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Promotions have been trending in the e-commerce marketplace to build upcustomer relationships and guide customers towards the desired actions. Sinceincentives are effective to engage customers and customers have differentpreferences for different types of incentives, the demand for personalizedpromotion decision making is increasing over time.  However, research on promotion decision making has focused specifically onpurchase conversion during the promotion period (the direct effect), whilegenerally disregarding the enduring effect in the post promotion period. Toachieve a better lift return on investment (lift ROI) on the enduring effect ofthe promotion and improve customer retention and loyalty, we propose aframework of multiple treatment promotion decision making by modeling eachcustomer's direct and enduring response. First, we propose a customer directand enduring effect (CDEE) model which predicts the customer direct andenduring response. With the help of the predictions of the CDEE, we personalizeincentive allocation to optimize the enduring effect while keeping the costunder the budget. To estimate the effect of decision making, we apply anunbiased evaluation approach of business metrics with randomized control trial(RCT) data. We compare our method with benchmarks using two promotions inMercari and achieve significantly better results.

Personalized Promotion Decision Making Based on Direct and Enduring Effect Predictions