This client wanted to increase both revenue per customer and customer loyalty, while also reducing dependency on their on-the-ground sales force. Their current cross-sell strategies were more hit or miss, rather than targeted on the right products and the customers who were most like to purchase.
Fractal build a cross-sell propensity model that enabled this client to answer these three key questions while executing cross-sell campaigns:
Our cross-sell propensity model analyzed our client’s e-channel customer profile data and transaction data. Customers with cross-sell histories were separated, and the time period after the first product purchase and the purchase sequence was identified. Using this data, Fractal developed a model that enabled the client to answer the three questions stated above.
Fractal build 15 cross-sell models for five insurance categories: four-wheel drive vehicles, two-wheel drive vehicles, Health, Travel and Home. Customers with the highest purchase propensity were targeted first during subsequent cross-sell campaigns, resulting in higher cross-sell rates.
Using Fractal’s propensity modeling answered three key customer questions for cross-selling to result in higher cross-sell success.
We identified the key factors that played a role in determining the purchasing inclination of our client’s customers, including: policy type, existing products, premium band, payment mode, city, age, and tenure with this client.
Our solution enabled our client to develop more focused cross-sell campaigns and reduce dependency on their on-the-ground sales force for profitability.
Our cross-sell propensity model allowed the client to develop a selective approach in targeting their cross-sell campaigns compared with their less successful go-all-out approach.