ЕВОЛЮЦІЯ ТА ПЕРСПЕКТИВНІ ВЕКТОРИ РОЗВИТКУ МАРКЕТИНГОВИХ ІННОВАЦІЙ У РИТЕЙЛІ

The competition in the fast fashion industry is getting more complex as online-only retailing has emerged in the industry. The fast fashion online-only companies rely on e-commerce platforms to merchandize products and provide services to customers. Online-only companies use artificial intelligence (AI) and machine learning (ML) through recommendation systems and chatbots to improve business functions and enhance online customer shopping experience. Fast fashion multichannel companies (online and physical stores) have a concern about their physical stores’ performance, and the role that physical stores can play to enhance customer experience. Multichannel companies are continuously looking for new ways to optimize services and enhance customer experience in both channels. Physical stores can play a crucial role in enhancing customer experience. By collecting data on in-store customers, their interests and interactions with products, multichannel companies can analyze such data using AI and ML to optimize production, marketing, and customers experience. This paper highlights the application of AI in ecommerce by fast fashion companies. Also, this paper discusses the effect of fast fashion online-only companies on fast fashion multichannel companies’ physical stores, aiming to understand the current impact of online-only business on physical stores performance. This paper, further, discusses the future role of fashion physical stores in the industry.KeywordsOnline-only companiesMultichannel companiesArtificial intelligenceMachine learningE-CommerceFast fashionCustomer experience

The U.S. retail sector, a $7 trillion economic engine, is undergoing rapid transformation fueled by digital commerce, shifting consumer expectations, and intensified competition. At the heart of this shift lies the imperative to modernize customer service infrastructure. This paper explores how Salesforce Service Cloud—a leading Customer Relationship Management (CRM) platform—can be strategically deployed to optimize service delivery, reduce churn, and support omnichannel responsiveness across the retail value chain. We begin by contextualizing the urgency of service innovation, drawing on recent data showing that U.S. companies lose over $75 billion annually due to poor customer experiences. We then examine Salesforce Service Cloud’s capabilities, including AI-driven case management, real-time analytics, automation, and integration with e-commerce platforms. Through use-case illustrations and performance metrics, we demonstrate how these features enable faster resolution times, improved customer satisfaction, and more efficient use of the retail workforce. Importantly, we highlight the platform’s role in enhancing employment efficiency for over 2.7 million Americans working in customer-facing roles, enabling frontline staff to shift from routine inquiries to high-value engagement. Finally, we position CRM modernization within the broader context of U.S. economic priorities, referencing Executive Order 14058 and other federal mandates that call for customer experience transformation. Our findings support the conclusion that Service Cloud is more than a software solution—it is critical infrastructure for ensuring that the U.S. retail sector remains competitive, resilient, and aligned with the digital economy of the future. Keywords: Customer Experience, Salesforce, Retail Sector, Digital Commerce.

The Future of Omni-Channel Retail: Predictions in the Age of Amazon

Although research on respectively online and offline customer experiences (CXs) is long-established, scholarly attention in the context of phygital CXs is still in its infancy. The purpose of this empirical paper is to propose a first investigation regarding phygital CXs. The present study contributes to CX literature by investigating the typologies of CX in phygital contexts depending on the intensity of consumers’ responses and reactions to stimuli, i.e., ordinary to extraordinary experiences. From a managerial perspective, this research helps business managers and owners go beyond the CX's subjectivity and contextuality, focusing on their controlled stimuli and touchpoints to trigger the intended CX. Keywords: Phygital customer experience; ordinary experience; extraordinary experience; physical store; Try & Buy; single-case study

Background. The retail sector in Ukraine is in crisis due to COVID-19. New risks and challenges have emerged that have put at risk the functioning of the trading industry. Therefore, there is a need to find ways to adapt and transform business models in retail to new, crisis conditions. Analysis of recent researches and publications. Peculiarities of trade business functio­ning in conditions of uncertainty, risks, and crises are actively studied by many scientists and practitioners. However, the issue of changing retail business models in the face of instability, which would allow companies to adapt to today’s challenges, remains insufficiently studied. The aim of the article is to study the process of transformation and adaptation of business models in retail to new economic realities, challenges, and threats associated with the situation around COVID-19. Materials and methods. The information base of this study was scientific work on the adaptation of business to modern conditions of instability and rapid change. The research methodology is based on a system of general scientific and special methods, in particular: analy­sis and synthesis; systematic and integrated approach. Results. The peculiarities of the instability of the modern world according to the VUCA concept, in particular its manifestations related to the COVID-19 pandemic, have been studied. The main threats to business development in the field of retail trade in the current crisis situation have been identified. Changes in business models in retail are proposed, which will help in adapting to difficult economic conditions and maintaining the competitiveness of retail enterprises in the consumer goods market. Conclusion. The necessity of transformational changes of business models in retail in order to adapt them to crisis conditions and ensure the survival of retail enterprises in today’s unstable world is proved.

