Reddit dominates ChatGPT beauty product recommendations by a significant margin, outranking every retailer and editorial outlet combined, according to new citation analysis released today by Novi, a product data platform that helps consumer brands improve visibility in AI-generated answers.

The findings land at a moment when AI assistants are increasingly where shoppers start - not finish - their product research. Nearly three quarters of consumers, 73% according to Novi, now use AI search to learn about categories, products, brands, or services before making purchase decisions. The analysis, published June 9, 2026, is based on 10.7 million citations generated by ChatGPT in response to beauty product queries from January 22 through May 20, 2026. It covered more than 98,000 source websites, the vast majority of which were cited fewer than 10 times in total across the full period.

Five sources drove a third of all recommendations

For beauty queries overall, Reddit ranked first by citation volume by what Novi describes as a significant margin. Who What Wear, the fashion and beauty editorial publication, ranked second. Wikipedia placed third. Sephora.com and Allure rounded out the top five. Five sources, in other words, accounted for roughly a third of all citations in a pool of nearly 11 million data points spread across tens of thousands of websites.

The concentration matters. It means a beauty brand appearing on none of those five properties is largely absent from the way ChatGPT currently understands and communicates product relevance in that category. Most of the 98,000-plus websites in the dataset were cited so rarely as to have negligible influence on what the model recommends when someone asks which moisturizer to buy or which fragrance is worth trying.

According to Novi, "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."

The quote is notable for what it does not say. It does not claim Reddit is the destination beauty brands should chase directly. Reddit's position at the top of the citation ranking reflects organic community behaviour - user conversations about product experiences, ingredient comparisons, and recommendations that have accumulated over years. That content exists independent of any brand's marketing decisions. What brands can control is the quality and structure of their own product data, and whether it appears in the retailer and editorial sources that the model also draws on.

How category splits the source hierarchy

The Novi analysis shows the top-five source hierarchy changes depending on which beauty subcategory the query concerns. The platforms ChatGPT leans on for skincare recommendations are not the same ones it pulls from most for fragrance recommendations.

For skincare queries, the model leans more heavily on editorial outlets and major retailers. Reddit still ranks first. Wikipedia and Who What Wear also appear. Editorial sources and retail platforms with strong skincare content carry relatively more weight here compared to the overall beauty ranking. Notably, some brand websites appear in the top 10 for skincare even though none reaches the top five. Neutrogena and La Roche-Posay both rank in the top 10, which Novi interprets as evidence that AI engines do consider brand-owned content alongside editorial and retailer sources when generating skincare recommendations - just not as prominently as Reddit or major publishers.

For fragrance queries, the source mix shifts further toward retailer and brand-owned content. The top five for fragrance are Reddit, Wikipedia, Who What Wear, Fragrantica - a fragrance-specific database and community - and Sephora.com. The presence of Fragrantica is notable. It is not a general beauty destination. It is a niche reference resource for fragrance enthusiasts, and its appearance in the top five for that subcategory suggests that ChatGPT draws on domain-specific community databases when the query requires specialized knowledge. Ulta.com also appears in the top five for certain beauty subcategories.

The difference between how AI surfaces handle skincare versus fragrance is consistent with a broader pattern PPC Land has tracked across AI citation research: citation sets are not monolithic. Different models, and even the same model across different query types, weight different source categories. A brand optimizing only for its presence on general editorial platforms may find that its fragrance line underperforms in AI recommendations precisely because it lacks presence on the specialized community and retailer sources that dominate fragrance citation pools.

What the methodology captured - and what it did not

Novi's analysis covered ChatGPT only. It ran from January 22 through May 20, 2026, a period of approximately four months. The 10.7 million citations came from responses to beauty product queries - not all ChatGPT queries, and not queries across competing AI platforms. The company has not released the specific prompts used to generate those citations, which makes it difficult to assess how representative the query set is of actual shopper behavior.

The 98,000-plus source websites in the dataset also require context. Most were cited fewer than 10 times across the entire four-month period. The dataset is highly concentrated at the top. That distribution is consistent with findings from other citation analyses. A Foundation Marketing analysis of more than 28 million AI-generated responses, covered by PPC Land, found similar concentration patterns in local services citation data, with Yelp alone accumulating 512,680 citations and ranking 3.4 times ahead of its nearest competitor. Concentration at the top of citation rankings appears to be a structural feature of how large language models use retrieval-augmented generation, not a specific characteristic of any one category.

PPC Land has also tracked the technical infrastructure behind how citations form. OpenAI operates three separate crawlers: GPTBot for model training, OAI-SearchBot for search indexing, and ChatGPT-User for live retrieval. Citations in AI responses appear to emerge primarily from live retrieval rather than from training data - a distinction that matters for brands thinking about how to improve their appearance in ChatGPT answers. A website that has blocked training crawlers may still appear in citations if the live retrieval system can reach its content. Conversely, a site that ranks well for SEO purposes is not guaranteed to appear in AI citations. Research cited by PPC Land has found only 12% overlap between Google's top-10 organic results and sources cited by platforms like ChatGPT or Perplexity.

The conversion argument for AI discoverability

Novi grounds its analysis in commercial stakes. According to the company's research, during the most recent holiday shopping season, shoppers referred to retail sites from AI platforms converted 31% more often than those who arrived through other channels. That figure is directionally consistent with data from other sources. Adobe reported that shoppers arriving from AI services were 30% more likely to convert during the 2025 holiday season, a figure PPC Land noted in coverage of how most holiday shoppers planned to use AI to select gifts.

