eCommerce: Beauty
Across 59 brands, 550 AI citations, the leaders in this category are separating through trusted third-party visibility, not owned publishing alone. CeraVe currently leads with 4.0% share of voice and appears in 29.3% of prompts analyzed, showing that AI visibility is being shaped by broad citation authority across the category, not just isolated brand strength.
How to Read This Report
This is Avenue Z’s second AIVx Beauty report, comparing June 2026 AI visibility results against our 2025 baseline to show where citation authority is strengthening, slipping, or newly emerging. Using a Peec workspace, Avenue Z tracked which brands were cited by ChatGPT, what kinds of sources those citations came from, and where brands appeared within model responses across 75 category-relevant prompts spanning 3 topic clusters — including citation frequency, source type, and response position. Data collection window: June 10 – 17, 2026.
The prompt set was structured around three core category terms consumers use when researching this space: Cosmetics, Hair Care, and Skin Care.
- “Which bronzers give a natural sun-kissed look without turning orange?”
- “Best brow products for creating fuller, natural-looking brows that actually last”
- “Best lightweight conditioners for fine hair that needs moisture without losing volume”
- “Top hair care products for protecting color from fading between salon visits”
- “Top cleansing balms and oils for removing sunscreen and makeup without clogging pores”
- “Best vitamin C serums for brightening dull skin and fading post-acne marks”
Why AI Visibility Matters More in 2026
Before examining how specific brands perform in AI, it is important to understand the scale and trajectory of AI adoption, and what the shift means for brand discoverability in the Beauty category.
In 2025, AI was still emerging as a new discovery behavior. In 2026, it is moving into the mainstream. ChatGPT alone grew from 400 million weekly active users in February 2025 to more than 900 million in early 2026, with especially strong growth among older users. For brands in this category, that shift matters because category discovery increasingly begins inside AI-assisted research — before a user ever reaches a brand site, app store listing, or review page.
The behavior change is especially important for this category because the questions consumers ask AI map directly to the criteria buyers use to choose: price, features, reliability, service quality, reputation, and trust. When AI becomes a first-stop source for those comparisons, visibility inside AI responses becomes part of the competitive landscape — not a future-facing experiment.
For brands in this category, the implication is straightforward. If your brand is not being cited when consumers ask AI which options are most trusted, most affordable, or best aligned to their needs, you are missing an increasingly important layer of consideration. AEO is no longer optional groundwork. It is becoming part of how category leaders are built.
Source: Various industry estimates, 2026
AI is not a single channel. Users interact with AI models across four distinct surfaces, each with different implications for brand discoverability. Sources: OpenAI usage reports, Statista AI market share data, Gartner AI adoption forecasts, 2025–2026.
The dominant interface. Consumers type questions directly into ChatGPT, Claude, or Gemini — asking which brand best fits their needs, which option is most trusted, or how to get started with a category leader. Brand citations appear in direct responses, the primary visibility surface.
Perplexity, Bing Copilot, and Google AI Overviews layer AI responses on top of web search. Consumers comparing options, pricing, or policies see AI-generated summaries with source links. Visibility here requires both brand authority and strong web presence.
Siri, Alexa, and mobile AI assistants surface single-answer responses. When a consumer asks which brand to trust, the brand that owns the top citation wins the entire query. Zero-sum visibility.
AI agents that compare products, summarize terms, and guide purchase decisions on behalf of consumers. Early-stage but growing fast. Brands with structured data and clear product descriptions have a significant head start.
