Overview
Stellagent released the Hakone edition of its AI Hotel Recommendation Survey on July 8, 2026. We asked ChatGPT, Claude, Gemini, Perplexity, and Microsoft Copilot for Hakone accommodation recommendations across five travel scenarios, collecting 125 responses and analyzing recommendation concentration as well as differences by scenario and AI service.
For more information, see the press release on PR TIMES.
The top five properties accounted for 31.1% of valid AI recommendations for Hakone
Background
Travelers are increasingly asking generative AI where to stay instead of comparing search results and booking sites one by one. The properties that appear first in an AI answer, and the reasons given for recommending them, can become the starting point for a traveler's consideration process.
The survey used five scenarios — couples, families with children, inbound visitors, students and young friends, and adult family trips — and recorded the recommended property, rank, rationale, best-fit traveler, and suggested booking path.
Key Findings
- Of 625 recommendation slots across 125 responses, 621 could be extracted as property names, covering 114 properties.
- The top five properties accounted for 31.1% of the 621 valid recommendations. Fujiya Hotel led with 51 mentions, followed by Hakone Kowakien Ten-yu with 49 and Hakone Ashinoko Hanaori with 34.
- Gora Kadan received the most first-place recommendations, with 19. The strongest properties changed by scenario: Hakone Hotel Kowakien for families with children, Gora Kadan for inbound travelers, and Fujiya Hotel for adult family trips.
Survey Overview
| Item | Details |
|---|---|
| AI services | ChatGPT, Claude, Gemini, Perplexity, Microsoft Copilot |
| Survey period | July 1–2, 2026 |
| Runs | 5 AIs × 5 scenarios × 5 runs, 125 responses (625 recommendation slots) |
| Data captured | Rank, property, rationale, best-fit traveler, booking path, and URL |
| Conducted by | Stellagent Inc. |
Implications for Hotels and Ryokan
Property information should connect concrete travel conditions — family composition, budget, activities, access, dining, and hot springs — with the reasons a property is a good fit. Operators also need a clear path from the information AI references to the official booking page and an operating process that reduces conflicts with outdated information.
The full ranking, scenario-level and AI-level analyses, and methodology are available in the AI Hotel Recommendation Survey: Hakone Edition.
Looking Ahead
Stellagent will continue conducting AI recommendation studies across regions and travel scenarios to show how accommodation providers are understood and recommended by AI.