  Promotions have been trending in the e-commerce marketplace to build up
customer relationships and guide customers towards the desired actions. Since
incentives are effective to engage customers and customers have different
preferences for different types of incentives, the demand for personalized
promotion decision making is increasing over time.
  However, research on promotion decision making has focused specifically on
purchase conversion during the promotion period (the direct effect), while
generally disregarding the enduring effect in the post promotion period. To
achieve a better lift return on investment (lift ROI) on the enduring effect of
the promotion and improve customer retention and loyalty, we propose a
framework of multiple treatment promotion decision making by modeling each
customer's direct and enduring response. First, we propose a customer direct
and enduring effect (CDEE) model which predicts the customer direct and
enduring response. With the help of the predictions of the CDEE, we personalize
incentive allocation to optimize the enduring effect while keeping the cost
under the budget. To estimate the effect of decision making, we apply an
unbiased evaluation approach of business metrics with randomized control trial
(RCT) data. We compare our method with benchmarks using two promotions in
Mercari and achieve significantly better results.