This paper analyzes the cases where the hotels have increased their services and enhanced their work process through IT solutions to cope with computerization globalization. Also the cases have been studies where national hotels use the CRM solution internally to respond effectively to customers requests, increase customer analysis, and build marketing strategies. In particular, this study discusses the introduction of the CRM solutions and CRM sales business and marketing services using a process for utilizing the presumed, CRM by introducing effective DEA(Data Envelopment Analysis). First, the comparison has done regarding the relative efficiency of L Company with the CCR model, then compared L Company's restaurants and facilities' effectiveness through BCC model. L Company reached a conclusion that it is important to precisely create and manage sales data which are the preliminary data for CRM, and for that reason it made it possible to save sales data generated by POS system on each sales performance database. In order to do that, it newly established Oracle POS system and LORIS POS system concerned with restaurants for food and beverage as well as rooms, and made it possible to stably generate and manage sales data and manage. Moreover, it set up a composite database to control comprehensively the results of work processes during a specific period by collecting customer registration information and made it possible to systematically control the information on sales performances. By establishing a system which unifies database and managing it comprehensively, impeccability of data has been greatly enhanced and a problem which generated asymmetric data could be thoroughly solved. Using data accumulated on the comprehensive database, sales data can be analyzed, categorized, classified through data mining engine imbedded in Polaris CRM and the results can be organized on data mart to provide them in the form of CRM application data. By transforming original sales data into forms which are easy to handle and saving them on data mart separately, it enabled acquiring well-organized data with ease when engaging in various marketing operations, holding a morning meeting and working on decision-making. By using summarized data at data mart, it was possible to process marketing operations such as telemarketing, direct mailing, internet marketing service and service product developments for perceived customers; moreover, information on customer perceptions which is one of CRM's end-products could feed back into the comprehensive database. This research was undertaken to find out how effectively CRM has been employed by comparing and analyzing the management performance of each enterprise site and store after introducing CRM to Hotel enterprises using DEA technique. According to the research results, efficiency evaluation for each site was calculated through input and output factors to find out comparative CRM system usage efficiency of L's Company four sites; moreover, with regard to stores, the sizes of workforce and budget application show a huge difference and so does the each store efficiency. Furthermore, by using the DEA technique, it could assess which sites have comparatively high efficiency and which don't by comparing and evaluating hotel enterprises IT project outcomes such as CRM introduction using the CCR model for each site of the related enterprises. By using the BCC model, it could comparatively evaluate the outcome of CRM usage at each store of A site, which is representative of L Company, and as a result, it could figure out which stores maintain high efficiency in using CRM and which don't. It analyzed the cases of CRM introduction at L Company, which is a hotel enterprise, and precisely evaluated them through DEA. L Company analyzed the customer analysis system by introducing CRM and achieved to provide customers identified through client analysis data with one to one tailored services. Moreover, it could come up with a plan to differentiate the service for customers who revisit by assessing customer discernment rate. As tasks to be solved in the future, it is required to do research on the process analysis which can lead to a specific outcome such as increased sales volumes by carrying on test marketing, target marketing using CRM. Furthermore, it is also necessary to do research on efficiency evaluation in accordance with linkages between other IT solutions such as ERP and CRM system.

Food Access Matters: Quantifying the Price Differential Across Four Major Food Retailers and a Mobile Market Aiming to Improve Affordable Nutritious Food Access.

