Designing a Customer Relationship Management Model in the Chain Retail Industry Based on Business Intelligence: A Grounded Theory Approach - Ghorchi Beigi, Ishaq; Rostami, Mohammad Reza; Shojaei Baghini, Golnar (Digital Transformation and Administration Innovation, 2025)
Business intelligence is recognized as a powerful and essential tool across various industries, with the retail industry being particularly well-suited for its application due to the influx of vast volumes of data. In this context, business intelligence in the retail sector is capable of transforming complex and diverse data into understandable and actionable information in a precise and intelligent manner. Therefore, the primary aim of the present study is to design a customer relationship management (CRM) model in the chain retail industry based on business intelligence, using a grounded theory approach. This research, based on the type of data, is qualitative in nature and is categorized as fundamental and exploratory research due to its goal of designing a CRM model in the chain retail industry grounded in business intelligence. Participants in this study included managers and experts involved in the field of customer relationship management in retail stores. The data collection tool was a semi-structured interview, and the method of data collection was field-based. The study employed theoretical sampling, and the sample size reached 22 participants based on theoretical saturation. The qualitative data were analyzed using the grounded theory methodology. According to the results obtained from coding, the following were identified as causal conditions: a culture of business intelligence acceptance, strategic planning based on business intelligence application, understanding the business ecosystem, comprehension of digital transformation, and infrastructural platforms. The central phenomena included customer identification, customer acquisition, recognition of customer needs, reorganization of business processes, customer engagement, and customer dependency. The strategies consisted of inventory management and control, application of business intelligence tools, customer knowledge management, value network management, and analytical, collaborative, and operational CRM based on business intelligence. The intervening conditions were identified as the development of technical infrastructure, qualitative enhancement of software and hardware in database architecture, development of modern technical infrastructures, and localization of information systems. Contextual conditions included cultural factors, social factors, and senior management support. Finally, the identified outcomes of the model were financial performance, improved customer experience, process agility, and the creation of organizational value. Based on the results of the model design, it is recommended that to strengthen business intelligence-based customer relationship management, special attention should be given to the causal factors of the model.