Modeling Cross-Selling Strategies in Retail Banking Using CRM Data

Authors

  • Chikaome Chimara Imediegwu  Access Bank PLC, Nigeria
  • Okeoghene Elebe  Access Bank PLC, Nigeria

Keywords:

Cross-Selling, CRM Analytics, Retail Banking, Customer Segmentation, Predictive Modeling, Customer Lifetime Value.

Abstract

This review paper explores the evolving landscape of cross-selling strategies in retail banking through the lens of customer relationship management (CRM) data analytics. In an increasingly competitive and digitally-driven financial sector, banks leverage CRM systems to generate actionable insights that enable targeted and personalized product recommendations. The paper synthesizes existing literature on CRM-based segmentation, behavioral modeling, predictive analytics, and machine learning frameworks that support cross-selling initiatives. It also examines the integration of customer lifetime value (CLV), channel preferences, and real-time behavioral triggers into campaign design. Challenges such as data silos, privacy concerns, and model interpretability are also discussed. Finally, the review identifies key gaps in current research and offers a forward-looking agenda for advancing CRM-enabled cross-selling through adaptive, ethically aligned, and AI-augmented strategies. The study contributes a structured understanding of the technological, organizational, and analytical dimensions of CRM-driven cross-selling models in retail banking.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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2022-10-30

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Volume 8, Issue 5, September-October-2022

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Chikaome Chimara Imediegwu, Okeoghene Elebe, " Modeling Cross-Selling Strategies in Retail Banking Using CRM Data" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 5, pp.498-519, September-October-2022.