AI-Driven Omnichannel Marketing and Customer Experience : A Bibliometric Overview

Покупки, совершаемые на онлайн-платформах, в значительной степени основаны на искусственном интеллекте (ИИ), который формирует покупательское поведение потребителей. Для изучения намерений повторных покупок в данном исследовании использованы данные об ИИ, вовлеченности в социальные сети, оптимизации коэффициента конверсии, опыте использования бренда и предпочтениях бренда. Был проведен опрос с помощью анкеты, разосланной 355 респондентам, которые хотя бы раз покупали или пользовались услугами, предлагаемыми онлайн на любом сайте, связанном с авиацией. Гипотезы исследования были проанализированы с использованием Amos V.22. Эмпирические результаты показывают, что ИИ повлиял на вовлеченность в социальные сети, восприятие бренда, предпочтения к бренду и оптимизацию коэффициента конверсии. Оптимизация коэффициента конверсии и взаимодействие с социальными сетями также влияют на предпочтения и опыт использования бренда, которые, в свою очередь, влияют на намерение совершить повторную покупку. Кроме того, связь между искусственным интеллектом и намерением повторной покупки обусловлена вовлеченностью в социальные сети, опытом работы с брендом, оптимизацией коэффициента конверсии и предпочтениями бренда. Результаты исследования могут помочь авиакомпаниям в разработке ИИ и создании более эффективных кампаний по брендингу и маркетингу, чтобы повысить желание клиентов совершать повторные покупки. Исследование также показало, что использование ИИ в маркетинге значительно улучшило предпочтения бренда, что впоследствии повлияло на желание потребителей совершать дополнительные покупки. Кроме того, для улучшения долгосрочных коммерческих показателей и привлекательности бренда авиакомпаниям рекомендуется сосредоточить усилия по созданию бренда на ИИ и, таким образом, увеличить инвестиции в ИИ и технологии бронирования, как для привлечения новых клиентов, так и для удержания существующих.

In retail, strategies in increasing sales through innovation and customer experience can be a critical factor in business success. In this case, artificial intelligence can be used to analyze customer data and market trends to develop innovations and customer experiences that can increase sales. To achieve this goal, it is necessary to implement an effective data management strategy and the use of appropriate technology to collect and analyze customer data in real-time. Thus, retail businesses can understand customer behavior, and design innovations that suit their needs. In addition, artificial intelligence can help retail businesses in the development of effective and relevant marketing strategies, leading to increased customer traction and experience. Through data analysis, retail businesses can identify market trends and customer needs, and develop innovative solutions that can improve customer experience. In addition, artificial intelligence can help retail businesses in developing effective and relevant marketing strategies, leading to increased customer attraction and experience.

Objectives: This study aims to analyze the effect of Artificial intelligence and gamification on online purchase intention, as well as the role of customer experience as a variable that mediates the effect of artificial intelligence and gamification on online purchase intention. The marketing approach in today's era tends to lean towards digital personalization using Artificial intelligence and gamification to improve customer engagement and experience. This is ongoing with the fast rate at which technology has been expanding. The development of artificial intelligence has increased consumer happiness even more, making it even more crucial in the contemporary environment. Also, Gamification has clearly been identified as a method of influencing consumer behavior. The use of game design elements in non-game contexts is known as gamification. Gamification and persuasive technologies have been used for business purposes and to influence customer behavior.Methodology: The method used in this study is a quantitative method using survey research with marketplace users in Indonesia as the object of the research. Data collection which was used is the cross-sectional method by distributing online questionnaires from Google Forms. The research sample was selected using the purposive sampling method in order to obtain 272 respondents from various users (Tokopedia, Shopee, Lazada, Blibli, and Bukalapak users). The data analysis that is used is the path analysis Structural Equation Model (SEM) by SmartPLS 3.0 software. The first stage in data analysis is to recapitulate data on the characteristics of the respondents. The next step is to measure the validity and reliability using discriminant validity, convergent validity, composite reliability, and Cronbach's alpha. Then, to test the inner model, a Goodness of Fit test was carried out through R-Square and significance testing by interpreting path analysis values, T-values, and P-Values.Finding: In this research conducted on marketplace users in Indonesia, it was found that Artificial Intelligence and Gamification are determinants of Customer Experience but these two variables cannot directly support Online Purchase Intention. Further findings indicate that Customer Experience can be an important determining factor for Online Purchase Intention. Customer experience can strengthen the online purchase intention among marketplace users.Conclusion: The result of this study shows that Artificial intelligence and gamification cannot affect online purchase intention directly but artificial intelligence and gamification can affect online purchase intention indirectly through customer experience

