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MEBS: Multi-task End-to-end Bid Shading for Multi-slot Display Advertising

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arxiv 2403.02607 v1 pith:VKC7SON7 submitted 2024-03-05 cs.GT cs.AI

MEBS: Multi-task End-to-end Bid Shading for Multi-slot Display Advertising

classification cs.GT cs.AI
keywords advertisingdisplaymulti-slotliftmethodonlineshadingend-to-end
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Online bidding and auction are crucial aspects of the online advertising industry. Conventionally, there is only one slot for ad display and most current studies focus on it. Nowadays, multi-slot display advertising is gradually becoming popular where many ads could be displayed in a list and shown as a whole to users. However, multi-slot display advertising leads to different cost-effectiveness. Advertisers have the incentive to adjust bid prices so as to win the most economical ad positions. In this study, we introduce bid shading into multi-slot display advertising for bid price adjustment with a Multi-task End-to-end Bid Shading(MEBS) method. We prove the optimality of our method theoretically and examine its performance experimentally. Through extensive offline and online experiments, we demonstrate the effectiveness and efficiency of our method, and we obtain a 7.01% lift in Gross Merchandise Volume, a 7.42% lift in Return on Investment, and a 3.26% lift in ad buy count.

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