Social media analytical CRM: a case study in a bank

Article type: Research Article

Authors: Duman, Ekrem^{; *}

Affiliations: Department of Industrial Engineering, Ozyegin University, Istanbul, Turkey

Correspondence: [*] Corresponding author. Ekrem Duman, Department of Industrial Engineering, Ozyegin University, Istanbul, Turkey. E-mail: ekrem.duman@ozyegin.edu.tr.; E-mail: dumane@gmail.com.

Abstract: The use of the social media (SM) has become more and more widespread during the last two decades, the companies started looking for insights for how they can improve their businesses using the information accumulating therein. In this regard, it is possible to distinguish between two lines of research: those based on anonymous data and those based on customer specific data. Although obtaining customer specific SM data is a challenging task, analysis of such individual data can result in very useful insights. In this study we take up this path for the customers of a bank, analyze their tweets and develop three kinds of analytical models: clustering, sentiment analysis and product propensity. For the latter one, we also develop a version where, besides the text information, the structural information available in the bank databases are also used in the models. The result of the study is a considerably more efficient set of analytical CRM models.

Keywords: Social media, banking, CRM, NLP, sentiment analysis

DOI: 10.3233/JIFS-221619

Journal: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 2, pp. 2631-2642, 2023