion rate from 2.3% to 5.7%, and strengthen customer loyalty through data analytics-based personalization services. AI chatbots play an important role in optimizing the customer journey in a faster and more relevant way. The conclusion of this study confirms that the use of AI chatbots can be an effective strategy in strengthening the competitive position of skincare e-commerce in the digital era. The practical implications of this research encourage companies to develop chatbots based on customer behavior analytics and pay attention to customer data security aspects.

Digital transformation, as a critical necessity, has confronted Iran's banking industry with new challenges and opportunities. This study aimed to propose a model for assessing the maturity of digital transformation in Iranian banks using a qualitative and exploratory approach. Data were collected and analyzed through semi-structured interviews with 25 banking industry experts (with postgraduate education and a minimum of 10 years of work experience) using the thematic analysis method. The interview framework was designed based on an extensive review of the literature, and sampling was conducted through a purposive (snowball) method. The final model consists of six main categories (technology and infrastructure; processes and operations; customer experience; data governance and security; digital strategy; and culture and human resources), 30 subcategories, and 139 basic themes, offering a comprehensive explanation of digital maturity. The findings revealed that culture and human resources, along with customer experience, are among the most influential dimensions, while processes and operations require further improvement. Barriers such as inadequate infrastructure and a lack of digital culture have hindered the advancement of digital banking. Recommendations include strengthening digital skill training, enhancing customer experience through an omnichannel approach, and developing a strategic roadmap. This localized model can serve as a framework for evaluating and guiding Iranian banks toward digital maturity and enhancing competitiveness in the digital era.

Content Marketing Optimization to Increase Consumer Engagement at Brand Necerel on Instagram Platform. Introduction, Marketing 4.0 provides an important role for marketers to guide the customer journey from the initial stage to the final stage. Content Marketing is a marketing strategy that ensures definite identification with strong analysis to attract the attention of potential customers distributed through digital media. The main purpose of implementing content marketing is to increase customer engagement. Methods: MBKM Independent Internship activities for students of the National Development University “Veteran” East Java at Qurota Academy as Digital Marketers at @Necerel.id began on February 19 - June 19, 2024. Internship activities are carried out face-to-face (Offline) at the Office located at Jalan Selat Karimata Block E3/1, Sawojajar, District. Kedungkandang, Malang City, East Java, 65139. The results of this study help optimize Content Marketing to Increase Consumer Engagement in the Brand Necerel on the Instagram platform.

This white paper explores the pivotal role of Customer Relationship Management (CRM) in the digital transformation journey of the chemical industry. As customer expectations continue to evolve and competition intensifies, chemical companies are turning to CRM solutions to enhance customer interactions, streamline operations, and drive business growth. The abstract provides an overview of CRM’s significance in the chemical sector, highlighting its role in customer segmentation, sales automation, marketing optimization, and customer service enhancement. By centralizing and optimizing customer-related processes, CRM enables chemical companies to deliver personalized experiences, improve sales productivity, and foster stronger customer relationships. Through a comprehensive examination of CRM implementations and potential applications in the chemical industry, this white paper aims to provide valuable insights for industry professionals seeking to leverage CRM to navigate the challenges and opportunities of the digital age.

This research examines the implementation of marketing automation technologies in optimizing various customer journey touchpoints within e-commerce contexts. Through a comprehensive analysis of peer-reviewed articles from the Scopus database spanning 2020-2024, this study explores how marketing automation, particularly programmatic marketing, leverages advanced data analytics and machine learning to personalize customer interactions and optimize marketing effectiveness. Our systematic review reveals three key findings. First, the strategic implementation of marketing automation significantly enhances revenue generation through improved customer data analytics, predictive modeling, and dynamic pricing strategies, with studies showing increased conversion rates and higher customer lifetime value. Second, marketing automation demonstrates substantial impact on customer retention by enabling personalized experiences and proactive engagement, leading to increased customer satisfaction and loyalty. Third, successful implementation of marketing automation requires robust technological infrastructure, organizational alignment, and continuous optimization of marketing processes. The analysis also highlights that effective integration of predictive analytics and personalization plays a crucial role in driving customer engagement, while the combination of social media analytics and game theory provides businesses with comprehensive frameworks for optimizing competitive strategies. This review contributes to the existing literature by providing a systematic understanding of marketing automation's role in the e-commerce customer journey, highlighting key success factors, implementation challenges, and emerging trends in the field. The findings offer valuable insights for practitioners and researchers interested in leveraging marketing automation for enhanced business performance and competitive advantage in the rapidly evolving e-commerce landscape.

This study examines how the customer journey, with its various elements, influences sustainable marketing practices. It also examines the moderating effect of digital social media on this relationship. A questionnaire was used to collect data from eight restaurants located in Anbar, Iraq, which are known for their advanced services. A PLS-SEM model was used to analyse data from a sample of 379 questionnaires distributed to customers of the selected restaurants. The results indicated that customer journey elements (staff interaction (SI), merchandise assortment (MV), shop atmosphere (SA), repatriation intentions (RI), and value experienced (VE)) play a crucial role in promoting sustainable marketing practices in restaurants. Of the six indirect effect hypotheses, three were supported, namely the moderating role of digital social media between (shop atmosphere, repatriation intentions, and value experienced) and sustainable marketing. To achieve optimal levels of marketing sustainability, effectively integrating digital social media into sustainability programs requires original thinking and innovative solutions. Restaurants can improve their sustainability levels by paying closer attention to customer journey elements to predict customer behavior and meet future needs.

The development of digital platforms in the mental health sector has shown significant growth, along with increasing awareness among younger generations regarding the importance of self-reflection and psychological well-being. One type of service with the potential to address these needs is digital journaling platforms. However, at the pre-launch stage, the main challenge faced by digital platforms lies not only in feature design, but also in building brand awareness from the outset through digital marketing strategies that are relevant to the needs of potential users.This study aims to design a digital marketing strategy based on consumer insight, customer journey, and value proposition at the pre-launch stage of the PelanPelan digital journaling platform. The study adopts a descriptive qualitative approach involving potential users from Generation Z aged 20–28 years. Data were collected through semi-structured interviews and open-ended surveys. The data were analyzed using thematic analysis to identify consumer insights, construct a conceptual customer journey, and formulate a value proposition as the foundation of the digital marketing strategy.The findings indicate that potential users perceive journaling as a tool for emotional regulation and self-reflection, yet still experience adoption barriers at the awareness stage. Based on these findings, pre-launch digital marketing strategies should focus on empathetic, simple, and emotionally driven communication to build contextual brand awareness.

In the rapidly evolving landscape of semiconductor manufacturing, this research paper explores the application of pivotal digital marketing trends and strategic innovations to reshape contemporary business strategies within the industry. Recognizing the significance of staying at the forefront of these transformations, our study aims to provide a nuanced understanding of three prominent digital marketing innovations: Influencer Marketing, Artificial Intelligence (AI)-driven Customer Support, and Voice Search Optimization. Through a rigorous methodology integrating literature review and case study analysis specific to semiconductor manufacturing in India, we unveil the successful implementation and tangible impact of these innovations on user engagement, brand perception, and overall marketing efficacy within the semiconductor sector of India. The research was done in 2022-2023 over the semiconductor companies working in India (HCL Technologies, Bharat Electronics Limited, ABB India Limited, Vedanta, CG Power and Industrial Solutions Limited, and Havells India Limited). Comparative analyses against traditional methods reveal significant improvements tailored to this industry: Influencer Marketing campaigns demonstrated a 25% increase in reach and engagement compared to conventional advertising. The integration of AI-driven Customer Support resulted in a 30% reduction in response time, enhancing customer satisfaction scores by 15%. Furthermore, Voice Search Optimization strategies yielded a 20% improvement in search accuracy, outperforming traditional text-based Search Engine Optimization (SEO) approaches within the semiconductor manufacturing context. Delving into challenges and opportunities associated with each innovation within the semiconductor industry, we provide evidence-based recommendations for businesses seeking to navigate the dynamic digital marketing landscape in this specialized domain. As semiconductor manufacturing continues to redefine its business ecosystem, embracing these innovations emerges as a cornerstone for sustained success in the digital era within this unique sector.

This study aims to provide an overview of the implementation of AI in Digital Marketing that has been carried out and how customer experience has been formed in the last 5 years. The main objective in this study is how AI methods and features are implemented in Digital Marketing and how customers respond to each feature implemented. We conducted the Systematic Literature Review methodology using PRISMA check sheet, we obtained 24 articles based on the criteria of the keyword customer experience AI Digital Marketing. The results of the study show that the use of AI in Digital Marketing is increasing, with personalization is the most used feature. AI in Digital Marketing improves customer experience in terms of customer satisfaction, purchase intention, and customer journey. Integrity and ethics in utilizing customer data in creating Digital Marketing strategies are the main concerns, since this has become a major factor in maintaining customer data privacy and maintaining customer trust.

Embracing Internet of Things (IoT) technologies presents significant opportunities for enhancing customer engagement. However, Tanzanian Small and Medium Enterprises (SMEs) are confronted with persistent challenges, including limited infrastructure, financial barriers, and low digital literacy. This study proposes an IoT-powered customer engagement platform built using Python-Django specifically tailored for Tanzanian SMEs to generate actionable customer insights and strengthen engagement strategies. A mixed-methods approach, combining surveys, observations, and interviews with SME owners and customers in Dar es Salaam and Arusha, revealed operational inefficiencies and gaps in customer interaction. Based on these insights, a scalable and cost-effective IoT solution was designed to automate feedback collection, monitor customer behavior in real-time, and deliver personalized services. The platform was evaluated through simulated testing, expert reviews, and performance analysis. Results showed a 15 - 20% improvement in customer retention, a 30% reduction in inquiry response time, 99.50% system uptime, and an 80% user-friendliness score. These findings demonstrate the novelty and effectiveness of integrating IoT, real-time monitoring, and marketing optimization in the Tanzania SME context. Overall, the research highlights the transformative potential of IoT in enabling data-driven decision-making, enhancing customer relationships, and promoting sustainable growth in underserved business environments.

Customer experience is central to omnichannel marketing and is increasingly the focus of research attention. However, few studies have focused on the development of excellent omnichannel customer experiences. To fill this research gap, we examined the drivers of these experiences from a customer journey design perspective. Partial least squares structural equation modeling (PLS-SEM) and partial least squares multigroup analysis (PLS-MGA) were employed to analyze 775 valid omnichannel customers’ data, which were collected through an online survey. The findings suggest that the thematic cohesion, consistency, context sensitivity, and connectivity of touchpoints play an important role in improving omnichannel customer experience. Value co-creation behavior can be significantly increased by affective, cognitive, physical, relational, and symbolic experiences, but not by sensorial omnichannel customer experiences. These results not only contribute to the knowledge of omnichannel customer experiences, customer journeys, and value co-creation behavior, but also offer useful advice for omnichannel marketers.

Providing high-quality services and delivering a positive customer experience has become critical to the success of any restaurant. The purpose of the paper to analyse the customer journey during fast food service delivery, establish a correlation between sensory marketing and the customer journey, and improve the interaction with touchpoints by comprehending the sensory influences that can be used to enhance the customer experience throughout the journey. The theoretical basis of the study is comprised of classical marketing theory and the customer-centric approach. Structural equation modelling, descriptive statistics, regression and correlation analyses were used as research methods. The empirical framework includes the results of an online survey with 303 respondents, who are regular customers of four most popular fast food restaurants in Baghdad (Iraq). SPSS V.26 software was used to analyse and process the data. The study found that there is a significant relationship between sensory marketing and the customer journey. The fast-food restaurants use sensory marketing techniques (visual, auditory, olfactory, and gustative) to enhance the customer experience and better manage the customer's journey during food ordering. In the fast food industry, gustative and olfactory marketing techniques have the most significant impact on the customer journey. It was also revealed that the interaction with touchpoints is influenced by the sensory response of the customer.

