# Research by LLM Audit

> Original measurements on how AI assistants recommend brands. Each study states its method and its limits and publishes the raw answers, so the numbers can be recounted and cited.

Canonical page: https://llmaudit.app/research

### How repeatable are AI recommendations? 4,500 answers from three model APIs

Study, 2026-08-23. The same buyer question asked 5 times to the same model returned the same set of brands in 15.0 percent of cases (mean Jaccard 0.54); the first-named brand held in 75 percent of runs; half of all brands named (49.8 percent) appeared only once. Dataset and raw answers downloadable, CC BY 4.0.

https://llmaudit.app/research/how-repeatable-are-ai-recommendations (markdown: https://llmaudit.app/research/how-repeatable-are-ai-recommendations.md)

### FAQ page or H2 sections? What AI models actually cite

Earlier data note, 2026-08-20. 438 URLs cited by ChatGPT and Gemini in 60 days of live buyer answers, classified by page type. None was a FAQ page; the models pointed at home and product pages.

https://llmaudit.app/blog/faq-page-vs-h2-sections-what-ai-models-cite (markdown: https://llmaudit.app/blog/faq-page-vs-h2-sections-what-ai-models-cite.md)

## Read next

- How the audit works: https://llmaudit.app/methodology.md
- Run the free audit: https://llmaudit.app/

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Machine-readable index: https://llmaudit.app/llms.txt · Full context: https://llmaudit.app/llms-full.txt · All URLs: https://llmaudit.app/sitemap.xml · Developer and agent resources: https://llmaudit.app/developers.md