Formulates privacy-constrained advertising measurement as a robust causal decision problem under signal loss and derives a sharp decision frontier separating certifiable from unresolved incrementality claims.
Gordon, Florian Zettelmeyer, Neha Bhargava, and Dan Chapsky
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
AI brand mentions in ChatGPT/Claude/Gemini conversations causally raise open-web searches and visits by 4.3/2.4/1.0pp via pre-trend event study, stance classifier, and same-category controls on joined clickstream-conversation panel data.
citing papers explorer
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Privacy-Robust Incrementality Measurement for Advertising Systems under Signal Loss
Formulates privacy-constrained advertising measurement as a robust causal decision problem under signal loss and derives a sharp decision frontier separating certifiable from unresolved incrementality claims.
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From Prompt to Purchase: How AI Brand Recommendations Move Consumers on the Open Web
AI brand mentions in ChatGPT/Claude/Gemini conversations causally raise open-web searches and visits by 4.3/2.4/1.0pp via pre-trend event study, stance classifier, and same-category controls on joined clickstream-conversation panel data.