Offline retail stores face increasing challenges in integrating technology to enhance the customer journey and overall customer experience. This study employed a descriptive qualitative method with a phenomenological approach to examine touchpoints in the customer journey at offline stores, focusing on the use of technology as a development strategy. Data were collected through interviews with 12 informants who had experience shopping in both offline and online stores, and through questionnaires distributed to 137 respondents to assess consumer demand for technology in offline retail environments. The findings revealed that all respondents experienced five key stages in the customer journey at offline stores—awareness, consideration, search, purchase, and loyalty—which were categorized into three service phases: pre-service, service, and post-service. At the awareness stage, store display touchpoints emphasized both atmospheric and technological elements, such as LED screens and digital catalog tablets. During the consideration stage, displays focused on atmospheric, communicative, technological, and interactional elements, supported by a comfortable store layout and tablets. At the search stage, the fitting room area highlighted product interaction, process, and communication, incorporating Augmented Reality or interactive services. At the purchase stage, cashier touchpoints prioritized process and technology through self-checkout systems and multiple digital payment options. In the loyalty stage, membership touchpoints focused on communicative and process elements. Overall, the results indicated that strategically incorporating technology at each stage of the offline customer journey can enhance customer experience and foster long-term loyalty.

The present research presented a novel model for incorporating service design to create guest experiential value. Taking a star hotel in Taiwan as an example, this study used the KJ method to classify online reviews about hotel services and then created a customer journey map (CJM) through participant observation of the entire service process. By deconstructing the service process and identifying key service touchpoints, service design ideas were incorporated into the CJM. A Kano questionnaire was then adopted to accommodate 38 service scape attributes in 4 segments: 1 attribute in the maintenance area, 10 of the high-priority area, 11 of the low-priority area, and 16 of differentiation. The overall research results propose experience design strategies for the hotel industry in terms of the service content and operation processes of star-rated hotels, which can then be adjusted according to their operating conditions to construct their unique service experience content. This is expected to be the basis for subsequent research and serve as a basis and reference for improving hotel service design strategies and competitiveness in the future.

This research aims to develop a new conceptual framework that investigates the effect of buy-online-pickup-in-store (BOPS) shopping on customer engagement and related outcomes from the touchpoint perspective. Based on the customer engagement theory and touchpoint literature, we define the concept of contact interactivity to explore the multiple touchpoints in the BOPS shopping experience and develop a conceptual framework and an associated set of propositions related to contact interactivity. To better understand contact interactivity, we propose the three dimensions of the customer–product interaction, customer–employee interaction, and customer–customer interaction, and further investigate the advantages of BOPS by comparing it with online shopping. This study has research implications for the BOPS literature by identifying specific touchpoints in multiple phases of the BOPS shopping journey and explaining the effect of BOPS shopping on customer engagement. We conclude by discussing important theoretical and practical implications that arises from our analyses.

Despite extensive literature reviews examining customer experience (CX) and the customer journey (CJ) separately, a comprehensive historical analysis that systematically explores their connection and co-evolution is lacking. Addressing this gap, the present study aims to systematically examine the emergence and co-evolution of CX and CJ research. A bibliometric-based review analyzed metadata from 1,634 scholarly articles (1,328 on CX and 306 on CJ), which were systematically retrieved from the Web of Science database using rigorous selection criteria. This article employs science mapping (i.e. thematic evolution and map) and automated content analysis (i.e. concept map) by using Bibliometrix and LexiPortal. This article maps the intellectual evolution of CX and CJ research over four decades, revealing five distinct periods characterized by shifts in focus, from early work on satisfaction and service quality to increasingly complex and technology-enhanced experiences. The analysis uncovers how CX and CJ have developed in parallel and often interwoven ways. Synthesizing these insights, the study introduces a future research agenda structured around three core building blocks of CX/CJ: Touchpoints, Contexts and Qualities. This study advances the service literature by offering a longitudinal, evidence-based view of how CX and CJ research have evolved, highlighting their growing integration and conceptual refinement. It helps clarify the intellectual roots and key developments in both fields, guiding future scholarship. For practitioners, the findings offer a clearer foundation to navigate the complexity of customer interactions and design more coherent, inclusive and transformative experiences.

Purpose: Customer journeys in today’s markets are “multitouch” and multichannel. Thus, the significance of studying customer journeys reflects the need to understand how the customer goes in an ongoing cycle of experience through dealing with the different touchpoints. The paper aims to understand the connectivity between how the touchpoints shape the customer experience and how it evolves throughout the customer journey from pre-purchase to purchase to post-purchase. The objective of the paper is understanding how the customer experience is shaped in multiple touchpoints, online and offline; in other words, brand-owned and social/external touchpoints. Design/Methodology/Approach: The study is generated using qualitative approach using interviews to investigate customers who purchase from high-street fashion stores in Egypt; the study focused on five stores which are: Zara, Mango, Pull and Bear, Bershka and Stradivarius. The data were collected from conducting twenty-five interviewees. The twenty-five interviews were digitally recorded and then fully transcribed. All the interviewees were informed about the confidentiality, anonymity of their identity. After a certain point, interviews reached semantic saturation in the data collection process where no or little new information was added (Gummesson, 2005). The interviewees were delivering no new themes regarding the study, and that emerged between the twenty and twenty-two interviews, in a total of twenty-five interviews. Findings: The finding reveals that there is empirical evidence to support the idea that touchpoints shape the whole customer experience in the pre-purchase, purchase and post-purchase stage.

In modern marketing, researchers are focused on the omnichannel approach due to the growing number of communication channels and sources of consumer information about brands. This paper examines the complexity and multifactorial nature of the omnichannel approach in the formation of customer experience and marketing communications in the digital environment. The article discusses the concept of a “Consumer Journey Map”, which reflects the stages of making a purchase decision, after-sales interaction and the customer experience formed within this path. This approach allows you to define and analyze the touchpoints with the consumer and information messages at each stage of the consumer journey in order to create a positive brand image. The consumer’s journey is formed by the sequential passage of a number of points of contact, which may belong to the brand, its partners or be independent. This affects the degree of brand control over the information at each of these points. Particular attention is paid to the complexity of tracking the entire variety of contact points through which the customer passes on the way to making a purchase. The management of this variety of points from the standpoint of a single communication environment of brand and consumer interaction is the subject of omnichannel marketing research. Within the framework of this study, the author considers the evaluation of the effectiveness of marketing channels at the stage of preparation for purchase. These channels may be underestimated, since in terms of direct return on marketing investments, they lose to the final pre-purchase channels, but they play a key role in shaping the customer experience leading to subsequent purchases. The article presents the results of a study of online communication based on a company providing educational services. This study demonstrates the relationship between the volume of investments in paid promotion channels and the total revenue from online channels. The results of the study emphasize the importance of the omnichannel approach in modern communication, where the buyer interacts with the brand in various channels and perceives communication as a single continuous process, even when switching from one channel to another.

Abstract There is little research that has examined how and why visitors engage in park safety information prior to, during, and after their visits. The current research presents a case study that uses semi-structured interviews to map out the visitor journey of 23 park visitors in Western Australia (11 frequent and 12 infrequent visitors). The results show that both frequent and infrequent park visitors engaged in varying degrees of research toward safety information. Beyond conventional sources of park and park safety information such as (1) traditional printed media including brochures and magazines and (2) official government and destination websites, the visitor journey mapping approach identified a number of other touchpoints including (3) local residents; (4) other travelers; (5) on-site staff and operators; (6) mobile phone applications; and (7) social media community. The findings provide significant insights into the management of park safety communication.

Customer experience research predominantly anchors the customer journey on a specific offering, implying an inherently customer-centric perspective. To address calls for a more goal-oriented approach, this study aims to develop an educational institutional view of customer journeys from the perspective of doctoral students. In a qualitative study, nineteen doctoral students were interviewed. Two independent researchers used triple coding and thematic analysis to unpack the experiences grounded by the perspective of the self-regulation model of a behaviour feedback loop. The findings suggest two pre-journey themes: supervisor selection and personal concerns, and three during-journey themes, namely, research complexity, administrative hurdles, and personal and social support struggles. The informants had pleasant experiences during the phase of the customer journey, expressing a favourable inclination towards trust and value. Nevertheless, they had difficulties in locating appropriate supervisors as a result of insufficient organised information. Several informants have reported suffering signs of depression, which can potentially result in serious consequences, specifically self-inflicted damage. Although the present study is not statistically generalizable to a broader population, the results are suitable and relevant for educational institutions that prepare doctoral students for rich and meaningful experiences in their doctoral journey. To the best of the authors’ knowledge, this study is among the very few studies that unfold the experiences among doctoral students in higher institutions using a customer journey map while building upon a self-regulation model of a behaviour feedback loop. It shows how higher education institutions should ensure what is offered meets the demands and preferences of students while considering their contemporary needs and wants. These institutions should extend their view beyond the immediate goals of their students to identify relevant touchpoints and other customer journeys that affect the students’ experience.

This study examines the influence of artificial intelligence (AI) and digital transformation on customer experience (CX) within Indonesia’s retail sector, focusing on physical, online, and hybrid shopping environments. Employing a qualitative exploratory design and semi-structured interviews, the research uncovers four central themes: AI-driven personalization, the role of omnichannel integration, organizational technological readiness, and differentiation of experiences across retail channels. The findings highlight that AI facilitates superior CX primarily through real-time personalization, enabling tailored interactions that respond dynamically to customer needs. Moreover, omnichannel integration emerges as a critical mechanism that ensures a seamless and consistent customer journey across various touchpoints. The study further reveals that customer perceptions of AI-enabled services vary depending on the retail channel. Physical stores emphasize tangible interactions and human engagement, online platforms highlight efficiency and convenience, while hybrid models deliver a blend of personalized digital features and physical experience. These differences demonstrate the moderating role of channel type in shaping how customers interpret the value of AI-driven services. From a theoretical standpoint, this research extends the literature by synthesizing Service-Dominant Logic (SDL), the Technology Acceptance Model (TAM), and Omnichannel Service Integration Theory into a coherent framework for analyzing CX in digitally transformed retail environments. Practically, it provides actionable insights for retailers on designing service strategies that are transparent, customer-centric, and context-sensitive. By doing so, businesses can align emerging technologies with ethical considerations while maintaining consumer trust. Ultimately, this study underscores the importance of adaptive innovation and responsible use of AI in achieving superior, consistent, and sustainable customer experiences. In rapidly evolving retail ecosystems, balancing technological capabilities with human values is essential for delivering meaningful and competitive service encounters.

No abstract available

. Today’s brick-and-mortar retail is struggling to stay competitive when compared to e-commerce. However, with a new form of retail emerging, which makes use of modern day technology to drive sales and offers unique customer experiences, the playing field seems to level out. Nevertheless, in this so-called “digital retail”, the number of touchpoints customers can encounter is constantly increasing due to the connection of online and offline customer journeys. To make use of sales-enhancing touchpoints, retailers require a comprehensive overview of brand-owned touch-points along the digital retail customer journey, as these are the touchpoints retailers are able to influence. The authors propose an approach that uses focus groups in combination with the creative techniques World Café, Channel CARDS, instant polls, and instant word clouds to gain a comprehensive overview of brand-owned touchpoints along the digital retail customer journey.

Nowadays, customer behavior has become highly complex. A stronger understanding of customer experience requires the explanation and analysis of the dimensions, components, and indicators of the customer journey model based on touchpoints. With this perspective, the overall aim of this study is to present customer experience-based touchpoints in the packaged food industry using the meta-synthesis method. The scientific research articles reviewed were published over a ten-year period from 2013 to 2023 in reputable academic databases such as Google Scholar, Elsevier, Emerald, Sage Journals, Taylor & Francis, and Springer, as well as local databases such as the Comprehensive Portal of Humanities, Scientific Information Database of Jahad-e-Daneshgahi, Ganj, and Iran's Scientific Information Database. After reviewing various articles, 15 relevant studies were selected and analyzed using the meta-synthesis method. The results indicate that the most significant touchpoints on the customer journey map in the food industry are virtual networks and the internet. These are followed by advertising, stores, products, promotion programs, and customers. In the virtual networks category, the most crucial touchpoint is social media; in advertising, it is word-of-mouth marketing; in stores, it is the physical environment; in products, it is packaging; in promotional programs, it is customer loyalty cards; and in the customer segment, it is other customers’ views/satisfaction that are recognized as the most important touchpoints.

Customer Experience Management (CXM) has been radically reshaped by the pervasive influence of Digital Transformation (DX), moving from a reactive support function to a proactive, data-driven strategic imperative. This paper asserts that successful CXM in the modern era requires seamless, personalized, and omni-channel interactions, underpinned by advanced technologies such as Artificial Intelligence (AI) and Machine Learning (ML). While DX offers unprecedented opportunities to map the entire customer journey and enhance service delivery, it also introduces challenges related to data privacy, personalization at scale, and maintaining the human touch. Organizations must strategically integrate technology, data analytics, and customercentric culture to deliver consistent, high-value experiences across all digital and physical touchpoints.

