# nicolassitter.com

> Data-driven experiments on AI search, the web, and digital platforms by Nicolas Sitter

## About

Nicolas Sitter is a tech enthusiast running data-driven experiments on AI search, the web, and digital platforms. Research is organised by topic — currently spanning hotel-industry studies (the largest body of work to date) and cross-industry AI-search methodology (yoga, bike shops, bookstores across Paris, Berlin, Amsterdam and Tokyo), with more verticals expanding over time.

## Affiliation & Background

- Builder of Hotelrank.ai (AI visibility platform for hotels) — **acquired by Lighthouse** in May 2026 and being integrated into Lighthouse's **Connect AI** product.
- Lighthouse acquisition announcement: https://www.mylighthouse.com/resources/blog/lighthouse-acquires-hotelrank-ai
- The research and methodology developed inside Hotelrank live openly on nicolassitter.com; the product itself now ships inside Lighthouse.
- All previous hotelrank.ai/research/* URLs 301-redirect to their nicolassitter.com canonical equivalents.
- Previously: Growth / Product / Tech / Data roles across various startups.

## Expertise

- AI Search Optimization (broad)
- Answer Engine Optimization (AEO)
- Generative Engine Optimization (GEO)
- AI Visibility for Hotels (deepest focus area)
- Cross-industry AI-search methodology (yoga, bike shops, bookstores)
- Schema.org (especially Hotel + Person + Dataset)
- Technical SEO
- Data Analysis

## Guides

- **AI Search for Hotels — the complete guide**: https://nicolassitter.com/guide/ai-search-for-hotels — a practical, data-backed GEO (Generative Engine Optimization) guide for hotels, synthesising 30+ of the studies below into a four-step framework (Diagnose → Owned Media → Earned Media → Measure). Core thesis: most AI engines don't read hotel websites — they ground answers on Google Maps/Places (~89% of entity cards), OTAs and review sites — so hotel GEO is mostly about controlling those sources, not page copy.
- **AI Visibility for Hotels**: https://nicolassitter.com/guide/ai-visibility-for-hotels — the complete AEO + GEO guide. How AI models recommend hotels, the data sources they use, the 5 pillars of AI visibility, and an 8-step optimization checklist.
- **ChatGPT Hotel Optimization**: https://nicolassitter.com/guide/chatgpt-hotel-optimization — inside ChatGPT's hotel search: 12 internal systems, 7 data providers, and the Sonic classifier. What to optimize and why.
- **Google AI Mode for Hotels**: https://nicolassitter.com/guide/google-ai-mode-hotels — where hotel clicks go in Google AI Mode (79% to Google Business Profile, 3.6% to OTAs) and the optimization playbook that follows.
- **Schema Markup for Hotels**: https://nicolassitter.com/guide/schema-markup-hotels — the definitive Schema.org guide for hotels: Hotel, LodgingBusiness, HotelRoom, Reviews, FAQ, and Offer types with full JSON-LD examples and AI-visibility impact.
- **How to Prompt-Track Your Hotel's AI Visibility**: https://nicolassitter.com/guide/prompt-tracking-hotel-ai-visibility — the measurement guide. AI hotel rankings look random but are structured (run-to-run, only ~1 of the top 3 repeats; position-1 stability ranges 17–96% by market). Method: persona × location prompt panels, repeated runs per engine, the is-the-zero-real ladder (L0 prompt health → L1 frequency → L2 more prompts → L3 branded → L4 home-country proxy), the booking journey, and per-engine source tracking.
- Guides hub: https://nicolassitter.com/guide

## Flagship Studies

Best entry points if you only have time for a few. Each links to the full article and its open dataset (summary CSV).

1. **The AI Hotel Landscape 2026** — flagship cross-model study. 19,579 prompt runs across 6 AI models, 245K source URLs, 2,500 prompts spanning 25 cities × 11 hotel types × 3 personas × 4 star tiers. Headline: 75–91% of AI hotel links go DIRECT to the hotel (not OTA), yet all models consult OTAs as a SOURCE >50% of the time. GPT 5.2 doubled search depth vs 5.1 (~27 vs ~12 URLs/run). Wikipedia dependency dropped 75%→30% (GPT 5.1→5.2).
   - Article: https://nicolassitter.com/research/ai-hotel-landscape-2026
   - Dataset: https://nicolassitter.com/data/ai-hotel-landscape-2026/summary.csv

