Cross-Selling Active Schemes to Direct Plan Passive Customers
For a Assest Management Company
CLIENT & PROBLEM STATEMENT
- The client, an asset management company, aimed to increase engagement by cross-selling active schemes to Direct Plan passive customers.
- The goal was to identify potential buyers for various schemes and target dormant customers, providing them with tailored suggestions for Flexi Cap, Mid Cap, Small Cap, Top 100, and Large & Mid Cap funds.
APPROACH
- Product-wise machine learning models were developed, with XGBoost emerging as the most effective classifier for predicting buying propensity.
- We evaluated the model using key accuracy measures such as Gini coefficient, sensitivity, and specificity to ensure high performance.
SOLUTION & OUTPUT
- The modeling exercise successfully identified a list of customers for targeted cross-selling of Flexi Cap, Mid Cap, Small Cap, Top 100, and Large & Mid Cap funds.
- The approach led to a conversion rate between 4.00% and 6.50 %, boosting sales of active schemes and enhancing customer engagement with the asset management company’s offerings.
Cross-Selling Active Schemes to Direct Plan Passive Customers
For a Assest Management Company
CLIENT & PROBLEM STATEMENT
- The client, an asset management company, aimed to increase engagement by cross-selling active schemes to Direct Plan passive customers.
- The goal was to identify potential buyers for various schemes and target dormant customers, providing them with tailored suggestions for Flexi Cap, Mid Cap, Small Cap, Top 100, and Large & Mid Cap funds.
APPROACH
- Product-wise machine learning models were developed, with XGBoost emerging as the most effective classifier for predicting buying propensity.
- We evaluated the model using key accuracy measures such as Gini coefficient, sensitivity, and specificity to ensure high performance.
SOLUTION & OUTPUT
- The modeling exercise successfully identified a list of customers for targeted cross-selling of Flexi Cap, Mid Cap, Small Cap, Top 100, and Large & Mid Cap funds.
Cross-Selling Active Schemes to Direct Plan Passive Customers
For a Assest Management Company
CLIENT & PROBLEM STATEMENT
- The client, an asset management company, aimed to increase engagement by cross-selling active schemes to Direct Plan passive customers.
- The goal was to identify potential buyers for various schemes and target dormant customers, providing them with tailored suggestions for Flexi Cap, Mid Cap, Small Cap, Top 100, and Large & Mid Cap funds.
APPROACH
- Product-wise machine learning models were developed, with XGBoost emerging as the most effective classifier for predicting buying propensity.
- We evaluated the model using key accuracy measures such as Gini coefficient, sensitivity, and specificity to ensure high performance.
SOLUTION & OUTPUT
- The modeling exercise successfully identified a list of customers for targeted cross-selling of Flexi Cap, Mid Cap, Small Cap, Top 100, and Large & Mid Cap funds.
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Case Study 1 : Customer Analytics
For a large bank
01
Client
The client is a large private sector bank in India with more than 2 million savings and current account holders. Along with their own products , client also sells third party products like Life Insurance, Health Insurance, Mutual Funds etc.
02
Problem
The client wanted to identify the potential customers from their existing customer base, to whom they can sell targeted third party products. The client also wanted to know when and how to target these prospects.
03
Solution
04
Outcome
G-Square’s solution helped client to focus on right customers which is giving them significant lift in the third party products than the traditional approach.