Purpose ­ One of the business sectors that has a quite important role for the national economy and has contributed to the absorption of labor and the distribution of development results is Micro, Small and Medium Enterprises (MSMEs). In the new normal era (Adaptation of New Habits) increasing the ability to use digital marketing will be able to help businesses deal with economic pressures, due to the Covid 19 pandemic which has caused a decrease in people's purchasing power where many people have shifted to buying online. In addition, in running a business, it is necessary to have complete documents or business legality. Likewise, De Thela's MSMEs based on observations have problems in terms of their limited ability to use digital marketing and do not yet have business legality.  Therefore, assistance is needed to overcome these MSME problems through digital marketing assistance through social media and the importance of having legality in developing a business. Methods – The methods used in the implementation of community service include problem identification, preparation, assistance, monitoring and evaluation of assistance. Result and discussions –  This community service activity has yielded results for De Thela's MSMEs including (1) De Thela's MSMEs have created social media content and joined the Shopee Food and Tukoni marketplaces so they can expand product marketing; and (2) UMKM De Thela has business legality by obtaining a Business Identification Number (NIB). Conclusion –  The results of this community service activity have implications where it is hoped that digital marketing assistance and business legality will make it easier for De Thela's MSMEs to develop businesses and increase sales and business sustainability, especially in the new normal era.    

This study examines the role of integrated digital marketing strategies, including personalized content, Customer Relationship Management (CRM) systems, and social media marketing, in building customer loyalty and driving long-term financial benefits. The research design uses a systematic literature review to examine how these digital tools work together to improve things. This is based on theories like relationship marketing and the resource-based view (RBV). The findings demonstrate that integrating these strategies leads to more muscular customer retention, reduced customer acquisition costs, and enhanced return on investment (ROI). Additionally, it confirms that a multi-channel approach, which aligns CRM data with personalized content and social media, provides a more cohesive customer experience, leading to increased customer lifetime value (LTV). The study highlights practical implications for businesses, emphasizing the need for integrated digital strategies to enhance customer engagement and financial sustainability. However, the study's limitations include its reliance on secondary data and the exclusion of emerging technologies like artificial intelligence. Future research should focus on longitudinal studies and explore industry-specific case studies to provide more tailored insights into the evolving landscape of digital marketing.

This study proposes the Tourism Adaptable Digital Marketing Framework (TADMF), a flexible, cyclical model tailored to optimize digital marketing strategies for hotels and destinations. By leveraging data-driven insights and neuromarketing principles, the framework addresses critical gaps in traditional linear models to maximize bookings for hotels and enhance awareness of destinations. The three-stage cyclical process, attraction, engagement, and conversion, ensures continuous feedback and refinement across the customer journey. Hotels benefit from tailored techniques, such as dynamic pricing and personalized recommendations, while destinations focus on storytelling and user-generated content to forge emotional connections. Compared to traditional marketing models, this framework uniquely integrates online and offline interactions to create cohesive customer experiences. Key findings reveal that the TADMF fosters a dynamic interplay between theoretical innovation and practical applicability, demonstrating scalability and adaptability to diverse tourism contexts. The study concludes that the TADMF offers a robust foundation for addressing the evolving challenges of digital marketing in tourism, paving the way for future research into advanced technologies such as AR, VR, and AI.

In the rapidly evolving digital landscape, small and medium-sized enterprises (SMEs) must adopt innovative digital marketing strategies to drive competitive advantage and sustainable growth. This review explores the critical components and benefits of leveraging digital marketing for SMEs, emphasizing how tailored strategies can enhance market presence, customer engagement, and business performance. SMEs face unique challenges in resource allocation and market competition, necessitating cost-effective and impactful marketing approaches. Innovative digital marketing strategies, including search engine optimization (SEO), social media marketing, content marketing, email campaigns, and data-driven analytics, provide SMEs with the tools to compete effectively against larger enterprises. By utilizing these strategies, SMEs can achieve greater visibility, attract a broader audience, and convert prospects into loyal customers. SEO and content marketing play a pivotal role in enhancing online visibility and organic traffic. By producing high-quality, relevant content and optimizing it for search engines, SMEs can improve their search rankings and attract targeted audiences. Social media platforms offer powerful channels for engaging with customers, building brand awareness, and fostering community. Through targeted advertisements and influencer partnerships, SMEs can reach specific demographics and drive engagement. Email marketing remains a cost-efficient strategy for maintaining customer relationships and promoting products or services. Personalized email campaigns can nurture leads, encourage repeat business, and build customer loyalty. Additionally, data-driven analytics enable SMEs to measure campaign performance, understand customer behavior, and make informed decisions to refine marketing efforts. The integration of innovative technologies such as artificial intelligence (AI) and machine learning further enhances digital marketing capabilities. AI-driven tools can automate tasks, provide insights into customer preferences, and optimize marketing strategies in real-time. For instance, chatbots can improve customer service, while predictive analytics can forecast trends and personalize marketing messages. In conclusion, innovative digital marketing strategies are essential for SMEs seeking to drive competitive advantage and sustainable growth. By embracing SEO, social media marketing, content marketing, email campaigns, and data-driven analytics, SMEs can maximize their marketing impact, enhance customer engagement, and achieve long-term business success. Leveraging these strategies allows SMEs to remain agile, responsive, and competitive in the dynamic digital marketplace. Keywords:  Innovative, Digital Marketing, SMEs, Sustainable Growth, Competitive Advantage.

Today’s business world is heading towards digital platforms aiming to reach more customers by performing sentiment analysis and recommending related products considering customers’ choice and preferences to enhance sales revenue and maximize profitability. Digital marketing plays a crucial role in this transformation by connecting digital stores with their target audiences through various online channels. This article explores how digital marketing affiliates digital stores in terms of sales enhancement, visibility, and customer engagement on platforms such as Shopify, Amazon, and Walmart. It also explores the challenges of affiliate fraud, SEO competition, and transparency issues in digital retail. Thematic analysis of the existing literature was performed with an emphasis on crucial themes of social media's role in affiliate marketing, search engine optimization for traffic generation, content marketing effectiveness, AI-embedded automation, and customer retention strategies. Only peer-reviewed studies and industry reports were considered. Digital marketing affiliates use influencer promotions, SEO optimization, and AI-driven automation to promote digital stores and increase conversions. Although its amplification of reach and engagement are significant benefits, the concerns of fraudulent actions, algorithmic bias and saturation within affiliate schemes pose questions about its effectiveness as a business practice. Leveraging AI-powered tracking tools, streamlining SEO strategies, and upholding ethical transparency in influencer partnerships position businesses to harness the full potential of affiliate marketing. Using blockchain for secure affiliate tracking can add to increasing credibility and trust. Future research should focus on long-term perspectives regarding the effects of AI in affiliate marketing, changing dynamics of influencer-led marketing strategies, and the effect of overall technological innovations on the effectiveness of affiliate programs.

The era of digital transformation has changed the paradigm of human resource management in the information technology industry, where organizations that focus on human capital development through strategic training programs show performance increases of up to 75% compared to organizations that do not make similar investments. The information technology industry faces a special challenge in maintaining the relevance of employee competencies to leading technological developments, so a comprehensive evaluation of the impact of digital marketing training programs using a measurable and objective quantitative approach is needed. The purpose of this study is to analyze and measure the effectiveness of digital marketing training programs on increasing employee work productivity in Metro Lampung through a pre-post implementation comparative study approach, identifying differences in productivity levels before and after implementation, calculating the magnitude of increase, and analyzing the most responsive productivity dimensions. The study used a quantitative approach with a quasi-experimental pre-post test design on 35 IT employee respondents selected using purposive sampling technique, with data collection using a structured questionnaire on a Likert scale of 1-5 and paired sample t-test analysis. The results showed a significant increase in work productivity (p < 0.001) by 20.2% with a confidence interval of 95% (18.7%-21.7%), where the Innovation Index achieved the highest responsiveness (23.0%, Cohen's d = 2.29), followed by Task Completion Rate (20.6%), Quality Performance (19.8%), and Collaboration Effectiveness (18.0%). Digital marketing training programs have proven to be effective in increasing work productivity with 97.1% of respondents experiencing progress in at least three of the four dimensions evaluated. Organizations need to optimize resource allocation on innovative technology training modules, integrate a holistic approach that leverages synergistic effects across productivity dimensions, and implement training personalization strategies to maximize outcomes for all participants.

This study investigates the role of digital marketing in expanding rural markets in Sub-Saharan Africa through a qualitative research approach. Focusing on three diverse countries—Kenya, Ghana, and Rwanda—the research involved in-depth interviews with rural entrepreneurs, digital marketing practitioners, NGO representatives, and rural consumers. The findings reveal that digital marketing significantly enhances market access, enabling rural businesses to overcome traditional geographic and infrastructural barriers. Trust-building emerged as a central factor for success, highlighting the necessity of leveraging local social networks and culturally resonant communication strategies. However, digital literacy gaps, infrastructural limitations, and socio-economic disparities pose persistent challenges to effective digital engagement. Participants demonstrated innovative adaptations to local contexts, such as the use of low-data applications and the blending of online and offline marketing efforts to maximize reach and credibility. The study contributes to the understanding of digital inclusion in emerging markets and emphasizes the need for localized, trust-centered marketing approaches. It also underlines the importance of investing in rural digital skills development and affordable connectivity to fully harness the potential of digital marketing in promoting inclusive economic growth. Despite its contributions, the study acknowledges limitations in terms of regional coverage, generalizability, and the cross-sectional nature of the research. Future studies are encouraged to adopt longitudinal and mixed-methods designs to capture the evolving dynamics of digital marketing adoption in rural Sub-Saharan Africa.

The development of digital technology encourages MSMEs to optimize social media as an effective and efficient marketing tool. This study aims to analyze the effectiveness of utilizing social media, especially Whatsapp Business , Instagram and TikTok, as digital marketing media for MSME Deandra Batik Lampung. The method used is qualitative with data collection techniques through interviews, observations, and documentation. The results of the study show that social media can significantly increase brand awareness , interaction with customers, and sales of batik products. However, obstacles such as lack of understanding of social media algorithms and limited technical skills are the main obstacles in optimizing digital marketing. Training efforts and utilization of social media analytics features help overcome these obstacles. Utilizing social media as a digital marketing medium is an effective way for MSME Deandra Batik Lampung to face market competition by maximizing market interaction and reach. This study provides important recommendations for increasing digital marketing capacity so that MSMEs can maximize the use of social media

This study aims to comprehensively analyze the influence of productivity, digital marketing, and operational costs on competitive advantage at Lilin Thrifting Store, a micro, small, and medium enterprise (MSME) located in Brebes Regency, Indonesia. In the current business environment characterized by intense competition and rapid technological development, MSMEs must adopt strategies that not only increase efficiency but also strengthen their competitive positioning. A quantitative research method was applied, employing a survey approach to obtain primary data from both customers and business managers. A total of 100 respondents participated in this study, selected through purposive sampling to ensure relevance to the research objectives. Data were collected via structured questionnaires and analyzed using multiple linear regression to determine the magnitude and direction of the relationships among the variables.The results reveal that productivity exerts a positive and significant effect on competitive advantage, indicating that improvements in work efficiency, service quality, and resource utilization directly enhance the store’s ability to compete in the market. Similarly, digital marketing demonstrates a positive and significant effect, highlighting the role of social media engagement, online advertising, and e-commerce platforms in expanding market reach and increasing brand visibility. Conversely, operational costs show a negative and significant effect on competitive advantage, suggesting that excessive or poorly managed expenditures can undermine profitability and weaken market standing. These findings underscore the importance for MSME actors, particularly in the retail and secondhand clothing sectors, to prioritize strategies that enhance productivity and maximize the potential of digital marketing while maintaining strict control over operational expenses. The practical implication is that sustainable competitive advantage can be achieved through a balanced approach that integrates internal efficiency, technological adaptation, and cost-effectiveness.