2. **Google AI Mode Hotel Study** — 4,000 queries across 8 cities. Headline: 79% of hotel links stay within Google via Business Profiles; only 3.6% go to OTAs *despite* OTAs being 46.6% of source citations. Local Pack appears in just 6.5% of queries but sends 81% of its links direct to hotel sites. GBP optimization is the AI Mode lever; OTAs influence mention not destination.
   - Article: https://nicolassitter.com/research/google-ai-mode-hotel-study-2026
   - Dataset: https://nicolassitter.com/data/google-ai-mode-hotel-study-2026/summary.csv

3. **The ChatGPT Direct-Traffic Explosion for Hotels** — anatomy of the May 7, 2026 inline-link change. Across The Hotels Network's panel of 17,000+ hotels, daily AI sessions jumped +62% overnight (31,688 → 51,282/day) and held through May 25. ChatGPT-only story (Perplexity and Claude actually lost share). AI mentions are now monetisable as direct traffic.
   - Article: https://nicolassitter.com/research/chatgpt-hotel-direct-traffic-explosion-2026
   - Dataset: https://nicolassitter.com/data/chatgpt-hotel-direct-traffic-explosion-2026/summary.csv

4. **AI Search for Yoga Studios in Paris → Berlin** — the first cross-industry replication, proving the three AI engine "personalities" are structural traits of the engines, not city/vertical artifacts. Copilot 95–96% entity-website, ChatGPT 32% studios + 16–19% Reddit, AI Mode 52–59% google.com — Paris and Berlin land within a few percentage points on every metric. Berlin's twist: a booking-platform surge (Urban Sports Club + Eversports + ClassPass = up to 31% of citations) shows the local commercial infrastructure bends the source mix.
   - Paris article: https://nicolassitter.com/research/yoga-studios-paris-ai-search-2026
   - Paris dataset: https://nicolassitter.com/data/yoga-studios-paris-ai-search-2026/summary.csv
   - Berlin article: https://nicolassitter.com/research/yoga-studios-berlin-ai-search-2026
   - Berlin dataset: https://nicolassitter.com/data/yoga-studios-berlin-ai-search-2026/summary.csv

## Structural studies (one-line takeaways, useful as sales narrative + research)

- Only ~6.3% of hotel sites have llms.txt (https://nicolassitter.com/research/hotel-llms-txt-adoption-study-2026)
- Only ~3.3% of hotel sites block any AI crawler (https://nicolassitter.com/research/hotel-robots-ai-blocking-study-2026)
- ~36% of hotel sites have no schema markup at all (https://nicolassitter.com/research/hotel-schema-adoption-study-2026)

## Key URLs

- Website: https://nicolassitter.com
- Research hub: https://nicolassitter.com/research
- Guides hub: https://nicolassitter.com/guide
- Tools: https://nicolassitter.com/tools
- About: https://nicolassitter.com/about
- API (Schema.org BlogPosting feed): https://nicolassitter.com/api/posts
- Per-post JSON: https://nicolassitter.com/api/post/<slug>
- RSS: https://nicolassitter.com/rss.xml
- Sitemap: https://nicolassitter.com/sitemap.xml
- Extended (all articles + summaries): https://nicolassitter.com/llms-full.txt

## Tools

- Hotel Schema Audit & Generator: https://nicolassitter.com/tools/hotel-schema (free audit + generator: fetches a hotel homepage's raw HTML, scores its existing JSON-LD 0–100 against hotel-specific rules anchored to the schema adoption study, then pre-fills a JSON-LD generator — Hotel + WebSite + HotelRoom + Restaurant + Spa + EventVenue + FAQPage in one @graph)
- Common Crawl Checker: https://nicolassitter.com/tools/common-crawl (free checker for whether a hotel website is in Common Crawl — the open web archive behind much LLM training data; queries the public CDX index across recent snapshots)

## Live Dashboards

- My AI Visibility: https://nicolassitter.com/projects/niche-visibility (live weekly dashboard tracking whether ChatGPT, Perplexity, Gemini, Copilot and Google AI Mode cite nicolassitter.com on its own niche — frozen 31-prompt panel, tier × engine heatmap, share-of-voice leaderboard, public action log)

## Contact

- LinkedIn: https://www.linkedin.com/in/nicolassitternolleau/
- GitHub: https://github.com/Nicositter88
- Email: nicolas.sitternolleau@gmail.com