From Churn to Loyalty

Improve customer retention by identifying interventions that reduce churn and increase loyalty — using analytics to surface patterns, predict who is likely to leave, and act while there is still time.

The firm faced rising customer dormancy, with 45% of individual investors inactive. The BI team was asked to predict churn likelihood, the revenue at risk, and exactly which investors to target for retention.

• Compiled data across core-system tables using a data warehouse (Oracle/SQL Server) with Tableau for analysis, on a daily refresh.
• Profiled churned investors across investment size, first product, product breadth and value-added service usage.
• Modelled likelihood of discontinuation and expected revenue impact per investor segment.

• Most churned customers had lifetime investments between Rs. 5,000 and Rs. 500,000.
• They typically bought a single fund (Asset Allocation, Income or Money Market) and never explored others.
• Most never activated value-added services (digital, debit card, e-transactions).
• They stayed active for less than a year before redeeming.

• Personalised service to deepen investor experience and brand connection.
• Proactive support to resolve issues early, plus a formal feedback loop.
• Trusted-advisor positioning, referral and awareness programmes, and social channels for informal engagement.