. Artificial intelligence is changing digital marketing today by making more individualized, effective, and efficient methods possible. Several studies led by experts have looked into the use of artificial intelligence for digital marketing. However, there is currently a lack of studies on Indonesia's use of artificial intelligence in digital marketing. This recent study focused on the use of artificial intelligence for digital marketing in Indonesia both during and after the Covid-19 epidemic (2019-2024). The study were investigated is based on Scopus databases. The remain number of paper based on the relevancies towards the topic is 12 articles. The in-depth analysis is conducted based on several categories, including the research urgencies, the type of artificial intelligence use for digital marketing, and the type of product or sector promote by artificial intelligent. The results revealed that artificial intelligence has been used in multiple earlier studies for digital marketing for a variety of reasons including improve marketing strategies, gathering information from consumers, revenue growth, and customer service enhancement. The study also revealed there were several variety of Artificial Intelligence used that combine with common technology, including AI algorithm, AI based voice assistant, SVM enhance machine learning, AI text analysis, AI powered geo-targeting, etc. Telecommunication companies, apparel retailers, food and beverage companies, and other e-commerce businesses are among the industries that have employed artificial intelligence for digital marketing. In summary, the application of artificial intelligence in digital marketing is commonly used to provide various kinds of marketing strategies, production efficiency, high-quality services, and profit maximization.

Blockchain technology is revolutionizing the world of e-commerce by providing innovative ways to improve digital marketing security, transparency, and trust. This analysis examines the use of blockchain technology in a variety of areas, highlighting how it can help solve issues such as data integrity, fraud prevention, and customer trust. Important developments include the use of smart contracts to improve business processes, blockchain-powered loyalty programs to increase customer retention, and hybrid models that combine blockchain, artificial intelligence, and the Internet of Things (IoT) to maximize operational efficiency and decision-making. Blockchain technology has the potential to improve the transparency of e-commerce transactions and encourage user engagement through secure solutions. Despite its many benefits, the adoption of blockchain in digital marketing presents several challenges, including data privacy concerns, interoperability issues, and the complexity of integrating blockchain-based solutions with existing marketing frameworks. Additionally, scalability limitations, high implementation costs, and regulatory uncertainties hinder widespread adoption. Addressing these challenges requires further research into developing scalable blockchain architectures, enhancing compatibility with traditional enterprise systems, and establishing regulatory guidelines tailored to digital marketing applications. Beyond its role in digital marketing, blockchain has broader implications for e-business by reshaping business models, improving operational security, and fostering trust in online transactions. This study provides a comprehensive examination of blockchain’s potential to revolutionize digital marketing and e-commerce systems by highlighting its strengths, weaknesses, and opportunities.

This study aims to identify internal and external factors of MSMEs related to digital marketing and formulate strategies and recommendations so that the use of digital marketing is optimal and has good competitiveness in local, national, and global markets. To achieve this goal, a quantitative method is used; the population of this study is MSME actors who are considered to understand external and internal factors and are involved in forming their business strategies. Samples were collected by purposive sampling, namely MSMEs who plan or are using digital marketing for their marketing activities; with the Slovin formula, 397 respondents were obtained, but only 62% could be used (250). Using the SWOT analysis tool, the results of the study were obtained: IFA scored 3.95, and EFA scored 3.89. Based on QSPM, 14 strategies were obtained according to their respective priority orders, and the top 3 strategies were: utilizing e-commerce platforms, increasing marketing activities, and maximizing personal content. Implementing these priority activities will allow MSMEs to adapt to the digital ecosystem quickly. The implication is that MSMEs need to be given technical training and assistance in using digital platforms, such as creating online stores, managing transactions, conducting promotions, or analyzing data available on social media. Theoretical implications support the theory that MSME growth in the digital landscape requires more effective offensive and proactive strategies. This provides an opportunity for further research to explore the use of digital marketing in MSMEs more deeply.

This study aims to analyze the application of digital marketing in micro, small, and medium enterprises (MSMEs) within the snack food sector, and its impact on business performance. Using a qualitative method with in-depth interviews, observations, and documentation study, this research explores the digital marketing strategies implemented by five MSME snack business owners, along with the challenges and outcomes they experienced. The results show that most MSME snack businesses have utilized digital platforms, particularly social media like Instagram and Facebook, as well as e-commerce platforms like Tokopedia and Shopee, to promote their products. Strategies include the use of engaging visual content, discounts, and partnerships with micro-influencers. Despite challenges such as limited knowledge, budget, and time, the impact of digital marketing has proven significant, especially in increasing product visibility, sales, and customer loyalty. Therefore, digital marketing offers great potential for MSMEs to expand their market reach and enhance business performance. The study also recommends improving digital literacy and leveraging advanced marketing features to maximize the potential of digital marketing for MSMEs.

This study examines the effects of digital marketing, word-of-mouth communication, and product quality on consumer purchasing decisions for Azarine products. Using a quantitative approach, the research analyzed both individual and combined impacts of these factors on consumer buying behavior. A purposive sampling method recruited 100 Azarine product users in Medan City. Primary data was collected through questionnaires, while secondary data came from literature review. Data analysis used SPSS including validity tests, reliability assessments, classical assumption tests, multiple linear regression, and coefficient of determination analysis. Results show digital marketing significantly influences purchase decisions (t = 11.499 > 1.985, p < 0.05) with a positive regression coefficient of 0.164. Word-of-mouth demonstrates significant positive impact (t = 7.958 > 1.985, p < 0.05) with regression coefficient of 0.155. Product quality positively affects purchase decisions (t = 2.079 > 1.985, p = 0.011 < 0.05) with regression coefficient of 0.044. The three variables collectively explain 66.9% of variance in purchase decisions (Adjusted R² = 0.669), indicating substantial explanatory power. The remaining 33.1% is attributed to external factors not included in this model. These findings suggest companies should emphasize digital marketing strategies, encourage positive word-of-mouth, and maintain high product quality to enhance consumer purchasing intentions. The study provides valuable insights for marketing professionals seeking to maximize consumer behavior influence through integrated promotional approaches.

Facebook is a valuable digital marketing tool as it enables companies and businesses to interact with customers, build brand awareness and access an extensive audience. This study aims to examine how effective Facebook is as a digital marketing tool for student online sellers. It investigates on the respondents’ thoughts on selling on Facebook, What Facebook have that others don't, the features of Facebook, the impact of Facebook on respondents’ businesses and their thoughts about Facebook's boost feature. The researcher employed a qualitative research methodology, focusing on Husserl's transcendental phenomenological research design. In addition, the proponents conducted semi-structured interview questions; the data were collected from 10 entrepreneurship students at the City College of El Salvador, Misamis Oriental, and Philippines. Furthermore, the responses were interpreted using thematic analysis. The results show that the use of Facebook as a digital marketing tool really helps student sellers as it yields financial opportunities, a broad reach and market potential, and accessibility and usability. In what Facebook has that others don’t, the result was categorized in terms of its user base and popularity, as well as community and engagement. Moreover, on the features of Facebook that the respondents know, aside from messenger, group pages, posting, and live was Marketplace and Selling Features, Visual Content Sharing, Limited to No Idea. In addition, on the impact on Facebook on the respondents’ businesses, the commonality was Positive Sales Impact, Increased Customer Engagement and Customer Feedback and Reviews. Furthermore, on the respondents’ thoughts about Facebook's boost feature, the commonality was Awareness and Familiarity, Lack of Awareness and Heard about it but Uncertain. The study concludes that Facebook significantly benefits student sellers by providing financial opportunities, broad market reach, and ease of use. Its unique strengths lie in its large user base and strong community engagement. Respondents identified key features like Messenger, group pages, Marketplace, and visual content sharing, though some had limited knowledge of advanced tools. Facebook positively impacted sales, customer engagement, and feedback. However, familiarity with the boost feature varied, highlighting the need for better awareness to maximize its marketing potential.

This study investigates the influence of laptop condition on pricing in the eBay marketplace, using statistical analysis to provide actionable insights for digital marketing strategies. The analysis is based on a dataset containing 2,952 laptop listings, categorized by condition into New, Open box, Excellent - Refurbished, Very Good - Refurbished, and Good - Refurbished. An ANOVA test revealed a significant difference in mean prices across these conditions (F-value = 76.69, p < 0.0001), indicating that condition is a critical factor in pricing. Post-hoc analysis using Tukey's HSD test further highlighted specific pairwise differences. For instance, the price difference between New and Good - Refurbished laptops was found to be approximately $192.66 (p < 0.0001), confirming that even minor wear significantly impacts consumer perception and pricing. Additionally, Excellent - Refurbished laptops were priced, on average, $62.79 higher than their New counterparts (p = 0.0008), suggesting a premium for well-maintained refurbished models. A multiple linear regression model was employed to quantify the impact of various factors on pricing, including condition, brand, RAM, and processor type. The model, with an R-squared value of 0.429, indicated that these variables collectively explain 42.9% of the variation in laptop prices. Despite the model's moderate fit, the coefficients provided insights into the relative importance of each factor, with condition emerging as the most influential determinant. The findings suggest that eBay sellers should prioritize accurate and detailed descriptions of product condition to optimize pricing strategies. These results underscore the importance of condition-based pricing in digital marketing, offering a data-driven approach to maximizing profitability in online marketplaces.

Background: Digital marketing has become a cornerstone of modern business strategies, particularly in rapidly digitizing regions like Kathmandu Valley, Nepal. With increasing internet penetration and smartphone usage, businesses leverage digital platforms for advertising, customer engagement, and sales. However, consumer awareness, perceptions, and the societal impact of digital marketing remain understudied in Nepal’s context. This research examines how digital marketing awareness influences individuals’ perceptions, focusing on its positive and negative effects, gender-based differences, and general opinions. Objective: The study aims to (i) Assess the level of digital marketing awareness among Kathmandu Valley residents. (ii) Examine the relationship between awareness and perceived positive/negative impacts. (iii) Evaluate general consumer opinions toward digital marketing. Methods: A quantitative research design was employed, using a structured questionnaire distributed to 200 respondents across various colleges and residential areas in Kathmandu Valley. Data was analyzed using SPSS, incorporating descriptive statistics, Pearson’s correlation, and hypothesis testing. Demographic variables (age, gender, education, internet usage) were examined, and relationships between awareness, perceived impacts, and general opinions were assessed. Findings: (i) Awareness and Positive Impact: A moderate positive correlation (r = 0.345, p < 0.01) was found, indicating that higher awareness leads to more favorable perceptions. (ii) Gender Differences: No significant correlation was observed between gender and awareness, positive/negative impacts, or general opinions (p > 0.05). (iii) Negative Impact: Awareness showed no significant link (p = 0.773) to negative perceptions, suggesting that informed consumers do not necessarily associate digital marketing with harm. (iv) General Opinion: Awareness had no meaningful influence (p = 0.887), implying that other factors shape overall attitudes. Conclusion: The study reveals that while digital marketing awareness enhances positive perceptions, it does not significantly affect negative views or general opinions. Gender plays a negligible role in shaping these perceptions. Businesses should focus on transparency, consumer education, and ethical practices to maximize trust and engagement. Policymakers may consider regulations to address privacy concerns without stifling digital growth. Novelty: This research provides first-hand empirical insights into digital marketing awareness and its societal impact in Nepal, a region underrepresented in global digital marketing literature. Unlike prior studies focused on Western markets, this work highlights localized consumer behavior, offering actionable strategies for Nepalese businesses and regulators.

This study examines the role of integrating Islamic values and digital marketing strategies in enhancing Muslim consumers' purchase intention for halal-certified MSME products in Aceh and its impact on preserving local wisdom. Using a quantitative approach, the research employs an explanatory design, collecting data from 215 respondents through purposive sampling. Primary data is obtained through questionnaires, supported by secondary data for contextual analysis. The findings reveal that the application of Islamic values plays a fundamental role in shaping consumer purchase intentions, emphasizing the importance of ethical principles in influencing purchasing behavior. Digital marketing strategies also positively contribute to consumer interest, though their influence is smaller compared to Islamic values. Additionally, the study highlights a strong relationship between consumer purchase intentions and the preservation of local wisdom in Aceh. It underscores the importance of a balanced approach that integrates value-based strategies with digital promotion to maximize consumer interest while preserving local traditions. The research advocates for holistic marketing strategies that align with Islamic principles and cultural preservation efforts, enabling MSMEs to thrive and sustain Aceh’s heritage in the era of globalization.

