Cross- sell campaign targeting using machine learning

Cross- sell campaign targeting using machine learning

The business problem

Call center capacity is expensive. When approaching customers with a new add-on product, our client so far has been using a random selection model, but this has yielded very low (10-15%) efficacy. Can this be optimized better so as to reach the most susceptible customers?

Solution

A complex model based on recursive partitioning used data about customers and their behavioral patterns to predict which customers are most likely to respond positively to an approach. Additional locality-based and interaction patterns were extracted from customer data.

Results

92% model accuracy (as measured by ROC AUC) and a very significant 6x uplift in conversion rate

By | 2019-01-26T14:07:36+00:00 December 17th, 2018|case study, data science, featured|0 Comments

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