Dynamic Reserve Price Design for Lazada Sponsored Search
In ecommerce platform, users will be less likely to use organic search if sponsored search shows them unexpected advertising items, which will be a hidden cost for the platform. In order to incorporate the hidden cost into auction mechanism which helps create positive growth for the platform, we turn to a reserve price design to decide whether we sell the traffic, as well as build healthy relationships between revenue and user experience. We propose a dynamic reserve price design framework to sell traffic more efficiently with minimal cost of user experience while keeping long term incentives to the advertisers to reveal their valuations truthfully. A distributed algorithm is also proposed to compute the reserve price with billion scale data in the production environment. Experiments with offline evaluations and online AB testing demonstrate that it is a simple and efficient method to be suitably used in industrial production. It has already been fully deployed in the production of Lazada sponsored search.
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