Customer Experience Management; Trends and Areas in Research

Customer experience management has been regarded as a hot topic for managers and marketing researchers recently. The growing interest in the customer experience area is a result of the increasing complexity of channels, interactions, choices, and customers’ journeys. Thus, companies attempt to meet these challenges by increasing their comprehensive efforts. Organizations typically depict and manage the customers’ experience through customer journeys (including a large number of contact points representing direct and indirect customer interactions with the organization). Given the importance of this area of ​​research, particularly in marketing studies, it is essential to identify the sub-areas and research process. This study aims to review previous studies in customer experience management, identify primary articles, and identify sub-areas and the research process.

This empirical research uses documentary approach for data collection, and data analysis is conducted based on the bibliometric method. Bibliometric analysis refers to a quantitative research method investigating the research literature from the science development perspective. The required data were collected from 124 articles published in the Scopus database, provided that Bibliographic coupling analysis and co-occurrence analysis of keywords were performed. Hence, primary and sub-domain articles were identified. Then, the research process in this field was determined by creating a cover map and the average life of words.

Based on the findings of this study, research on customer experience management can be divided into the following nine clusters: cluster 1: branding, brand loyalty, brands and B2B customer experience indicating research efforts dedicated to the relationship between brand concept and customer experience management; cluster 2: customer relationship management (CRM), customer engagement, interactional marketing, social CRM, and social media; cluster 3, including a large number of studies related to customer satisfaction and loyalty: service quality, satisfaction, trust, and loyalty; cluster 4: customer experience and service design, feelings and cultural differences, and service ecosystem ; cluster 5, including a significant amount of research related to customer experience management in the field of retail; cluster 6: customer experience management, customer journey, marketing strategy, Omni-channel, services, and contact points; cluster 7, including research on the integration of customer experience management and information technology: artificial intelligence and macro data; cluster 8: retail branding, self-service, and social environment; and cluster 9, including studies on e-commerce and the core of customer experience management: macro data, customer journey, service quality, social customer relationship management, and online sales.

This study uses a cover map to address different topics such as the application of macro data in customer experience management, customer journey and contact points, online sales, service quality, customer engagement, B2B customer experience, and social customer relationship management. It also addresses various topics such as service marketing, online customer experience, macro data, customer journey, artificial intelligence, customers’ perceived value, online sales, service quality, social customer relationship management, cultural differences, and Omni-channels by analyzing the average life of words. Therefore, the results obtained from both methods emphasize topics like customer journey, the implementation of macro-data in customer experience management, online sales, service quality, and social customer relationship management.