This study synthesises current understanding and developments in omnichannel marketing, provides a comprehensive and structured review of this domain, and suggests future research directions. The research adopts a structured literature review approach to analyse and synthesise 174 omnichannel-related papers published from 2011 to 2021. Within the omnichannel-related literature, omnichannel marketing is in its infancy stage. We find mature themes such as consumer behaviour, customer decision, and customer experience, as well as emerging topics such as customer engagement and switching experience, thus allowing us to define key trends in omnichannel marketing. We apply a holistic perspective and present a novel and original review of omnichannel marketing within an up-to-date, comprehensive picture of omnichannel-related studies. This study is useful for practitioners as it outlines the pillars of recent developments in omnichannel marketing based on scholarly literature.

The integration of Artificial Intelligence (AI) in retail has redefined customer experience, offering new opportunities for personalisation, service quality enhancement, and continuous service delivery. This study investigates the impact of AI on customers’ experience at Giant Hypermarkets in Klang Valley, Malaysia, focusing on four key areas: personalisation, service quality, hassle-free service, and customer service. Using quantitative methods, data were gathered from 365 respondents to assess the influence of AI-driven services on customer experience. The findings reveal that hassle-free service significantly enhances customer experience, while personalisation, service quality, and customer service show no significant impact. These results suggest that while AI is effective in streamlining operations and reducing customer effort, it may fall short in providing the emotional engagement needed to enhance the overall customer experience. This study highlights the importance of balancing AI efficiency with human interaction, particularly in relational services. This research offers valuable insights for retailers, academics, and small business owners, emphasizing the need to adopt AI technologies that focus on customer convenience and experience while maintaining a personal touch. This study clearly highlights the implications for the retail industry, demonstrating that AI can significantly enhance customer experience, but its strategic integration is crucial to address both operational efficiency and emotional engagement.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0735/a.php" alt="Hit counter" /></p>

The aim of this study is to identify the practical benefits and associated risks generated by the implementation of artificial intelligence (AI) in retail and capitalize on the results by developing a conceptual framework for integrating AI technologies in the information systems of retail companies. To this end, a systematic study of recent literature was conducted by carefully examining the topic of AI implementations. The main results of the documentation were used to substantiate the conceptual framework introduced by the paper. The research revealed a variety of advanced solutions, benefits, but also risks that AI generates in retail, in different segments of the value chain, abbreviated CECoR, from improving the customer experience (Customer Experience, CE) with the help of virtual agents (chatbots, virtual assistants, etc.), to cost reductions (Cost, Co) by using smart shelves, and to increasing revenues (Revenue, R) due to product recommendations and personalized offers or discounts. The proposed conceptual framework is focused on customer profiles and includes recommendations on AI implementations in a retail company, from the perspective of CECoR drivers. The results of the research can be capitalized by practitioners and researchers in the field, who are presented with concrete examples of benefits, challenges, and risks generated by AI technologies. The CECoR framework could be a useful tool for both retail and AI specialists, providing common and clear guidelines for initiating and overseeing projects for integrating AI in a company's information systems. Literature-based CECoR analysis dimensions have allowed the restriction of the research area, which is particularly wide, at the confluence of retail and AI. The originality of the article lies in the CECoR orientation of the research and the conceptual framework focused on customer profiling.

