Location, Location, Generation: Where You Ask Matters for Generative Engine Optimization
Generative search engines answer local and commercial questions with a written answer and a few cited sources. A growing practice of generative engine optimization (GEO) monitors which sources and brands these answers show, typically from a single place. In this paper, we present a controlled audit of how the user's location changes the sources that generative engines cite. We ask 300 questions of ChatGPT with 19 declared locations, and of ChatGPT and Gemini from five network locations, each twice to measure run-to-run noise (31,200 answers). The engines take location from different channels. ChatGPT follows the location an application declares, down to the city: it writes the place into ...
| Authors | Mahe Chen, Nick Koudas |
|---|---|
| Primary category | cs.IR |
| Published | 16 October 2026 |
| Last updated at source | 16 October 2026 |
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