Dynamic Reserve Price Design for Lazada Sponsored Search
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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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