The implementation of omnichannel marketing at AES Motor showroom aims to improve customer experience through effective integration of communication channels. Consumers now conduct marketing interactions through various channels, including physical stores and gadgets, to evaluate products, compare prices, and conduct digital transactions. Omnichannel marketing helps improve customer satisfaction by integrating multiple communication channels, such as physical stores, websites, chat apps, and customer service. This research focuses on how omnichannel marketing can improve the customer experience at the AES Motor showroom, as well as how this strategy can help improve customer loyalty and increase sales. The purpose of this research is to create a conceptual model that can help scholars and practitioners understand the dynamics between omnichannel marketing and customer experience. The results are also expected to provide information on how best to implement integration strategies and provide strategic advice for businesses in the used car retail industry.

This article aims to scrutinize the dynamics of scientific publications devoted to optimizing the customer journey in the retail sector through the application of artificial intelligence (AI) and determines the status of existing research on the role of AI in the retail sector. The research objective was to analyse the pool of scientific publications from the Scopus database to analyse how emerging technologies have improved customer journey (pre-purchase, purchase, post-purchase). The research employed a publication search by article title, abstract and keywords to collect the data set from the Scopus database. The selected publications were visualized using the software VOSviewer 1.6.16.0, and Biblioshiny to perform bibliometric analyses. An initial sample of 356 research articles was collected. After reading the abstract and full article, a final corpus of 149 scientific publications over two decades (1989–2021) was analysed in the study. Our findings suggest the prominence of authors and journal publishing in implementing AI in retail to automate customer journey. The results highlight how the application of AI fosters in improving the different phases of customer journey among the retailing sectors. Banking and fashion are the retailing sectors that have major applications of AI in the customer journey. Further studies should be conducted to gain deeper insights into the emerging use of AI in other sectors of the economy. It was also found from the intensive literature review that in the purchasing and decision-making phase of the customer journey, the deployment of AI is the most. This study analysed the incorporation of AI into the customer journey to highlight its impact on retailing. This study contributes to the literature by adding the lenses of AI in key management areas in retailing.

In the face of growing competition in the home appliances and electronics market, omnichannel marketing is becoming a key tool for attracting and retaining customers. Artificial intelligence, influencer marketing, and augmented reality can increase business efficiency, improve customer experience, and strengthen the competitive position of the Foxtrot brand. The article aims to analyze and substantiate the effectiveness of modern digital omnichannel marketing tools for promoting the Foxtrot brand. The study aims to identify optimal strategies for using influencer marketing, artificial intelligence, and augmented reality to increase brand awareness, improve customer experience, and optimize business processes. The article explores measures to strengthen the Foxtrot brand’s omnichannel marketing through modern digital tools. The author analyzes the impact of artificial intelligence (AI), augmented reality (AR), and influencer marketing on increasing the effectiveness of brand promotion, improving customer experience, and optimizing operations. The author considers the prospects for long-term cooperation with influencers, which will increase brand awareness, expand the audience, and compete with Comfy, which actively involves opinion leaders in its marketing campaigns. It is proposed that a product exchange program for reviews be introduced and a focus on regional bloggers to strengthen positions in local markets. Particular attention is paid to using artificial intelligence to forecast demand, personalize content and price offers, and optimize logistics processes. The authors propose analyzing historical sales data, using machine learning algorithms to identify seasonal trends, automated generation of dynamic discounts, and improving supply chain management to reduce costs and delivery times. Integrating augmented reality is an innovative approach to increase brand trust and reduce product returns. It is proposed to develop, a mobile application with AR functionality that allows customers to virtually evaluate products in their space before purchasing. It is also recommended to launch advertising campaigns with demonstration videos of the benefits of AR to popularize the technology among users. It is concluded that the integrated integration of influencer marketing, artificial intelligence, and augmented reality will help strengthen the Foxtrot brand’s market position, increase customer loyalty, and increase the efficiency of omnichannel sales.

