Learning Optimal Personalised Reservation Prices in Impression Ad Auctions with Mixture Density Networks

Reservation prices have proven effective in boosting revenue in Generalised Second Price (GSP) auctions, particularly in cost-per-click (CPC) settings. However, in domains like music streaming, where ads are consumed passively without user clicks, a cost-per-impression (CPM) model is more appropriate. Additionally, in the music streaming domain, user intent is typically unknown, unlike in sponsored search, making it essential to optimally leverage all available user and contextual information when setting prices. This paper addresses the challenge of optimising reservation prices in GSP auctions with CPM pricing, adopting a personalised approach that accounts for both user- and advertiser-specific factors.