Developing product recommendation platform for customers.
The client wanted to implement an effective mechanism which could assess the nature of individual customers and recommend them the right services for effective cross-selling and up-selling.
Situation: Lack of accuracy while using the existing model.
The client’s existing model was not proving effective when it came to accuracy of predictions, at an individual product level. The client wanted to implement a much more robust mechanism.
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Big data analytics for assessing customer and service level data for actionable insights.
We did a customer segmentation based on various factors including demographics, purchase, spend etc., to develop effective cross-sell and up-sell recommendations. Our robust algorithm was capable of determining the correlation between different offerings based on customer behavior.
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Improvement in cross-selling and up-selling opportunities resulting in better profitability.
Our solution helped the client in implementing an improved product recommendation platform. This helped them in automating the process of product recommendation to the customers and improving the chances for cross-selling and up-selling.