Ads in Conversations
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Abstract (arXiv)
We study the optimal placement of advertisements for interactive platforms like conversational AI assistants. Importantly, conversations add a feature absent in canonical search markets -- time. The evolution of a conversation is informative about ad qualities, thus a platform could delay ad delivery to improve selection. However, delay endogenously shapes the supply of quality ads, possibly affecting revenue. We characterize the equilibria of first- and second-price auctions where the platform can commit to the auction format but not to its timing. We document sharp differences in the mechanisms' outcomes: first-price auctions are efficient but delay ad delivery, while second-price auctions avoid delay but allocate inefficiently. Revenue may be arbitrarily larger in a second-price auction than in a first-price auction. Optimal reserve prices alleviate these differences but flip the revenue ordering.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Mar 2024.
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Citing papers per year: 2025: 3; 2026: 1.
4 papers.
- 2025Game Theory Meets Large Language Models: A Systematic Survey with Taxonomy and New Frontierscited by 16
- 2026Ad Insertion in LLM-Generated Responsescited by 8
- 2025MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attributioncited by 3
- 2025Sponsored Questions and How to Auction Themcited by 1
- 2026Ad Insertion in LLM-Generated Responses27 Jan 2026
- 2025MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution5 Dec 2025
- 2025Sponsored Questions and How to Auction Them3 Dec 2025
- 2025Game Theory Meets Large Language Models: A Systematic Survey with Taxonomy and New Frontiers13 Feb 2025