Scientific mapping for customer lifetime value research in organizations using cluster analysis method

The aim of this research is to analyze and map international scientific publications related to Customer Lifetime Value (CLTV). This study adopts an interpretive paradigm and employs a descriptive approach using a systematic review method. By utilizing specific search terms in the Web of Science database, covering the period from 1985 to 2024, and after thorough screening and qualitative assessment of the studies, the final analysis was conducted on 639 articles. An in-depth examination of the selected articles revealed a notable increase in international research in this field, particularly during the last twenty years. However, there have been periods of decreased research activity in years such as 2008, 2017, and 2023. The primary focus of this research has been on customer lifetime value and customer segmentation, with a significant association to the keyword "data mining," highlighting the importance of this technique in the discipline. Moreover, it was found that countries like Iran, Canada, and Turkey have lower average citation rates, whereas the United States, France, and Germany exhibit higher average citation rates. This suggests different patterns of co-authorship among these countries. By examining the most and least productive countries and researchers through scientometrics, new research opportunities in the field of customer lifetime value can be identified, providing insights for Iranian researchers to enhance the visibility of their findings on an international scale.