AI franchise recommendations draw mainly on comparison sites, October study finds

Which sources does generative AI use to support its franchise suggestions? A study covering October 2026, published by Branding Works on 5 November, found that franchise comparison and recruitment websites ranked among the leading sources cited. For those exploring Japan’s franchise market, the findings offer a reason to look beyond the names suggested and examine the information behind them.

Comparison and recruitment sites lead citation share

The study repeatedly submitted the same question — “Which franchises would you recommend?” — to ChatGPT and Gemini, recording company names, cited sources and other details in their responses. Among the websites cited to support answers, Franchise WEB Report had the highest citation share, at 9.7%.

Franchise Hikaku Net followed at 9.4%, with Entrep at 8.7%, placing sites offering franchise comparisons and recruitment information at the top of the list. IBJ’s website accounted for 5.8% and YouTube for 5.2%. All figures are from Branding Works.

The company said comparison sites and ranking articles formed the core of the cited material, suggesting that their content influences generative AI recommendations. However, the study directly demonstrates only which sources were cited in the responses measured. It does not establish that appearing on a particular website causes more recommendations, nor that a listing guarantees inclusion among the suggested franchises.

Citation share and company mention rate are also different measures. Citation share indicates how information sources are used, while mention rate is the proportion of all responses in which a company’s name appears. The ranking of frequently cited websites cannot therefore be read as a ranking of franchise brands’ merits.

AI suggestions focus on costs, margins and demand

The company analysed not only the names mentioned but also the angles generative AI used to present its suggestions. In October’s responses, “low start-up costs” appeared in 35.9%, “high profit margins” in 20.4% and “stable demand” in 13.8%.

Osoji Honpo, Otakaraya and Kaitori Daikichi were the main brands presented in relation to start-up costs. The same three brands were highlighted for profit margins, while Magokoro Bento, Takeda Juku and Takuhai Cook 123 were presented in relation to stable demand.

The important distinction here is between AI-generated descriptions and evidence of business profitability. This analysis summarised how AI described each brand. It was not a like-for-like comparison of their start-up costs or profit margins, and it does not guarantee franchisees’ future demand or profits.

The announcement also summarised responses that linked cost burdens to whether premises or stock were required, and stable demand to Japan’s ageing population. Prospective franchisees should not treat these brief explanations as statements of the actual business terms. They need to check them against the contractual and operating conditions that would apply.

Read the findings as observations from 167 responses over 28 days

The study period ran from 1 to 31 October 2026, with measurements taken on 28 days. The remaining three days were excluded because of maintenance to the measurement system.

Using the ChatGPT and Gemini APIs with web search enabled, the researchers submitted the same question to each service three times a day. Of the 168 planned responses, one could not be retrieved because of a response error, leaving 167 valid responses for analysis.

The results are therefore a record of answers to a particular question under specific measurement conditions. They do not measure users’ overall search behaviour or prospective franchisees’ preferences. Nor do they establish whether the same sources or candidates would appear if the question included a budget, location or level of experience.

Branding Works explicitly noted that generative AI responses change daily and that these figures reflect trends during the study period. It also stated that the study did not assess the relative quality of the companies’ services. Franchisors presenting these figures should likewise distinguish between the fact that “AI cited this source” or “AI mentioned this name” and any assessment of quality or business performance.

Follow citations back to primary information before investing

The findings show how comparison and recruitment websites serve as information gateways when generative AI is used to identify potential franchises. They also highlight the need for caution: the more concise an answer becomes, the easier it is to read statements about costs and earnings without considering the conditions of an individual opening.

For prospective franchisees, a practical approach is not merely to note the brands AI suggests, but to follow the cited articles and recruitment listings to check the basis for each suggestion. Comparing that information with the franchisor’s stated costs, operating arrangements and support can then help identify questions to raise in meetings. This is different from using the study’s rankings as a recommended order of franchise choices.

For franchisors, the findings also offer a reason to review descriptions on external recruitment and comparison pages, rather than focusing solely on their own websites. Nevertheless, the study cannot establish the effectiveness of any particular listing strategy. Decisions about information outreach should be considered separately from the need to explain accurately the terms on which prospective franchisees will make their decisions.

The practical takeaway is to treat AI recommendations as a starting point for checks, not a conclusion. Verify the sources and compare statements about costs, profits and demand with the franchisor’s documentation before proceeding with a franchise decision.