Artificial intelligence (AI) has been widely adopted in the service sector to enhance the customer experience and gain a competitive advantage. However, there are a limited number of papers that focus on the relationship between AI and customer experience, and there is no clear framework to reveal how AI influences the customer experience. Therefore, this paper will address how AI affects the customer experience and develop a conceptual framework of AI applications in customer experience along the customer journey. A two-step research design is adopted in this paper. The first phase aims to identify a framework through an extensive systematic literature review of the relevant databases. The findings cover three main themes: AI experience, AI functions, and AI services. A research framework is created on the basis of the findings. This paper contributes to consumer behavior and services by integrating AI with customer experience and providing a comprehensive framework for guiding future research. The study also offers practical implications for practitioners to enhance customer experience.

Purpose This research is the first to use bibliometric analysis to provide insight into the landscape and forecast the future of customer experience research in the banking sector. Design/methodology/approach We used bibliographic coupling and co-word analysis to delineate the existing knowledge structure after reviewing 338 articles from the Web of Science database. Findings The bibliographic coupling analysis revealed five key clusters: customer engagement and experience in digital banking; customer experience and service management; customer experience and market resilience; digital transformation and customer experience; and digital technology and customer experience—each representing a significant strand of current research. In addition, the co-word analysis revealed four emerging themes: customer experience through AI and blockchain, digital evolution in banking, experience-driven ecosystems for customer satisfaction, and trust-based holistic banking experience. Practical implications These findings not only sketch an overview of the current research domain but also hint at emerging areas ideal for scholarly investigation. While highlighting the industry’s rapid adaptation to technological advances, this study calls for more integrative research to unravel the complexities of customer experience in the evolving digital banking ecosystem. Originality/value This review presents a novel state-of-the-art analysis of customer banking experience research by employing a science mapping via bibliometric analysis to unveil the knowledge and temporal structure.

Omnichannel marketing has become one of the most critical research areas, as the interactions of customers over different contact channels have been becoming increasingly complicated. The study focuses on the effectiveness of omnichannel integration in driving customer satisfaction and loyalty, placing special emphasis on the mediating role of satisfaction. The research will be based on widely accepted frameworks and theories and will seek to establish how dimensions such as synchronization, accessibility, and consistency will affect the customers' experiences. In testing the relationships among the constructs, SEM analysed data from 357 respondents. The method included outer loadings, path coefficients, and mediating effects to establish the significance of various factors. Synchronization was noted as the most influential dimension of omnichannel integration and enhancing customer satisfaction significantly. The results further reveal that while omnichannel integration is not directly affecting customer loyalty, it is doing so indirectly through satisfaction. Secondly, customer satisfaction turned out to be the strongest predictor of loyalty, with an almost perfect explanatory power of its variance. Control variables, including age, gender, and income, were ineffective and thus signified that these findings apply to each and every group.Therefore, it concludes that satisfaction is the equity point that will enable well implemented omnichannel strategies to be transformed into loyal behaviours and that synchronization plays a leading role in shaping satisfaction. This indicates a better expectation of customers toward seamless and real time experiences. These findings provide valuable insight for organizations in refining their omnichannel approaches and offer a robust foundation for future research in the dynamics of customer experience and loyalty.

