A Prominent UK Bank Increased Product Cross-Sell by 75% Using AI-Powered Segmentation and Recommendation Engine
Overview
A leading UK-based bank with a diverse portfolio of financial services catering to commercial and corporate clients. The bank aimed to strengthen customer intimacy and drive growth through tailored product offerings and data-driven engagement.
The client lacked a scalable framework to segment B2B customers and deliver personalized offers based on data, income, and Lifetime Value (LTV). This led to:
Inconsistent customer segmentation and limited visibility into customer potential.
Inefficient targeting and missed cross-sell opportunities.
Low engagement due to generic, non-personalized product recommendations.
Solution
Coforge implemented an AI-powered segmentation and next-best-offer engine to enhance personalization and improve product cross-sell performance:
Applied K-Means clustering to segment customers using demographic and financial indicators.
Enriched internal data with external agency datasets (registrations, credit portfolios) for deeper insights.
Created cohorts and feature buckets based on clustering patterns to refine customer groupings.
Used collaborative filtering to identify shared product interests and detect purchase trends.
Developed a multi-class recommender algorithm to automate personalized product suggestions.
Executed A/B testing to validate model performance and measure KPI impact.
The Impact
75% increase in product cross-sell to existing customers.
15% uplift in customers transitioning to higher-value segments.
Improved marketing ROI through targeted offers and faster campaign execution.
