Identification of Key Components of Smart Customer Relationship Management in Small and Medium-Sized Enterprises Using Artificial Intelligence: A Thematic Analysis Approach

Abstract

The present study aims to identify the dimensions and key components of customer relationship management (CRM) in small and medium-sized enterprises (SMEs), with a particular emphasis on the utilization of advanced technologies such as artificial intelligence (AI) and machine learning (ML). This research is qualitative and exploratory in nature and was conducted within the framework of grounded theory using a thematic analysis approach. The statistical population consisted of academic experts in the fields of management and marketing, as well as senior managers and experts from SMEs in Mazandaran Province. Purposive and snowball sampling techniques were employed until theoretical saturation was achieved, resulting in a total of 12 in-depth semi-structured interviews. The collected data were analyzed using MAXQDA software and based on the six-phase thematic analysis method by Braun and Clarke (2006). To enhance the validity and reliability of the data, triangulation was employed (interviews, documents, and expert review), and the coding process was repeated by a second researcher. The findings identified seven key indicators of smart technology-based CRM: “customer-centric strategy,” “customer interaction management,” “technological infrastructure for CRM,” “human resource management in CRM,” “strategic CRM planning,” “CRM monitoring and evaluation,” and “machine learning and artificial intelligence in CRM.” These dimensions were designed and analyzed in the form of an initial conceptual model to improve efficiency and customer satisfaction in SMEs. The results of this study can serve as a robust foundation for developing localized and practical operational models for AI-based customer relationship management in small and medium-sized enterprises.