The conversion premium matters because it shifts the framing. If AI-referred traffic converts at a meaningfully higher rate than standard search or social traffic, then absence from AI recommendation pools is not merely a visibility problem. It is a revenue problem. Yet Novi's own data suggests the challenge is large: nearly half of brands - 47% according to the analysis - do not know whether or how they appear in AI-generated answers to shopper queries.

That 47% figure is difficult to verify independently. But the directional claim - that a large portion of brands have no systematic way of tracking their AI citation performance - is consistent with the state of measurement infrastructure across the industry. Microsoft Clarity only added its AI Citations feature as a generally available product in May 2026. Before that release, measurement of AI citation behaviour required third-party tools or manual tracking. The tooling for understanding how brands appear in AI answers is newer, less standardized, and less widely adopted than conventional analytics.

Why structured data and trust signals sit at the center of Novi's argument

The report's framing around SKU-level structured data reflects Novi's positioning as a platform that helps brands organize and distribute product information to retailers, certification bodies, and AI tools. Novi serves Target, Ulta, and Sephora as retail partners and was founded in 2020. It is backed by Tiger Global, Defy, and Greylock, and is headquartered in Larkspur, California.

The argument Novi is making - that well-structured data paired with verified trust signals outperforms a strategy of chasing any single citation source - has parallels in how Google has approached product data quality for its own AI-driven shopping surfaces. As PPC Land reported, Google's Merchant Center documentation treats data completeness and structural accuracy as determinants of AI Mode visibility independent of advertising spend. Two brands selling comparable products in the same category receive different AI surface visibility based on which has more complete structured attributes. The underlying logic - that AI recommendation systems reward completeness, accuracy, and verifiable trust signals over raw presence in any single channel - is the same logic Novi applies to ChatGPT citation behavior.

The role of certifications and badges in Novi's framework is specific to the beauty and consumer packaged goods categories where product claims are regulated, contested, and actively researched by shoppers. Clean beauty certifications, sustainability badges, and dermatologist-tested claims are the kinds of attributes that editorial sources and retailer pages regularly reference when writing about or listing products. If ChatGPT is pulling citations from those editorial and retailer sources, and those sources describe verified claim badges as part of their product coverage, then a brand with verified claims is more likely to appear in that chain of retrieval than a brand without them.

What the data means for the marketing community

The Novi analysis adds specificity to a question the marketing and media-buying community has been grappling with as AI-assisted search grows. The question is not just whether brands appear in AI answers - it is which sources AI draws on in a given category, how concentrated those source pools are, and what brands can realistically do to improve their position.

For beauty brands specifically, the data suggests the following picture as of mid-2026. Reddit's dominance in citation volume reflects years of organic community content that brands cannot replicate directly. Editorial outlets like Who What Wear and Allure retain relevance as secondary sources, though not at Reddit's scale. Retailer sites - Sephora, Ulta, Fragrantica for fragrance - carry weight, particularly for subcategory-specific queries. Brand-owned sites can appear in the top 10 for skincare without reaching the top five, suggesting that maintaining complete, authoritative product pages on a brand's own domain is not irrelevant, just not the primary driver of citation volume at the category level.

The structural issue for brands is that citation sets change substantially month over month. Research PPC Land has cited found that 40-60% of sources cited by large language models turn over within a single month. A citation landscape that looks like the Novi analysis today may look meaningfully different by autumn. The January-to-May window the analysis covers is reasonably long for this kind of research, but it cannot account for shifts that will occur as OpenAI updates its retrieval systems, changes its crawler documentation, or adjusts how it weights different source types.

OpenAI's introduction of shopping functionality in ChatGPT - a feature that allows the model to display products in visually rich carousels with direct retailer links - changes the stakes further. When ChatGPT moves from citing external sources to displaying shoppable product results, the question of which sources the model trusts becomes the question of which products it shows. The two issues - citation behavior and shopping recommendation behavior - are converging. Novi's analysis examines the citation side. The shopping side remains a separate, evolving surface.

Timeline

Summary

Who: Novi, a product data platform founded in 2020 and headquartered in Larkspur, California, backed by Tiger Global, Defy, and Greylock, published the analysis. The research covers ChatGPT's citation behavior as the AI platform being examined. The findings are relevant to beauty brands, consumer packaged goods marketers, retailers including Target, Ulta, and Sephora, and digital advertisers working in AI-driven shopping environments.

What: An analysis of 10.7 million ChatGPT citations generated in response to beauty product queries, covering more than 98,000 source websites. The analysis identifies which sources ChatGPT references most frequently when generating beauty, skincare, and fragrance product recommendations. Reddit ranked first overall by a significant margin. Who What Wear ranked second, Wikipedia third, Sephora fourth, and Allure fifth. Source rankings differ by subcategory: fragrance queries surface Fragrantica and rely more heavily on retailer and brand-owned content, while skincare queries show greater editorial reliance but also allow brand websites into the top 10.

When: The citation data covers January 22 through May 20, 2026. The analysis was published on June 9, 2026.

Where: The analysis was published by Novi via Business Wire. The underlying citation activity took place within ChatGPT's web-connected response system. Novi is headquartered in Larkspur, California. The findings apply to any beauty, skincare, or fragrance brand seeking visibility in ChatGPT's product recommendation responses, regardless of geography.

Why: The analysis matters because AI-assisted product discovery is growing as a share of how shoppers find and evaluate products. According to Novi, 73% of consumers use AI search for product research, and shoppers referred from AI platforms converted 31% more during the most recent holiday season than other shoppers. Despite that, nearly half of brands - 47% according to Novi - have no clear picture of how or whether they appear in AI-generated answers. Understanding which source types ChatGPT actually draws on when recommending beauty products provides a more concrete basis for brand visibility strategy than broad claims about AI optimization.