Enhancing Customer Engagement: How Coforge Empowered a Leading UK Bank with Data-Driven Customer Segmentation & Personalized Offers .

Challenges.

• Enhancing customer intimacy and driving business growth through tailored product offerings. 

• Segmenting B2B clients based on data, income, and overall Lifetime Value (LTV). 

• Guiding the marketing team in identifying the most appropriate products for each customer segment. 

Solution.

Coforge implemented a data-driven approach to segment the bank’s commercial and corporate customers and determine the next best offer: 

• Utilized K-Means clustering algorithm to segment customers based on financial and demographic features. 

• Merged internal data with external datasets from agencies regarding registrations and credit portfolios. 

• Divided features into buckets and created cohorts based on clustering output patterns. 

• Mapped existing products to each cohort and used collaborative filters to identify common products among customers. 

• Developed a multi-class recommender algorithm to generate scalable next best offer models. 

• Conducted AB tests to evaluate the performance of the machine learning models and analysed feedback to measure KPI changes. 

The Impact.