Leader Roles for Innovation: Strategic Thinking and Planning

This research primarily explores the role of service innovation and customer experience in ethnic restaurants, and the relationship with customers' behavioural intention. Data were collected by means of a questionnaire distributed to 10 types of ethnic restaurants. In total, 322 samples were obtained. Statistical techniques employed include descriptive statistics, exploratory factor analysis, correlation analysis and hierarchical regression. The results suggest that service innovation has significant effects on behavioural intention and customer experience, and the mediating effect of customer experience on service innovation and customers' behavioural intention was supported. Finally, theoretical and practical implications, direction of future research and research limitations are proposed.

The article examines the features of integrating artificial intelligence algorithms (Explainable AI, XAI) into CRM systems aimed at enhancing customer experience (Customer Experience, CX). Based on an analysis of recent publications, the study explores the principles of personalization as well as approaches to the explainability of machine learning algorithms, including chatbots and recommendation systems. It demonstrates that transparency and interpretability of model outputs positively influence customer trust and loyalty while simultaneously improving the efficiency of internal business processes. The article analyzes the implementation experience of XAI in the banking sector, insurance call centers, and online retail, which has led to improvements in retention, conversion, and satisfaction metrics. The information presented in the article is intended for researchers and professionals in the field of artificial intelligence focused on developing interpretable machine learning algorithms, as well as for analysts seeking to optimize CRM systems to enhance customer experience management. In addition, the material is useful for professionals in corporate governance and marketing who aim to integrate advanced Explainable AI methods into personalization strategies and decision-making processes, ensuring the transparency and adaptability of services under dynamic market conditions.

The article substantiates the role of artificial intelligence (AI) technologies as a key tool for modern personalization of customer experience within CRM systems. The growing volume of data processed by businesses and increasing consumer expectations for individualized interaction necessitate intelligent approaches to customer relationship management. The study systematizes three main areas of AI-driven personalization: customer experience adaptation, analytics and prediction of future customer behavior, and automated support tailored to the user’s context and emotional state. The functional capabilities of such tools as generative content, recommendation systems, predictive analytics, intelligent chatbots, and emotionally responsive AI are described in detail, revealing new opportunities for enhancing customer loyalty, satisfaction, and retention. Special attention is paid to the core personalization functions implemented in modern AI-powered CRM systems. At the same time, the article addresses a range of ethical challenges, including the opacity of algorithmic decisions, potential model bias, risks of data privacy violations, and the diminishing role of human decision-making. It is demonstrated that the use of a four-stage integration model enables risk structuring and ensures efficiency at each stage. The model emphasizes the importance of cultivating a customer-oriented culture, involving interdisciplinary teams, defining key performance indicators, and testing solutions in pilot environments. This model demonstrates the importance of considering the implementation of AI personalization not only as a technical process, but as an element of strategic change management. Thus, AI-based personalization is viewed not only as a technological challenge but also as a crucial element of strategic change management, whose successful implementation requires adherence to the principles of responsible artificial intelligence. The results obtained can be used for further research in the areas of personalization in conditions of limited data, ethical assessment of AI solutions, and personalization in a B2B context.

PurposeThis research analyzes how the dimensions of the customer experience derived from using a digital kiosk during the store visit influence shopping value, self-mental imagery and the behavioral intentions of buying and word of mouth. Mediation effects of utilitarian, hedonic and social shopping values are examined, as well as the mediating effect of self-mental imagery.Design/methodology/approachTwo empirical studies were conducted to test the research hypotheses. A first analysis was carried out using a sample of 115 customers from several retail sectors. For the second study, 200 customers of one of the largest international sporting goods retailers were interviewed immediately after their store visit.FindingsThe results confirm significant influences of each dimension of the digital kiosk customer experience (sensorial, pragmatic, cognitive, social) on shopping value and self-mental imagery. They highlight strongest effects as well as the quasi-generalized mediating role of these values, and this self-mental imagery in the relations between the components of the experience and the behavioral intentions.Research limitations/implicationsThe studies were carried out in only one country (France). It would be also useful to consider variations in shopping motives and in involvement between retail sectors. Highlighted relationships should be deepened by experiments intended to identify the psychological mechanisms and emotions capable of mediating influences of customer experience on shopping value.Practical implicationsThe results encourage both advice on the design of digital kiosks and the specifications of their content and several recommendations about the widespread introduction of kiosks or similar new technologies.Originality/valueThis research highlights influences of each of components of customer experience when using an interactive kiosk on shopping values and self-mental imagery, and central roles of these in understanding influences of the customer experience on behavioral responses.

