Part of GEOly's "GEO / AEO Expert Watch" series · meet **Lily Ray**, a quick map of their public work and where to follow them — with links to the original sources.
Who is Lily Ray
Publishes practical investigations into Google AI Overviews, citation quality, algorithm updates, and spam risks.
These experts track AI Overviews / AI Mode and algorithm updates first-hand: who gets cited, why citations swing, and how trust signals affect appearance. They are GEO’s weather station. Their recurring focus areas include: AI Overviews, E-E-A-T, algorithm research.
What GEO / AEO practitioners can learn from Lily Ray
- **Citations are volatile**: for the same query, sources can differ sharply across time and platforms — single snapshots mislead, so monitor continuously. - **Trust signals gate inclusion**: E-E-A-T, author/source credibility and factual consistency increasingly act as the threshold for being cited. - **Make monitoring systematic**: turn core questions, competitors and brand terms into fixed probes you run on a schedule and diff over time.
**GEOly angle**: Evidence-led piece on AI Overview citation volatility and trust signals.
What it means for brands going global
For global-facing brands, do not treat one day’s mention in ChatGPT as victory, nor one day’s disappearance as disaster. Build cross-platform, cross-time citation monitoring (exactly what GEOly does) and judge GEO health by trend, not snapshot.
Follow Lily Ray: homepage & socials
- [Website](https://lilyray.nyc) - [LinkedIn](https://www.linkedin.com/in/lily-ray-44755615/) - [X](https://x.com/lilyraynyc) - [YouTube](https://www.youtube.com/channel/UCjKPDVkFchRoWNENtaG-n-g)
To meet more experts across GEO, AEO and agentic commerce, visit the [GEOly author hub](/blog/author).
*This profile is an editorial compilation of publicly available information, curated by the GEOly team for industry learning and reference. All links point to the expert's own public pages. Contact us for any correction or removal.*