Objective: This study aims to analyze the implementation of digital marketing in MSMEs in Gedangan District by adopting the policy implementation theory model from George C. Edward III. Method: The approach used is qualitative descriptive, involving in-depth interviews, direct observation in the field, and document data collection. Results: The results of the study show that the use of digital marketing has resulted in an increase in revenue and the expansion of the small and medium enterprises (MSMEs) market. However, implementation still faces many challenges. This includes elderly business actors who do not have digital literacy, lack of technological infrastructure, and lack of post-training mentoring. Although policy communication has been carried out through socialization and training, it has not been consistent and equitable. While most senior business actors stick to conventional approaches, young human resources tend to be more flexible in social media management. Novelty: For continuous improvement, consistent implementation of digital marketing, more practical routine training and assistance are needed. In addition, it is necessary to increase access to financing and improve technological infrastructure so that MSME actors can maximize promotion and market expansion in a sustainable manner.

Artificial Intelligence (AI) is revolutionizing digital marketing automation by enhancing efficiency, personalization, and predictive capabilities. This study examines the role of AI in transforming marketing practices, focusing on its applications, benefits, ethical considerations, and future directions. By leveraging AI tools such as predictive analytics, NLP, and chatbots, businesses can achieve improved customer segmentation, content personalization, and campaign optimization in marketing strategies. Secondary data from journals, articles, and conference papers were synthesized to provide insights into AI's impact on digital marketing automation. A systematic literature review utilizing the PRISMA methodology initially identified 2,850 records from database searches. Following the removal of duplicates and non-relevant studies, 1,035 records were screened for eligibility based on defined criteria, resulting in the inclusion of 150 relevant studies and 25 high-quality reports for detailed analysis. This robust approach ensured the inclusion of high-quality research, minimizing biases. The findings reveal that AI enhances digital marketing by streamlining processes, automating repetitive tasks, and delivering hyper-personalized customer experiences. Predictive analytics helps anticipate consumer behavior, while chatbots improve real-time customer engagement. However, challenges such as data privacy, algorithmic bias, and the high costs of AI adoption persist. AI adoption allows businesses to make data-driven decisions, improve customer retention, and maximize return on investment. Ethical AI practices, such as transparency and algorithm fairness, are essential for maintaining consumer trust. The study primarily focuses on existing literature, with limited empirical validation. Future research should explore long-term effects of AI-driven marketing on consumer behavior and investigate its integration with emerging technologies like the Internet of Things (IoT) and blockchain. Additionally, tailored AI solutions for SMEs and under-researched areas, such as B2B marketing, are critical for inclusive growth.

Purpose The development of increasingly modern times makes all business activities use digital marketing to increase brand awareness of a business. PT Lifa Plasmet Indonesia is a company in the field of manufacturing plastic ID accessories and product customization decided to do digital marketing with sites, Facebook and Instagram social media, create Mailchimp, and create a trade account on the Tokopedia marketplace site. Methodology The research method used is descriptive qualitative with a data triangulation approach through interviews, observation and documentation. Findings The results in this study show an impressive positive impact in gaining public awareness about PT Lifa Plasmet Indonesia through websites or sites and social media. These results can be seen from the number of website visits, insights from Facebook and Instagram social media, as well as increased customer reviews and interactions on Google My Business. Suggestion It is hoped that the company will remain consistent in maintaining the content uploaded on social media and maximizing the increased exposure of PT Lifa Plasmet Indonesia

The purpose of this study is to identify best practices for digital marketing of food products of micro, small, and medium enterprises (MSMEs) in Tanggulangin District, Sidoarjo Regency. The methodology used in this research is qualitative. In this study, five MSMEs in the culinary sector of Tanggulangin sub-district were surveyed-the owners of Warung Pring Bali and Warung Candi Ubud as well as Omah Kidul culinary, lesehan sawah in Kedungbanteng (LTS), and rujak cingur Tanggulangin. The research took place in these sectors. Results from interviews and focus groups were triangulated in the data analysis. Based on the findings, MSME owners in the food industry really need to master digital marketing if they want to maximize or improve their competitiveness while facing business problems. A number of micro, small and medium enterprises (MSMEs) have improved their digital marketing strategies by making good use of social media, while others still have not done so. In order for micro, small and medium enterprises (MSMEs), especially those engaged in catering services, to grow rapidly, cooperation and coordination between various parties are needed. In addition, MSME activists in Tanggulangin Subdistrict have their own obstacles due to the fierce competition in the food service sector

The purpose of this research is to study how the use of online promotion strategies through Instagram impacts customer interest in the Janji Jiwa Arif Rahman Cianjur outlet. This research was conducted through a quantitative approach, and data was collected through questionnaires that can be accessed online. The number of respondents in this study were forty people who had purchased the coffee shop's products. The data obtained was then analyzed through multiple linear regression analysis and hypothesis testing using the F test and t test. The results showed that the Digital Marketing variable had the greatest influence on customer interest in the outlet. These variables affect customer interest both overall and partially. Therefore, companies need to maximize the use of Digital Marketing by providing details about promos, discounts and other innovations by following trends, working with influencers or endorsements, and consistently creating creative content to reach a larger audience.

Small and medium enterprises (SMEs) UD Meubel Maju Barokah is a small and medium enterprise engaged in the production of wooden furniture, such as doors, cabinets, frames, and other household furniture. This business has good product quality but has not been able to maximize digital marketing strategies in expanding market reach and increasing competitiveness. This community service activity aims to assist SMEs in implementing digital-based marketing strategies to increase product visibility and attract wider consumer interest. The method of implementing the activity is carried out through a participatory approach, starting from field observation and direct interviews with business actors to solution design and training and implementation assistance. The focus of the activity is directed at five main aspects, namely the use of social media (Instagram, Facebook, TikTok), periodic content creation, marketing through e-commerce (Tokopedia, Shopee), product catalog website development, and optimization of customer testimonials. The results of the community service activity are expected to enable SMEs to actively utilize digital media to promote products, communicate with consumers, and build a professional image. This strategy can increase customer interaction and expand market reach. Thus, this community service provides a real contribution in supporting the digitalization of local SME marketing so that they can survive and develop in the era of digital competition.

This study examines the role of digital advertising and price in the sales volume of Ultra Glue products in Java, Indonesia. A quantitative approach was applied and data were collected from 50 respondents through a survey. This study evaluates the impact of promotion, price, and sales using multiple regression analysis. The results show that promotion, especially through digital marketing, has a significant impact on sales, which is in line with the literature that recognizes promotional activities as vital in stimulating consumer demand and purchase intention. On the other hand, the impact of price on sales, although positive, is more complex because it is influenced by product quality, overall strategy, and other marketing elements. This study emphasizes the importance of integrated marketing, in which digital promotions are effective, prices are competitive, and products are of good quality to maximize sales. This study also highlights external variables, such as brand loyalty and market competition, to understand consumer behavior in greater depth. We recommend using a blended approach to enrich our understanding of the consumer decision-making process.

Objective: This study explores an optimization model for digital marketing strategies based on the 4P theory, addressing the limitations of traditional marketing in digital environments, enhancing corporate profitability, user conversion rates, and customer satisfaction, and verifying the effectiveness of the optimized strategies. Methods: Based on the 4P theory, combined with dynamic pricing models and omnichannel layouts, we constructed an optimization model aimed at maximizing profits. Through simulation experiments, we compared experimental and control groups of electronic products, clothing, and daily necessities on an e-commerce platform. The evaluation indicators included profit growth rate, user conversion rate, and customer satisfaction index. Results: The optimized strategies significantly improved marketing performance: the experimental group's profit growth rate increased by 25%-33.3% compared to the control group, user conversion rates improved by 50%-66.7%, and the average customer satisfaction index increased by 6-8 points. Conclusion: The optimization strategies based on the 4P theory have significant value in digital environments, providing support for enhancing enterprise competitiveness and resource allocation efficiency. Future work can expand multi-scenario validations and integrate artificial intelligence to achieve real-time strategy optimization.

The aim of this paper is to provide an overview of literature on digital strategy, brand image, and customer loyalty, contributing a strengthened perspective to this discourse. This paper employs a qualitative methodology, utilizing a literature review model based on findings from papers related to the variables within this study over the past eight years. The outcomes of this paper aim not only to reinforce existing implementation findings but also to contribute to and enrich the research field. The Digital Strategy Model has proven to be a valuable asset for Umrah and Hajj travel agencies in shaping brand image and maintaining customer loyalty. As the digital landscape evolves, a commitment to innovation, personalization, and customer trust will be crucial for sustained success in this competitive industry. Implementing these recommendations, Umrah and Hajj travel agencies can optimize their digital strategies, ensuring a holistic and customer-centric approach that fosters brand loyalty and satisfaction in the digital era.

Digital transformation (DT) fundamentally disrupts enterprise operations presenting both unprecedented opportunities and complex challenges for organisational leadership. Drawing upon dynamic capability theory, we develop a model exploring the dynamics of digital transformational leadership (DTL) and its effects on DT within small- and medium-sized enterprises (SMEs). Specifically, we investigate the mediating roles of digital capabilities and digital strategies. Data from 256 SMEs in Ghana were analysed using structural equation modelling techniques to test hypotheses. The findings reveal a positive relationship between DTL and DT, demonstrating that the former positively influences digital IT capabilities (ITDC), employee digital capabilities, and digital strategies. ITDC and employee digital capabilities partially mediate the relationship between leadership and DT, while digital strategy shows a weaker mediating effect. The findings enhance understanding of how transformational leadership influences DT in SMEs, emphasising the role of digital capabilities and the nuanced impact of digital strategies.

PurposeThis research aims to elucidate the interplay between implementing digital strategies, adopting big data analytics–artificial intelligence (BDAAI), and business process innovation, with a particular emphasis on assessing the moderating impact of digital culture. This article explores how big data analytics can provide organizations with the tools and resources to utilize their data assets effectively, fostering novel and innovative processes.Design/methodology/approachThe research employed a questionnaire-based approach to collect data from managers in Pakistan’s telecom sector. Data analysis was conducted using SPSS and AMOS software. The measurement model’s suitability was assessed via confirmatory factor analysis (CFA) using AMOS.FindingsPreliminary results indicate a correlation between these critical factors: digital strategy prioritization, big data analytics incorporation and digital culture cultivation. The study results confirm the effect of digital strategy on business process innovation and support the positive mediating role of the adoption of BDAAI and the moderating role of digital culture.Research limitations/implicationsThe research offers insights but is limited to Pakistan’s telecom industry. Digital strategy is crucial for innovation amid digital transformation, with BDAAI enhancing process innovation. The digital culture in telecom will drive industry digitalization through BDAAI in business innovation.Originality/valueLeveraging artificial intelligence within a digital culture context could be a productive tool for improving business processes. This research represents a novel exploration of the intersection between digital strategy, BDAAI and digital culture within the context of the telecommunications industry.

This study empirically tests whether and through which mechanisms digital strategy (DS) influences digital organisational culture (DOC) in small and medium enterprises (SMEs). While prior research often treats DOC as a precondition for digital transformation, our study reverses this direction by conceptualising DS as a driver of cultural change. Grounded in contingency and strategic choice theories, the study develops and tests a parallel mediation model linking DS to DOC through two mediators: digital transformational leadership (DTL) and digital capabilities (DCs). The model is evaluated using cross-sectional survey data collected from 160 SMEs operating in Poland's energy sector – a highly regulated and technologically evolving environment. The results confirm that DS significantly shapes DOC, both directly and indirectly. DCs and DTL act as parallel mediators, with DCs emerging as the stronger pathway. DS remains the most influential predictor, underscoring its strategic role in driving cultural alignment. This study employs a cross-sectional, single-respondent design and focuses on SMEs in one highly regulated national sector, which may constrain causal inference and generalisability. Future studies should adopt longitudinal or multi-level approaches and extend inquiry to larger firms or alternative institutional environments. Although DCs and DTL are key mediators, variables such as agility, collaboration or innovation climate may further influence DOC. These findings provide a theoretical basis for investigating how strategy-driven change unfolds in constrained contexts and highlight avenues for refining strategic-cultural alignment models. To foster digital organisational culture and accelerate transformation, SME leaders should prioritise strategic digital alignment and invest in leadership development and capability-building. The inherent agility and flat hierarchies of SMEs enhance their responsiveness to cultural change when strategically guided. Policymakers can amplify this potential by offering targeted, sector-specific incentives, particularly in regulated industries – to lower adoption barriers, reduce compliance burdens and catalyse sustained digital-cultural convergence. This paper contributes to digital transformation literature by reframing the DS–DOC relationship through a contingency-theoretic lens. It clarifies the mediating roles of capabilities and leadership in shaping DOC and empirically tests this model in an under-digitised and heavily regulated sector. By focusing on Polish energy SMEs, the study addresses a significant contextual gap in the literature.