Social media advertising has become an essential digital marketing strategy for influencing customer decision-making and enhancing organizational value in a rapidly evolving digital economy. The relationship between social media advertising, customer experience, and organizational performance has attracted increasing attention from academics and practitioners, especially in relation to emotional and psychological influences on consumer behavior. This study investigates the effect of social media advertising on customer experience and organizational performance, incorporating the mediating role of social anxiety. A mixed-method research design was adopted, combining structured questionnaires and semi-structured interviews. Data were collected from 180 social media users and 10 marketing professionals from retail, telecommunications, and e-commerce sectors, of which 162 responses were valid for quantitative analysis using SPSS. Findings revealed that social media advertising significantly enhances customer experience and has a positive effect on overall organizational performance. Correlation and regression analyses confirmed statistically significant relationships between advertising effectiveness and customer experience (r=0.711, p <0.01), and between customer experience and organizational performance (r=0.694, p<0.01). Social anxiety partially mediated the relationship between advertising and customer experience, suggesting that emotional sensitivity impacts how consumers interpret promotional messages. The study offers theoretical and practical implications for emotionally responsible advertising and sustainable digital brand strategies.

This academic paper aims to explore the role of technological innovation in merchandising and its impact on consumer behaviour and retail performance. The study uses a systematic review and meta-analysis approach to collect and analyse existing research articles, industry reports and case studies related to technological innovation in merchandising. A comprehensive search strategy is used to identify relevant literature sources and rigorous inclusion and exclusion criteria are applied to select high quality studies for analysis. The results of the systematic review and meta-analysis demonstrate the significant impact of technological innovation on various aspects of merchandising. These include improvements in inventory management, supply chain logistics, product presentation and customer engagement. In addition, the integration of technology into merchandising strategies was found to enhance the customer experience, increase sales conversion and improve overall retail performance. The findings of this study have practical implications for retailers and marketers seeking to leverage technological innovation in their merchandising strategies. It highlights the importance of embracing emerging technologies such as augmented reality, virtual reality, mobile applications and smart devices to create immersive and interactive shopping experiences. Retailers can use these technologies to improve product discovery, provide personalised recommendations and streamline the buying process. In addition, the study highlights the need for continuous adaptation and investment in technology to remain competitive in the evolving retail landscape. This research contributes to the existing body of knowledge by systematically synthesising the available evidence on the role of technological innovation in merchandising. It provides valuable insights into the potential benefits and challenges associated with the adoption of new technologies in the retail sector. This study serves as a valuable resource for academics, practitioners and policy makers interested in understanding and harnessing the power of technological innovation in merchandising.

Omnichannel commerce offers a smooth buying experience from the very first to the very last customer touchpoint. Omnichannel retailing is a practice of conducting business across a variety of channels, such as social media, marketplaces, physical stores, and more. This study aims to investigate the implication of integrating multiple channel platforms in the modern retail landscape to enhance the overall customer experience. The study identifies key factors influencing customers' agreement with Omni-channel strategies and reveals the mediating effect of these strategies on customer experience.The methodology used to develop the proposed model is the Partial Least Square Equation Modelling Technique. A quantitative research process was adopted, and the data was collected through a questionnaire from 506 respondents. Methodology – The research collects data through an online and offline mode. At the beginning of the questionnaire, a screening question was set up to ask whether the respondent is an Omni-channel shopper i.e., using more than one mode in their purchase process. We received a total of 525 responses from Omni-channel shoppers out of which a total of 506 responses were considered for analysis after deleting duplicate items. A systematic sampling technique was used for selecting the sample and the selection of the respondents was done both offline and online based on the type of sales channel used during the shopping journey. The partial least square–structural equation modelling (PLS-SEM) software were employed to analyze and test proposed hypotheses. Findings - The findings reveal the importance of perceived value, social influence, and perceived uncertainty/risk as primary factors of customers' willingness to adopt Omni-channel strategies. The findings also demonstrate a strong mediating effect of Omni-channel strategies on usage intention, suggesting they stimulate customers to engage across different channels. However, it is important to note that while these strategies significantly contribute to encouraging usage intention, their mediation effect on customer experience is only partial, indicating a moderate impact on enhancing overall customer satisfaction. Originality- The insights gained from this research offer valuable guidance for retail managers aiming to develop and implement effective Omni-channel strategies.