1. Improving incentive policies to salespeople cross-sells: a cost-sensitive uplift modeling approach.
- Author
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Vairetti, Carla, Vargas, Raimundo, Sánchez, Catalina, García, Andrés, Armelini, Guillermo, and Maldonado, Sebastián
- Subjects
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BUSINESS analytics , *INCENTIVE (Psychology) , *CROSS selling , *DATA analytics , *COMMERCIAL agents - Abstract
In this study, we present a novel cost-sensitive approach for uplift modeling in the context of cross-selling and workforce analytics. We leverage referrals from sales agents across business units to estimate the individual treatment effects of incentives on the cross-selling outcomes within a company. Uplift modeling is employed to predict relationships between salespeople that should be encouraged based on the probability of successful cross-selling - defined when a customer accepts the product suggested by sales agents. We conducted experiments on data from a Chilean financial group, evaluating both statistical and profit metrics. Exploring various machine learning classifiers for predictive purposes, we observed a significant improvement over the current approach, which exhibits an uplift below 0.01. Finally, we show that selecting the best classifier with profit metrics results in a 31.6% improvement in terms of average customer profit. This emphasizes the importance of defining an adequate compensation scheme and integrating it into the modeling process. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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