ABSTRACT Manufacturing businesses worldwide increasingly strive to devise and implement strategies to succeed in digital transformation and improve their performance by developing digital capabilities and competencies. We argue that this process should incorporate a culture and dynamic capabilities that support this transformation. In this vein, we propose and test a model explaining the impact of digital strategy on firm performance and the mediation mechanisms of digital platform capabilities and digital culture in this relationship. Our analysis of time-lagged data, gathered from middle and top managers of small and medium-sized manufacturing enterprises (SMEs), affirms our initial hypotheses: digital strategy positively influences firm performance, and digital platform capabilities and organisational culture mediate this relationship. Our study carries significant implications for manufacturing SMEs, particularly those in developing countries, as it underscores the pivotal role of digital platform capabilities and cultural factors in leveraging digital strategies for competitive advantage.

Digital transformation (DT), digital strategy and digital leadership, digital agility seem to be concomitant phenomena in recent years, drawing a NIT theory, TAM theory and digital transformation theory, this study developed and tested a model and hypothesis on how digital transformational leadership, digital strategy and organizational agility influence digital transformation. Alternatively, this paper found that digital transformational leadership, digital strategy and organizational agility positively influence digital transformation and their relationships. This study uses survey data from the Chinese companies -Qihoo and Didi Global as a sample. The sample size is more than 220 respondents. The quantitative text analysis method is used to measure the attention to digitalization of Qihoo and Didi companies. This paper discusses: (1) explore the relationship between digital transformational leadership, organizational agility and digital strategy, and how they affect digital transformation in China (Qihoo360 and Didi Global firm). (2) identify the firm's measurement items of digital transformation organizational in the relationship between digital transformational leadership, digital agility, and digital strategy. The findings of this study provide an advanced understanding of the impact of transformational leadership, digital strategy and organizational agility on digital transformation and the role of digital strategy in Chinese technological companies.

The study aimed to analyze the effect of digitalization strategies on business performance, mediated by organizational innovation in Brazilian family Micro, Small, and Medium Enterprises (MSMEs). This research adopted a descriptive approach with a quantitative methodology, using a sample of 301 Brazilian family MSMEs. Data were collected from studies by the Foundation for Strategic Analysis and Development of Small and Medium Enterprises (FAEDPYME). The theoretical model generated four research hypotheses. Data were processed and analyzed using the structural equation method in SmartPLS 4.0 software. The results confirm the existence of a positive and significant relationship between digitalization strategies, business performance, and organizational innovation, including the mediating effect. The findings highlight the importance of digitalization strategies and organizational innovation in driving the business performance of Brazilian family MSMEs. This study contributes to strategic management practices in family businesses by identifying that effective digitalization strategies and innovation practices allow significant advancements in business performance and subsequent organizational innovation. Thus, they can guide the development of more effective business policies and practices, contributing to the competitiveness of family businesses in the contemporary market.

PurposeSuccessful digital transformation involves all areas which bring new impacts and challenges to the leadership of the enterprise. From the perspective of organizational identification, the authors construct a theoretical model of digital leadership–digital strategic consensus–digital transformation and explore the different moderated mediation effects of diversity types.Design/methodology/approachThis paper obtains data from 351 Chinese science and technology enterprises and uses regression analysis and bootstrap analysis to test the research hypotheses.FindingsThe results demonstrate that digital leadership has a positive impact on digital transformation. Digital strategic consensus partially mediates the linkage between digital leadership and digital transformation. Disparity diversity and variety diversity positively moderate the mediating role of digital strategic consensus between digital leadership and digital transformation, respectively; and separation diversity negatively moderates the mediating role of digital strategic consensus between digital leadership and digital transformation.Originality/valueThe research innovatively measures digital leadership and digital transformation. It expands the application of leadership, strategic consensus, diversity and other related theories in a digital context and provides a decision-making basis for enterprises' digital transformation.

PurposeResearch of currently limited literature sees Robotic Process Automation (RPA) as an important tool at the tactical level. However, the literature has not considered its potential contribution to creating competitive advantages. This paper aims to link RPA and Resource-based view (RBV) literature, proposing a conceptual framework boosting RPA research as part of an organizational AI strategy.Design/methodology/approach This study applied a Systematic Literature Review (SRL), combining bibliometrics and content analysis. This study also built a new framework based on the updated RBV model that was transformed based on the RPA literature review results.Findings By bridging the two bodies of literature on RBV and RPA, this study manages to show the strategic side of the technology. Therefore, this study brought to light the most updated fundamental concepts of complementarity and scale-free fungible resources from RBV theory and AI technologies, applied to the domains of RPA, information systems and information technology (IS/IT) through the development of a new theoretical lens. Also, this study was able to elaborate on a new conceptual framework for AI strategy formulation to help organizations on their journey to AI utilization.Originality/value The authors did not find any research that has shown the strategic side of RPA, nor any that has used a theoretical lens based on the RBV theory to show this side. To the best of the author’s knowledge, this study seems to be the first to make the case for RPA's strategic potential.

A lack of entrepreneurship understanding causes students to think about becoming employees rather than entrepreneurs (Athia et al., 2018). This study aims to attempt to teach students why it is so crucial to start their own businesses and encourage the growth of an entrepreneurial mindset by conducting an introduction and deepening of the business model canvas (BMC). BMC is a template that is used to describe what kind of business we want to build, or what kind of business we are currently running as a whole and from various aspects (Elliyana & Sudrajat, 2020). The researchers utilized structural equation modelling (SEM) method with LISREL 8.80 to analyze the data from 200 respondents. The findings reveal that entrepreneurial interest increases with the number of client categories, value propositions, channels, customer relationships, income streams, key resources, key activities, important partnerships, and cost structures. The originality of this research lies in the significant influences of the BMC on students’ mindset, entrepreneurship methods, business elements, and strategy. The visualization model presented by BMC is able to facilitate students in business, improving creativity, simple thinking, collaborating throughout elements needed in running a business, as well as leveraging opportunities.

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Digital strategy alignment is a dominant concern for today ’ s managers and information systems researchers. Yet research in this area remains fragmented, particularly on the digital strategy alignment of small and medium-sized enterprises (SMEs), which is concerning owing to their value to European economies. Employing dynamic capabilities as an analytical lens, we investigate how 43 British, Irish, Italian, and Spanish SMEs, across five industry sectors, enact digital aligning. We identify a model of digital alignment comprising five phases, which we term “ passive acceptance, ” “ connection, ” “ immersion, ” “ fusion, ” and “ transformation, ” as well as the specific combinations of sensing, seizing, and reorganizing capabilities associated with each phase. Our model provides a holistic, practice-based perspective and highlights the role of micro-behaviors and leadership in SMEs implementing digital strategy.

The rapid growth of digital technologies and the extraordinary amount of data that devices and applications collect each day are increasingly driving companies to radically transform the business architecture through which they create and appropriate value. However, companies may fail to extract value from digital transformation due to the disconnection between strategy formulation and strategy implementation. Through the analysis of three case studies of firms that digitally transformed their business—namely ABB, CNH Industrial, and Vodafone—this article presents a framework than can help companies implement their digital transformation strategy and thereby renovate their business model.

Digitalization and digital strategy have become one of the variant concepts these days since the fourth industrial revolution 4.0. The earlier debate a on the role of digital strategy and degree of digitalization for environmental and sustainable performance of small and medium enterprises (SMEs) is at its nascent stages. This study aims to investigate the impact of digital strategy and digitalization on the environmental performance in Pakistani SME’s during the pandemic times. In addition, it explores the mediating role of five measures of digitalization degree such as overall digitalization degree (ODD), digitalization methods (OM), digital technology adaptation (DTA), digital product services (DPS) and digital processes (DP). This study collected data from 298 respondents using random sampling technique. The unit of analysis was managerial staff and employees working for the organization for last 5 years. To investigate the relationship between constructs, we considered Structural-equation modeling (SEM) using SMART-PLS. Building on the contingency theory, the findings of the research reveal that digital strategy showed a positive impact on digitalization measures but negatively impacted on overall environmental performance. In addition, (DP) ODD, OM, and DPS showed a (negative) positive meaningful impact on environmental performance and (partially) fully mediated the relationship between digital strategy and environmental performance. The digital strategy failed to improve the environmental performance however the role of digitalization is crucial to ensure environmental sustainability. Digital strategy alone fails to alleviate the pressure on environmental performance however excessive digitalization can aggravate the adverse consequences on environment. This research provides useful implications for governments and policymakers to avoid excessive digitalization.

This paper investigates how leaders of hybrid organizations can develop flexible mental models − or “agile minds” − to navigate digital strategy under uncertainty. The study introduces AI-assisted scenario thinking as a cognitive scaffold that reduces cognitive load and enhances leaders’ adaptive capacity. The paper adopts a conceptual, propositional theory development approach. Drawing on Cognitive Load Theory and the Human–AI Collaboration (HAIC) framework, it develops the “5F framework” (Foundation, Forces, Focus, Futures, Formations) and the corresponding five novel propositions, including an extended proposition. Each stage explains human–AI collaboration process in scenario thinking that allocates tasks between humans and AI according task complexity and levels of uncertainty (complementarity, substitution, symbiosis). The paper integrates HAIC into scenario thinking process and theorizes five propositions showing how AI-assisted scenario thinking reduces extraneous and intrinsic cognitive loads while enhancing germane load for leaders and decision-makers. By shifting from rigid, means-end problem solving toward forward-working thinking, leaders can better revise schemas, recognize weak signals, and craft adaptive strategies under uncertainties in the digital age. The 5F framework provides managers with a structured method to leverage generative AI as a cognitive partner in scenario thinking. It clarifies when AI should complement, substitute, or co-evolve with human reasoning, offering a practical pathway to reduce mental overload while enhancing strategic agility. This study extends scenario thinking literature by offering a cognitive-process explanation of how AI-assisted foresight support strategic adaptability under certainty. Rather than proposing a new foresight method, this paper contributes a theoretically grounded framework that integrates Cognitive Load Theory and Human–AI Collaboration. This paper explains why and when scenario thinking can facilitate adaptive mental model development in digitally intensive organizational context.

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Purpose This study investigates the strategic dimensions of digital transformation in business, focusing on the development and implementation of a digital strategy. It explores the evolution of digital services, highlights key steps in digital transformation, and introduces the Hoshin Kanri model as a tool for structuring digital transformation strategies. The aim is to equip organizations with frameworks to enhance competitiveness and adapt to technological advancements. Design/methodology/approach The study employs bibliometric analysis using Scopus and VOSviewer to examine global research trends in digital transformation strategy. The Hoshin Kanri methodology is adapted to design a strategic framework for digital business transformation. A combination of systemic, synergistic, and critical evaluative approaches underpins the analysis, alongside a review of literature spanning business management, digital ecosystems, and strategic planning. Findings Key findings include the identification of five steps in digital transformation strategy development, ranging from vision formation to digital acceleration. The Hoshin Kanri model is presented as a novel adaptation for digital strategy, integrating technology, human resources, customer orientation, processes, and financial planning. The analysis underscores the role of integrated approaches in mitigating risks and enhancing the efficacy of digital transformations. Originality/value This study is the first to adapt the Hoshin Kanri model specifically for digital business transformation. It provides a comprehensive strategy roadmap that aligns digital transformation with corporate objectives, organizational culture, and stakeholder needs, offering practical insights for businesses navigating the Web 4.0 era.

Digital transformation (DT) fundamentally reshapes business models (BMs) across emerging economies, yet limited empirical evidence exists regarding the underlying mechanisms driving this transformation (Rane et al., 2024; Li et al., 2024). This study investigates the impact of technological, organizational, and environmental factors on DT levels and subsequent BM innovation. By integrating the technology-organization-environment (TOE) framework with BM innovation theory, we developed a conceptual model that was tested through structural equation modeling (SEM). Data were collected from 319 firms across multiple industries in Vietnam using validated scales. Bootstrap analysis confirmed the model’s reliability and the validity of hypothesis testing. The results reveal that technological readiness, organizational capabilities, and environmental pressures significantly predict DT levels, which in turn influence BM innovation. Technology infrastructure investment emerges as the strongest predictor of transformation success. These findings extend the application of the TOE framework to emerging market contexts and provide actionable insights for firms pursuing digital BM innovation. The research limitations include a single-country focus and a cross-sectional design. Future research should examine longitudinal transformation patterns across diverse emerging economies to validate these relationships.

