What elements are listed as characteristics of restaurants recommended by AI?

The number of Google reviews and the frequency of appearance in summary articles that AI refers to significantly influence recommendations.

Is there a correlation between AI recommendation frequency and review scores?

According to the survey results, there is no clear correlation between AI recommendation frequency and review scores (number of stars).

Under what conditions does AI recommend restaurants?

In this survey, general prompts were used. However, prompts containing personal conditions such as anniversaries or private rooms may lead to recommendations of smaller, less famous establishments.

What are CHILLNN's business activities?

CHILLNN develops and provides accommodation reservation systems and offers marketing support to lodging facilities.

CHILLNN AIO Lab Conducts Large-Scale Survey on 'Characteristics of Restaurants Recommended by AI'

Q: In which cities was the survey conducted?

The survey was conducted in five cities: Sapporo, Shinjuku, Kyoto, Osaka, and Fukuoka, over about one month (April 2 to May 5).

Published May 21, 2026 8:00 PM ・ Updated Jun 14, 2026 4:17 AM ・ 4 min read ・ Source: PR TIMES

CHILLNN's AIO Lab has conducted a large-scale survey in five major Japanese cities on how generative AI recommends restaurants. The study found that review volume and inclusion in summary articles are key, while star ratings showed no clear correlation.

The use of generative AI such as ChatGPT and Gemini to search for restaurants is rapidly increasing. With the integration of Gemini into Google Maps (the AskMaps feature), AI-driven local search is expected to expand further.

However, for restaurant operators, the mechanism of "how to be recommended by AI" remains unclear. While there is prior research overseas, guidelines for AIO (AI Optimization) measures in the Japanese market have not been clarified. Therefore, this survey explored the characteristics of restaurants easily recommended by AI, specifically for the Japanese market.

Overview of the Initiative

For approximately one month (April 2 to May 5), different prompts were executed against three types of AI—ChatGPT, Perplexity, and Google AI Overview—across five cities (Sapporo, Shinjuku, Kyoto, Osaka, and Fukuoka), and the restaurants recommended were aggregated on a large scale. The main findings are as follows:

- Restaurants recommended by AI show a positive correlation with the number of Google reviews, but not with the review score (star rating). - There is no clear correlation between the number of Google search results for "restaurant name x area" (web exposure) and the frequency of AI recommendation. - The frequency of appearance in "summary articles" referenced by AI significantly affects whether or not it is recommended.

However, the survey prompts used were limited to general phrases such as "recommended restaurants in XX." For prompts that include more personal conditions such as anniversaries, private rooms, or specific genres, there is a possibility that unique, small-scale shops other than famous stores could be recommended by AI. CHILLNN AIO Lab will continue to investigate and disseminate practical knowledge on recommendation trends with personal prompts and AIO measures in the restaurant sector.

The survey results are available for free on the AIO Lab media page.

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Source: PR TIMES
Category: Survey
Dates in source: 5/5

CHILLNN AIO Lab Conducts Large-Scale Survey on 'Characteristics of Restaurants Recommended by AI'

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Overview of the Initiative

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