Artificial Intelligence (AI) is rapidly transforming industries across the globe, and the insurance sector in India is no exception. With its ability to streamline processes, enhance decision-making, and personalize customer interactions, AI presents a new frontier for innovation and efficiency. In India’s dynamic and highly competitive insurance market, the adoption of AI is gaining momentum. This paper delves into the potential of AI to disrupt traditional insurance practices, focusing on operational efficiency, customer experience, and innovation. By examining secondary data from academic and industry sources, it explores both opportunities and challenges associated with AI integration. The findings aim to inform future strategies for stakeholders navigating this evolving technological landscape. Purpose: This paper explores the potential disruptive impact of artificial intelligence (AI) on the insurance sector in India, focusing on its implications for operational efficiency (OE), the customer experience (CE), and the overall innovation within the insurance industry (I). This investigation seeks to identify potential opportunities and challenges associated with the increasing reliance on AI in this fast-evolving marketplace. Design/Methodology/Approach: This paper takes a qualitative approach that entails a conceptual analysis of secondary data obtained from academic journals, industry reports, and case studies. The overall aim is to analyse AI depending on operations while discussing its relevance to the context of India. Findings: AI's disruption is increasing underwriting, claims processing, fraud detection, and customer engagement in the Indian insurance sector, however, problems such as privacy and regulatory grey areas, alongside skills shortages must include for organizations to harness fully the power of AI and its possible functionalities. Research Limitations/Implications: This paper contains secondary data which may not reflect the most current development in this industry, future researchers would be able to undertake primary studies and longitudinal studies to better inform future thinking. Practical Implications: The study provides actionable insights into AI for insurers, policymakers, and technology developers around the suitability of the strategic development of AI and trading off for ethical and regulatory work on AI. Originality/Value: This paper offers a specific analysis of AI's contributions in India’s insurance sector, a relatively unexplored but significantly growing area, and adds to the literature on technology-driven transformation in emerging markets.

In the contemporary digital economy, artificial intelligence (AI) has emerged as a transformative force in reshaping customer experience (CX) strategies. This study investigates how Salesforce, a global leader in customer relationship management (CRM), integrates AI technologies to build intelligent CX architectures that drive customer engagement and operational efficiency. By analyzing Salesforce’s approach, the research aims to provide actionable insights for businesses seeking to leverage AI for competitive advantage in increasingly dynamic markets.The methodology combines qualitative and technical analyses, including three industry case studies demonstrating Salesforce AI implementations, a deep dive into the Einstein AI platform (encompassing predictive analytics, natural language processing, and machine learning models), and synthesis of market data from CRM trends and adoption metrics. These methods evaluate how AI tools are operationalized to address real-world CX challenges, such as personalization at scale and workflow automation.Key findings reveal that Salesforce’s AI-driven solutions significantly enhance CX through three core mechanisms: (1) hyper-targeted personalization, enabling dynamic content curation and product recommendations that boost customer satisfaction by up to 35%; (2) automation of service interactions via chatbots and intelligent routing, reducing response times by 40%; and (3) predictive analytics that anticipate customer needs, improving retention rates and lifetime value. These outcomes underscore AI’s role in transforming reactive CX strategies into proactive, data-driven ecosystems. The study proposes a strategic framework for businesses to adopt AI-powered CX architectures, emphasizing alignment between AI capabilities, organizational goals, and customer journey mapping. Practical implications include guidelines for integrating Salesforce’s AI tools with existing infrastructure, upskilling teams, and addressing data privacy concerns. By bridging technical innovation with business strategy, this research equips organizations to harness AI for scalable, personalized, and future-ready customer experiences.

The wide diffusion of artificial intelligence (AI) is one of the most disrupting technological revolutions in recent human history. Yet, still little is known on how and to what extent the diffusion of AI in business practices affects brand experiences in general and brand experience co-creation in particular. While the literature dealing with brand experience is becoming increasingly consumer-centric and keener to frame brand experience as a socially-constructed and context-sensitive phenomenon, research hardly addresses the current role that AI technologies play in the creation of new and different forms of brand experience. In this chapter, we explore this “terra incognita” at the theoretical level by constructing an updated framework of brand experience co-creation that combines recent theoretical refinements of the brand experience concept with the service dominant logic of markets and actor-network theory. The developed theoretical framework results in a novel ontology of brand-experience co-creation at the time of AI which inspires theoretical and practical implications and opens avenues for future research.