This study investigates the influence of Digital Business Strategy (DBS) and Artificial Intelligence (AI) adoption on corporate competitiveness among companies in Indonesia. Using a quantitative, cross-sectional design, data were collected from 85 managerial respondents representing various industries through a structured questionnaire using a 5-point Likert scale. The data were processed with SPSS 25, including descriptive statistics, tests of validity and reliability, classical assumption diagnostics, and multiple linear regression. The empirical results show that both DBS and AI adoption have positive and statistically significant effects on corporate competitiveness, whether examined separately or jointly. The regression model indicates that the two predictors together explain 50.6% of the variance in competitiveness, suggesting that digital transformation constitutes an important driver of strategic performance. DBS emerges as the dominant predictor, underscoring the need to align digital initiatives with organizational goals, resources, and market positioning. AI adoption further strengthens competitiveness by supporting data-driven decision making, improving operational efficiency, and enhancing customer value creation. The findings highlight the growing importance of digital capabilities for firms seeking to sustain advantage in Indonesia’s dynamic, technology-intensive business environment and provide practical insights for managers and policymakers aiming to accelerate digital transformation in emerging markets. Future studies may extend this work by using larger samples, additional performance indicators, and comparative settings across countries or sectors.

This convergence of sustainability imperatives and digital transformation is reshaping the future of the fashion industry, particularly for local micro, small, and medium enterprises (MSMEs). However, the integration of digital value chains into sustainability strategies remains underexplored, especially in emerging economies. This conceptual paper aims to develop a theoretical framework that positions digital value chain innovation as a strategic enabler of sustainable competitiveness in the local fashion industry. Using content analysis on 60 journal articles published between 2012 and 2025, the study identifies dominant variables. Drawing from the domains of digital transformation, green marketing, and customer value theory, the proposed model illustrates how digitalization of core value chain activities—including sourcing, production, promotion, distribution, and after-sales service—can enhance customer-perceived value through transparency, ethical branding, and operational efficiency. The framework highlights how these innovations contribute to long-term brand trust and competitive advantage in sustainability-oriented markets. This paper contributes to the growing body of literature on sustainable digital marketing and offers practical insights for policymakers and fashion entrepreneurs striving for ecological, social, and economic sustainability alongside prevailing analytical methods, including Structural Equation Modeling (SEM) and Multiple Linear Regression.

The transformation and reform of business model triggered by digitalization widely occurs in life, travel, finance, entertainment and other related fields closely related to the public. At the same time, it also involves a large number of actors and elements. Sorting out and clarifying their action network will help to comprehensively present the network system of digital business and its future development. Based on the actor network theory (ANT), this paper introduces human and non-human actors such as government, society, enterprise, public and network, data and algorithm, and analyzes their relationship in the process of action translation and network map to explain the integrated actor network system. Furthermore, it puts forward three thoughts and prospects on the future development of digital commerce, namely, the role positioning and coordination of actors, value-free and social adaptation, and the promotion of the balance between human and technology.

No abstract available

This paper aims to answer questions around digital strategy development in organizations providing clarity, specifically to leaders and ICT departments, the role of human resource and process innovation in the digital strategy implementation. It includes the lessons learned from 256 SMEs from Serbia as business representatives, their attitudes given on the topic of the research in the experimental research provided in 2020 in Serbia. In the focus of the paper is the financial industry sector with insurance and accounting services. The authors of the paper explored the impact of the four variables: leadership, ICT, business processes and business model as independent, to the digital strategy risks, as dependent variable. Also is explored the possible decision making impact on the digital strategy issues brought by these influences. The hypothesis of the research, that the digital strategy risk of SMEs organizations would be significantly influenced by four other risks, leadership, ICT, business processes and models in further medium term, is confirmed. Descriptive statistical analysis, IPA decision-making methods, Pearson’s correlation, with the attitudes of the SME representatives given by the method of Likert’s valuation scale are used in the paper. The key results of the research would contribute to better understanding the opportunities and threats of digitizing implementation in the strategy creation, needed investment and the agility of SMEs in these processes.

This study aims to investigate the causal relationship between consumer behavior and purchasing experience through food delivery applications. Data were collected from 680 participants using random sampling, comprising students who use food delivery applications. Data were analyzed through structural equation modeling (SEM). The results indicate that consumer behavior focuses on providing effective information, with media design related to user interaction, trust, shopping pleasure, and ease of use having a positive effect on product loyalty. Moreover, the same media design factors positively influence non-rational purchasing decisions, as demonstrated by the causal relationship model. According to concordance verification, the model showed a good fit with a ratio of chi-square minimum and degrees of freedom (CMIN / DF) = 1.74, goodness-of-fit index (GFI) = 0.86, comparative fit index (CFI) = 0.96, and root mean square error of approximation (RMSEA) = 0.05, consistent with empirical data. These findings highlight the role of product loyalty and non-rational purchases in shaping business opportunities in the growing food delivery sector (Alalwan, 2020).

No abstract available

This study examines the impact of responsible digital innovation on innovation performance, with a focus on the mediating roles of digital organizational culture and digital strategy and the moderating role of digital literacy in Ghana's technology sector. Data were collected from 613 employees, managers, and digital leaders across high-tech firms using a time-lagged survey design. Structural equation modeling was employed to assess the relationships among the variables. The findings revealed that responsible digital innovation boosts innovation performance by promoting a collaborative and adaptable digital organizational culture and strengthening digital strategy through ethical alignment. The results indicated that digital organizational culture mediates the relationship between responsible digital innovation and innovation performance, highlighting its role in converting ethical principles into tangible innovation outcomes. Similarly, digital strategy mediates the relationship between responsible digital innovation and innovation performance, highlighting its importance in aligning digital activities with organizational goals. However, digital literacy did not moderate the relationship between digital strategy and innovation performance, indicating that strategy implementation outweighs literacy levels in driving innovation outcomes. These results provide theoretical insights into the mechanisms linking responsible digital innovation to innovation performance, emphasizing the importance of integrating ethical innovation practices into organizational culture and strategy. Practically, the study suggests that firms should prioritize fostering a collaborative digital culture and aligning their strategic objectives with responsible digital innovation principles to drive innovation. This study contributes to the understanding of how responsible innovation can drive sustainable technological advancements in resource-constrained contexts. Plain language summary How digital culture, strategy, and skills affect innovation success This study explores how Responsible Digital Innovation (RDI) influences innovation performance, focusing on the roles of digital organizational culture, digital strategy, and digital literacy in Ghana’s high-tech sector. Using a quantitative survey of 613 participants, the research examines relationships between these factors. The findings highlight that RDI positively affects digital organizational culture, which fosters collaboration, transparency, and adaptability, essential for successful digital transformation. RDI also enhances digital strategy, aligning innovation activities with organizational goals to improve performance. Additionally, RDI directly boosts innovation outcomes by encouraging ethical and sustainable practices. Digital organizational culture and strategy are shown to mediate the link between RDI and innovation performance. A supportive culture promotes ethical behavior, collaboration, and continuous learning, while a robust digital strategy ensures alignment of resources and goals, enabling effective innovation. However, digital literacy did not significantly moderate the relationship between strategy and performance, suggesting that a strong strategy can overshadow varying literacy levels. The study underscores the importance of fostering a strong digital culture and crafting a well-defined strategy to harness RDI for better innovation results. While highlighting the transformative potential of RDI, it calls for future research on its applicability across different contexts and the role of digital literacy in shaping innovation outcomes. Practical recommendations include promoting ethical innovation values, aligning strategy with digital transformation goals, and investing in organizational culture development. This work contributes to understanding the interplay of culture, strategy, and innovation in driving sustainable technological progress.

Global organizations are still facing challenges in achieving sustainable performance despite the surge in digital technologies. It is imperative that firms invest in digital capabilities to secure sustainable market performance in the face of a barrage of novel inventions. Today, ensuring a resilient future demands business to focus on digital ambidexterity capabilities (i.e., exploitation and exploration), digitalized strategy adoption, and digital transformation. This study investigates the intricate dynamics between digital capabilities and digitalization strategies and their impact on sustainable business performance. The research employed a questionnaire-driven methodology to gather data from managerial personnel within industries. Results show that digital exploitation and exploration capabilities significantly enhance sustainable business performance. The research also establishes the beneficial effect of adopting a digitalization strategy on business performance and innovation. Market-driven business model innovation emerges as a critical factor, not only driving sustainable performance but also serving as a mediating link between various digital strategies and business success. Moreover, the study highlights the importance of digital leadership capabilities, further strengthening the relationship between innovative business models and sustainable performance. The findings underscore the synergistic effect of digital competencies and strategic digitalization in promoting sustainable and innovative practices in today's digital-driven business landscape.

Companies face significant challenges in implementing digital transformation, often because of the use of fragmented strategies and limited cross‐functional coordination. Furthermore, not all digital innovations align with sustainability objectives. In response to this complexity, recent European Union directives have introduced digital product passports (DPPs) as strategic instruments to bridge the gap between digitalization and sustainability. Although promising, DPP implementation remains in its infancy and requires robust data governance to mitigate the risk of information overload. The present study integrates business perspectives into the design of DPPs, with a particular focus on the textile industry. It explores how DPPs can enhance competitiveness, facilitate sustainability monitoring, and promote circularity. Drawing on insights from textile firms and consulting support, this research employs multicriteria decision‐making methodologies—specifically, the analytic hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS). The findings reveal a strong alignment between these methodologies and a shared recognition of the strategic value of DPPs, particularly in facilitating access to information on product reuse, repair, and recycling. Additionally, the analysis highlights consultants' emphasis on the “Made in Italy” designation as a key differentiator. Overall, DPPs are shown to advance the development of circular business models in the textile sector by supporting three strategic priorities: material traceability, repair guidance, and optimized recycling pathways.

PurposeThis paper's purpose centres on advancing the current financialisation strategies within digital transformation (DT) through a rebalanced synthesis of both financialisation and people/centric, non-financialisation strategies of the DT field. Based on empirical data from Bahrain's energy sector, a new framework on People-centric, Sustaining Network Leadership is developed, capturing DT's human values deficit and proposing a new model on financialisation and non-financialisation strategies showing ‘how’ and ‘why’ DT is implemented in contemporary organisations.Design/methodology/approachThis study conducted a mixed methodology of narrative interviews, case studies and reviewed significant contributions from the DT, leadership and change management debates. A total of 26 operational and high-level leaders from Bahrain, 8 top energy companies and Braun and Clarke's 6-phase analysis were combined to form four empirical thematic bundles on ‘how’ and ‘why’ leaders adopted financialisation and non-financialisation strategies to resolve organisational sustainability issues in an Arabic context.FindingsFour sets of findings (bundles 1–4) highlight participants' financial and structural understanding when implementing DT initiatives, the different leadership styles ranging from authoritarian to network leadership, the socio-economic, political and cultural ramifications of their practices and the urgency of staff reskilling for organisational resilience and strategic sustainability. Based on the eight energy cases and interviews, a new values-driven, People-centric Sustaining Network Leadership Model is developed to show a more effective and efficient use of financial and non-financial resources when organisations implement DT initiatives in efforts to resolve global energy sustainability problems.Research limitations/implicationsLeadership, change management, DT, energy and environmental sustainability is a huge area of scholarship. While new studies emerge and contribute to this growing body of knowledge, this investigation has focused on those that significantly highlight how to make effective use of financialisation and non-financialisation resources. Therefore, all the literature on the topic has not been included. Although this study has filled the non-financialisation gap in current DT studies, a further rebalancing of the financialisation versus non-financialisation debates will be needed for theoreticians, practitioners and policy makers to continue addressing emerging and more complex socio-economic, political and cultural issues within and beyond organisations. Limitations are the study's focus on the Bahrain energy sector and the limited sample of 26 leaders.Practical implicationsThe study provides practitioners and policy makers with an approach for the successful implementation of DT initiatives in the oil and gas sector. For academics, this study provides empirically unique and interesting thematic bundles, insightful analyses into leadership, organisational change, digital transformation and network leadership theories to develop an innovative and creative People-centric, Sustaining Network Leadership Approach/Model on the practical barriers, implications/impacts of various leadership styles and potential solutions via a socio-cultural values-based alternative to the current financialisation discourse of DT.Originality/valueWhile there is a growing body of literature on DT, Leadership and Organisational Transformation and Change, there is a dearth of scholarship on the human-orientated strategies of DT implementation outside of western contexts. A contemporary and comprehensive, empirically evidenced analysis of the field has led to the development of this study's People-centric, Sustaining Network Leadership model which frames, captures, synthesises and extends the dominant cost-minimisation rhetoric of DT discourse to include a shared set of leadership practices, behaviours, intentions, perceptions and values. This helped to reveal the previously missing ‘how’ and ‘why’ of DT’s operational and strategic implementation.

