Accepted Papers

Internal Promotion Optimization

Rupesh Gupta, Guangde Chen and Shipeng Yu

Most large Internet companies run internal promotions to cross-promote their different products and/or to educate members on how to obtain additional value from the products that they already use. This in turn drives engagement and/or revenue for the company. However, since these internal promotions can distract a member away from the product or page where these are shown, there is a non-zero cannibalization loss incurred for showing these internal promotions. This loss has to be carefully weighed against the gain from showing internal promotions. This can be a complex problem if different internal promotions optimize for different objectives. In that case, it is difficult to compare not just the gain from a conversion through an internal promotion against the loss incurred for showing that internal promotion, but also the gains from conversions through different internal promotions. Hence, we need a principled approach for deciding which internal promotion (if any) to serve to a member in each opportunity to serve an internal promotion. This approach should optimize not just for the net gain to the company, but also for the member’s experience. In this paper, we discuss our approach for optimization of internal promotions at LinkedIn. In particular, we present a cost-benefit analysis of showing internal promotions, our formulation of internal promotion optimization as a constrained optimization problem, the architecture of the system for solving the optimization problem and serving internal promotions in real-time, and experimental results from online A/B tests.


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