Reddit, Who What Wear, Wikipedia and Sephora are the top sources ChatGPT references most frequently when responding to beauty product recommendation prompts. That’s among the findings of a new analysis from Novi, the platform that helps brands and retailers ensure AI assistants like ChatGPT and Gemini can find and recommend their products in response to shoppers’ unique queries.
The Novi analysis examined 10.7 million citations across more than 98,000 source websites that ChatGPT considered when generating responses to user queries to identify the sources large language models (LLMs) most frequently pull from when generating beauty product recommendations. For beauty category queries overall, Reddit ranked first in number of citations by a significant margin, followed by editorial publication Who What Wear and free online encyclopedia Wikipedia. Sephora.com and Allure rounded out the top five.
The findings come as shoppers increasingly make AI platforms their first stop for product discovery, with nearly three quarters (73%) using AI search to learn about categories, products, brands or services. Over the most recent holiday shopping season, shoppers who were referred to retail sites from AI platforms converted 31% more often than others. Yet nearly half of brands (47%) don’t know if or how they show up in the answers AI platforms generate in response to shoppers’ questions.
Novi’s AI citation analysis underscores the soundness of its methodology, showing that brands benefit from building consistent, structured product data across their digital footprint and that certain social, editorial and retail sites where that information is validated may matter far more than others. In AI product recommendations, those citations can influence how LLMs understand product relevance, evaluate credibility and determine which products to recommend.
“AI models weigh both SKU-level data and trust signals when recommending what products consumers should buy,” said Kimberly Shenk, CEO of Novi. “Our research shows products with verified trust signals, like certifications and badges, are presented to shoppers significantly more often than products without them. For beauty brands, that means the most effective path to AI visibility is pairing well-structured data with verified trust signals, not chasing visibility via any single source.”
For Skincare and Fragrance Questions, AI Platforms Prioritize Different Sources
The Novi analysis shows that AI platforms prioritize different combinations of sources depending on the beauty category covered by the consumer’s particular query. For skincare questions, the AI algorithms lean more heavily on editorial outlets and major retailers, while for fragrance queries, retailer websites and brand-owned content are cited more frequently.
Top 5 Sources: Skincare Queries
- Who What Wear
- Sephora.com
- Allure
- Ulta.com
Although they don’t rank in the top 5 most frequently cited sources for skincare product queries, some brand websites, including those of Neutrogena and La Roche-Posay, do rank in the top 10, indicating that AI engines prioritize brand-owned content alongside editorial and retailer sources when generating product recommendations in this category.
Top 5 Sources: Fragrance Queries
- Wikipedia
- Who What Wear
- Fragrantica
- Sephora.com
Methodology
Novi analyzed 10.7 million citations in response to beauty product queries across ChatGPT from January 22, 2026 through May 20, 2026. The analysis identified the source websites that LLMs reference most frequently when generating beauty product recommendations, segmented by the overall beauty category and the skincare and fragrance subcategories. The analysis covered more than 98,000 source websites, the vast majority of which were cited fewer than 10 times in total.
About Novi
Novi is a technology platform that helps consumer brands drive discoverability, sales and trust by optimizing their product data so AI shopping tools can find and present it to shoppers. Serving as the bridge between brands, certification organizations and major retailers like Target, Ulta and Sephora, Novi ensures SKU-level data is accurate, consistent and structured, so AI tools can easily surface it, no matter how consumers phrase their shopping questions. Novi then circulates each brand’s optimized digital data footprint, increasing discoverability through consistent citations across platforms. Founded in 2020 and headquartered in Larkspur, CA, Novi is backed by Tiger Global, Defy, Greylock and other leading venture firms.
To learn more, visit NoviConnect.com.
View source version on businesswire.com: https://www.businesswire.com/news/home/20260609998894/en/
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