In the era of the digital economy, digital technology brings new opportunities for enterprises’ development. The degree of enterprises’ digital transformation determines their development level and potential. At present, China’s “double carbon” policy is having a profound impact on the industry. The relationship between digital transformation strategy and environmental, social, and governance (ESG) performance is analyzed based on the digitalization and sustainable development goals of enterprises, and on the basis of positioning enterprise digital transformation level through the strategic alignment model (SAM). Data are collected by questionnaire survey from 224 large manufacturing enterprises in China as a sample for empirical testing by the hierarchical regression method. The empirical results show the following. (1) Digital transformation strategy has a direct positive and significant impact on enterprise ESG performance. Specifically, it is reflected in the two dimensions of digital transformation strategy, namely business digitalization and platform digitalization, which have a significant direct positive impact on enterprise ESG performance. (2) Enterprise green innovation plays a significant intermediate role in promoting the relationship between digital transformation strategy and enterprise ESG performance. (3) The two dimensions of green innovation, namely green process innovation and green product innovation, both play a partial mediating role in promoting business digitalization and platform digitalization development level to enterprise ESG performance, respectively. It can be concluded that business digitalization and platform digitalization can improve enterprise ESG performance by promoting green process innovation and green product innovation. Therefore, enterprises should clarify the direction of development of their digital transformation strategy, emphasize green innovation, and continuously improve their ESG performance to create favorable conditions for achieving sustainable development.

Ever increasing demand for customization and product diversity from the customers has made it important for firms to predict changes in the customer demand patterns and adopt accordingly. Customer integration allows firms to understand customers and respond to their particular needs in a better way. This study investigates the mechanisms through which customer integration is developed and affects supply chain performance. We develop a structural model underlining the role of market orientation and supply chain strategy as factors affecting the degree of customer integration. We also investigate the contingency role of marketing – supply chain integration in these relationships. We test the hypothesized model using data from Pakistani manufacturing organizations using structural equation modelling. Our results provide support for the study hypotheses except that marketing-supply chain alignment does not moderate the relationship between supply chain strategy and customer integration.

Digital transformation in the global higher education industry determines the future roadmap to a sustainable education management strategy. This research paper aims to develop a qualitative model that advocates how digital transformation as a propelling force could be used to build competitive advantages for universities. Building competitive advantage is a relative, evolving, and important concept in strategy formulation. In recent years, specifically in the education industry, the notion of building competitive advantage is challenged by global phenomena such as digital transformation globalization, information exchange, digitization and social media in most of the global industries. These phenomena have collectively made the process of building competitive advantage rapidly changing, short-term and contextual. These findings aid the evolution of strategic management practices in universities by providing empirical insights in determining the impactful changes and their connection to evolutionary learning. It also stresses the importance of using the developed model as a decision support system to generate, regulate and retain student experience and expectations. This research paper provides first-hand insight into the impactful changes affecting universities’ vision and how they can turn these changes to their advantages and set a road map to design-develop models to integrate and regulate these essential changes in their strategies using evolution learning mechanism and digital transformation strategy.

用户粘性不再仅仅是重复购买行为的表征,其本质是用户对平台或品牌产生的心理依赖,信任归属与情感联结[5].这种基于情感认同的粘性,能够有效抵御外部竞争冲击,激发用户的自发 ...

研究不仅识别了服务水平,性价比,配套设施及资源维护等方面的不足,更从电子商务运营和网络营销角度,提出了包括数据驱动的服务优化,动态定价,线上线下融合,以及基于用户生成 ...

在电子商务与社交媒体主导的数字化时代，老字号企业面临品牌传播与市场竞争的双重挑战。以镇江恒顺醋业为研究对象，探讨其在互联网营销环境下的转型升级。

本文以SICAS营销模型为分析框架,对电商平台生态下新零售领域的两大代表性企业——盒马鲜生与京东七鲜的营销策略进行系统性对比研究.研究发现,两家企业都注重全渠道融合, ...

游客可一次性购买全程服务，平台自动协调各地资源并生成电子行程单，而后同步建立数据共享与协同营销机制。参与联动的景区通过平台共享脱敏后的游客画像与消费数据，共同分析 ...

新零售场景重构的目标是实现线上线下渠道的功能互补与数据贯通,创造便捷性与体验感兼具的无界消费旅程.首先,线下触点应摒弃高成本的独立“前店后仓”模式,优先采取轻资产策略 ...

本文基于价值共创理论,从用户参与,社交传播,品牌共建与平台机制四个方面,系统分析马蜂窝的营销策略与实践逻辑.研究发现,平台虽在激发用户互动和增强品牌影响方面取得成效, ...

本研究旨在系统剖析DTC模式如何引领传统企业进行深层次的营销变革，并深入探讨其转型过程中所面临的信息化挑战。论文首先解构DTC模式以“直接用户关系”为核心的本质特征， ...

顾客契合是顾客基于内在动机，在与品牌互动中产生的认知、情感与行为上的多维、主动投入，是品牌保持长期竞争优势的关键[5]。CEO凭借其独特特质与人格魅力，具备激发深度顾客 ...

实体店体验应被视为顾客旅程中的一个环节，企业应积极拓展线上平台，鼓励更多软件企业融入O2O (线上到线下)的商业生态系统中[2]。此后，随着移动互联网技术的快速发展 ...

企业应抓住机遇，充分利用现代信息技术，从以产品为中心的品牌营销模式向以客户为中心的精准营销模式转变，为客户提供个性化的产品和服务，以准确定位他们的偏好。基于数据驱动 ...

网络营销有助于拓展农产品的销售渠道；有助于农村产业建立自己的品牌形象；为农产品带来更多的销售机会；还能够为农村产业提供市场信息、技术交流、产业链合作等机会[3]。4I ...

本研究融合技术特性、行业实践与用户行为逻辑，系统梳理了三维高斯泼溅在电商场景中的应用路径与商业价值。研究表明，三维高斯泼溅通过支持用户主导的多角度探索、高保真材质 ...

随着数字经济的快速发展，电商平台通过数字赋能实现了商业模式的革新与生态系统重构，推动了产业链各环节的数字化转型与优化。本研究旨在探讨电商平台在数字赋能过程中所 ...

本文聚焦于互联网时代下，深入探究网红景点旅拍馆与电商协同发展这一新兴产业发展状况。以贵州千户苗寨、贵阳青岩古镇、福建泉州簪花的典型案例为切入点， ...

... 接触到购后服务的全旅程.从首次在线上接触品牌信息时的内容吸引力,到咨询环节的响应速度与专业度;从试驾预约的便捷性,到购车流程中数字化操作的流畅度;再到提车后社群 ...

摘要: 商业银行数字化转型的核心就是要以客户为中心,敏捷组织则是快速响应市场变化和客户需求的基础保障.对大多数中小银行来说,尚需结合实际情况对敏捷转型的方向路径 ...

本研究将通过理论演绎与逻辑推演，试图构建一个连接微观评论内容、中观消费者心理与宏观营销策略的整合模型，以期为深化数字消费行为理论、提升电商平台精细化运营效率提供 ...

本文基于“4R”营销理论,深入分析了蔚来新能源汽车的营销策略.首先对蔚来在关联,反应,关系和回报四个方面的营销策略表现进行了分析,随后针对其中存在的问题提出了优化 ...

本文将基于S-O-R理论分析星巴克数字化营销从技术应用到行为改变的内在作用机制，探讨星巴克咖啡如何利用大数据转型提升品牌私域流量，并将私域流量如何进行转化的问题。

近年来，随着“互联网+”战略的深入推进，餐饮行业数字化转型已成为学术界和产业界共同关注的热点问题。 ... 在顾客体验层面，打造无缝衔接的服务旅程。例如，允许顾客线上点餐到店 ...

借助数字化平台与新媒体营销,肇兴侗寨探索出“互联网+ 侗歌文旅”新模式,通过在线直播“云上侗歌节”等方式,激活了旅游新流量.在此基础上,可以结合肇兴侗寨等知名旅游景点,深度 ...

当游客的视线被持续引导至设备界面,追踪虚拟标注与动画演示时,其对真实海洋环境的多感官沉浸——如海风的触感,潮汐的气味与生态系统的细微声响等可能被削弱.更进一步的隐忧 ...

1) 用户转化率最高的三个城市为：北京(7.84%)，深圳(7.79%)，上海(7.28%)。可继续重点在该三个城市深入推广。 2) ...

本文通过建模的方式，利用线性模型和非线性模型，尤其是机器学习模型，以转化率为目标进行回归预测。本文的研究意义及目的在于帮助平台型电商进行转化率的预测，以辅助根据不同 ...

研究据此构建“内容运营–信任机制–算法协同”模型，通过峰终定律强化内容记忆点、建立用户证言可视化机制及优化LBS标签匹配，实现头部博主咨询转化率提升19.8%。该模型揭示了 ...

我们定义一个网络电视用户行为计算状态模型，从单频道、个体用户和群体用户三个角度对一个大型IPTV系统的用户行为数据进行计算与分析，对观看时长、在线人数及其在24小时内的 ...

感知价值又作为中介变量，引导用户在平台中的浏览深度、购买转化率及平台忠诚度形成分层分化的行为表现[10]。从依恋风格出发识别用户差异，不仅有助于平台实现更具针对性的 ...

摘要: “社交+ 电商”模式通过社交平台与电子商务的深度融合，重构了传统电商的运营逻辑及营销路径。该模式以社交关系链为传播媒介，以用户生成内容为核心驱动力，形成了 ...

在大数据的基础之上,AIGC对用户进行行为分析,将用户有可能感兴趣或需要的内容进行推送,提高用户的满意度,拓宽受众的认知渠道.同时,个性化的信息推送能够动态更新,根据用户 ...

本文提出电商平台的品牌年轻化本质是一个以用户为导向、以数据为驱动、以设计为整合手段的动态闭环系统，系统性探讨实现品牌年轻化的设计策略体系和实施路径，推进品牌年轻化 ...

首先，改变以往单一票务模式，建立票务信息发布、查询、活动讲座预约等票务功能，开发手机扫码、微信公众号服务系统，拓展多渠道支付方式。同时，积极实施“全网络营销”战略， ...

面对渠道多元化与消费个性化并行的市场环境，快消品销售模式创新需深度整合大数据、物联网及人工智能等数字技术，破解渠道协同不足、供需匹配困难等核心挑战。通过构建 ...

主播通过实时互动、解答疑问增强消费者信任，并通过商品演示直观展示使用效果，提升购买意愿。其专业性、外貌、口才等个人特征也显著影响观众吸引力和商品曝光度。虽然目前 ...

从网络营销策略角度看，城市形象的打造本质上是在“液态社会”中为个体提供短暂“情感锚点”——让人们在不确定性中找到归属感，这正是城市形象营销的核心逻辑。淄博、哈尔滨、贵州 ...

在电商环境下，以消费心理为基础制定恰当的营销策略更有利于网络营销行业的良好发展。第一，满足消费者个性化需求。现在人们注重生活品质，他们会选择个性化定制产品。

本研究旨在探讨文旅融合视域下青岩古镇的电子商务营销策略,通过分析其资源禀赋,现状特点,提出针对性的电商营销方案.这不仅有助于提升青岩古镇的市场竞争力,也为其他同类 ...

本研究基于扎根理论，系统剖析了社交媒体在独自旅行体验中扮演的矛盾角色，揭示了其在情感联结、文化体验与实用功能三个维度上的双重性。研究发现，旅行者并非被动承受这种 ...

通过提高大学生的财务知识教育、引导合理设定和管理心理账户，以及创建健康的社交媒体消费环境等措施，共同促进大学生形成理性的消费习惯和观念。本文为理解大学生线上消费 ...