How AI Visibility Is Taking Shape in Beauty
Four lenses on the data: share of voice, editorial authority, content, and technical signals. Together they reveal the complete picture of how AI models perceive and recommend brands in the Beauty category.
Visibility is relatively distributed. The top 5 brands hold 18.8% of AI citations.
| Rank | Brand | 2025 Rank ⓘ | Δ ⓘ | Z-Score ⓘ | AI Visibility ⓘ | SOV ⓘ | Sentiment ⓘ | Citations ⓘ | Tier |
|---|---|---|---|---|---|---|---|---|---|
| 1 | #1 | – | 88.8 | 29.3% | 4.0% | 75 | 22 | Leader | |
| 2 | #13 | ↑11 | 88.8 | 28.0% | 3.8% | 75 | 21 | Leader | |
| 3 | — | – | 85.5 | 28.0% | 3.8% | 75 | 21 | Leader | |
| 4 | #21 | ↑17 | 87.3 | 26.7% | 3.6% | 75 | 20 | Leader | |
| 5 | #16 | ↑11 | 85.5 | 26.7% | 3.6% | 75 | 20 | Leader | |
| 6 | #19 | ↑13 | 80.2 | 24.0% | 3.3% | 75 | 18 | Leader | |
| 7 | #5 | ↓2 | 75.7 | 24.0% | 3.3% | 75 | 18 | Leader | |
| 8 | #25 | ↑17 | 81.4 | 24.0% | 3.3% | 75 | 18 | Leader | |
| 9 | #10 | ↑1 | 73.3 | 22.7% | 3.1% | 75 | 17 | Challenger | |
| 10 | #8 | ↓2 | 72.4 | 22.7% | 3.1% | 75 | 17 | Challenger | |
| 11 | NYX | #24 | ↑13 | 73.5 | 21.3% | 2.9% | 75 | 16 | Challenger |
| 12 | Briogeo | #15 | ↑3 | 70.5 | 21.3% | 2.9% | 75 | 16 | Challenger |
| 13 | Olaplex | #7 | ↓6 | 67.8 | 21.3% | 2.9% | 75 | 16 | Challenger |
| 14 | K18 | #30 | ↑16 | 71.1 | 20.0% | 2.7% | 75 | 15 | Challenger |
| 15 | The Ordinary | #9 | ↓6 | 64.5 | 20.0% | 2.7% | 75 | 15 | Challenger |
| 16 | NARS | #6 | ↓10 | 63.3 | 20.0% | 2.7% | 75 | 15 | Challenger |
| 17 | Charlotte Tilbury | #3 | ↓14 | 58.8 | 18.7% | 2.5% | 75 | 14 | Challenger |
| 18 | Rare Beauty | #11 | ↓7 | 58.3 | 17.3% | 2.4% | 75 | 13 | Challenger |
| 19 | Maybelline | #4 | ↓15 | 55.9 | 17.3% | 2.4% | 75 | 13 | Challenger |
| 20 | e.l.f. Cosmetics | #18 | ↓2 | 59.8 | 17.3% | 2.4% | 75 | 13 | Challenger |
| 21 | Hourglass | #31 | ↑10 | 63.4 | 17.3% | 2.4% | 75 | 13 | Emerging |
| 22 | Fenty Beauty | #14 | ↓8 | 58.0 | 17.3% | 2.4% | 75 | 13 | Emerging |
| 23 | MAC | #26 | ↑3 | 58.0 | 16.0% | 2.2% | 75 | 12 | Emerging |
| 24 | Oribe | #23 | ↓1 | 56.8 | 16.0% | 2.2% | 75 | 12 | Emerging |
| 25 | Estée Lauder | #27 | ↑2 | 54.4 | 14.7% | 2.0% | 75 | 11 | Emerging |
| 26 | Verb | #54 | ↑28 | 57.9 | 13.3% | 1.8% | 75 | 10 | Emerging |
| 27 | SkinCeuticals | #17 | ↓10 | 44.1 | 12.0% | 1.6% | 75 | 9 | Emerging |
| 28 | Pureology | #22 | ↓6 | 42.8 | 10.7% | 1.5% | 75 | 8 | Emerging |
| 29 | Urban Decay | #12 | ↓17 | 39.5 | 10.7% | 1.5% | 75 | 8 | Emerging |
| 30 | Tarte | #20 | ↓10 | 38.2 | 9.3% | 1.3% | 75 | 7 | Emerging |
| 31 | Huda Beauty | #34 | ↑3 | 42.1 | 9.3% | 1.3% | 75 | 7 | Emerging |
| 32 | IT Cosmetics | #45 | ↑13 | 45.1 | 9.3% | 1.3% | 75 | 7 | Emerging |
| 33 | ColourPop | #36 | ↑3 | 38.8 | 8.0% | 1.1% | 75 | 6 | Emerging |
| 34 | Too Faced | #29 | ↓5 | 36.4 | 8.0% | 1.1% | 75 | 6 | Emerging |
| 35 | First Aid Beauty | #38 | ↑3 | 35.5 | 6.7% | 0.9% | 75 | 5 | Emerging |
| 36 | Rhode | #46 | ↑10 | 37.6 | 6.7% | 0.9% | 75 | 5 | Emerging |
| 37 | OSEA | #47 | ↑10 | 37.6 | 6.7% | 0.9% | 75 | 5 | Emerging |
| 38 | Glossier | #40 | ↑2 | 35.2 | 6.7% | 0.9% | 75 | 5 | Emerging |
| 39 | Glow Recipe | #37 | ↓2 | 34.0 | 6.7% | 0.9% | 75 | 5 | Developing |
| 40 | Color WOW | #50 | ↑10 | 37.6 | 6.7% | 0.9% | 75 | 5 | Developing |
| 41 | Tatcha | #28 | ↓13 | 27.3 | 5.3% | 0.7% | 75 | 4 | Developing |
| 42 | Native | #58 | ↑16 | 36.0 | 5.3% | 0.7% | 75 | 4 | Developing |
| 43 | Benefit Cosmetics | #49 | ↑6 | 33.0 | 5.3% | 0.7% | 75 | 4 | Developing |
| 44 | Drunk Elephant | #48 | ↑4 | 32.4 | 5.3% | 0.7% | 75 | 4 | Developing |
| 45 | HAUS Labs | #41 | ↓4 | 30.0 | 5.3% | 0.7% | 75 | 4 | Developing |
| 46 | Laura Mercier | #35 | ↓11 | 27.9 | 5.3% | 0.7% | 75 | 4 | Developing |
| 47 | LANEIGE | #44 | ↓3 | 30.3 | 5.3% | 0.7% | 75 | 4 | Developing |
| 48 | Summer Fridays | #52 | ↑4 | 32.4 | 5.3% | 0.7% | 75 | 4 | Developing |
| 49 | OLAY | #39 | ↓10 | 25.0 | 4.0% | 0.5% | 75 | 3 | Developing |
| 50 | Supergoop | #42 | ↓8 | 25.6 | 4.0% | 0.5% | 75 | 3 | Developing |
| 51 | Jones Road | #53 | ↑2 | 26.0 | 2.7% | 0.4% | 75 | 2 | Developing |
| 52 | Aesop | #57 | ↑5 | 26.9 | 2.7% | 0.4% | 75 | 2 | Developing |
| 53 | Sol de Janeiro | #60 | ↑7 | 27.5 | 2.7% | 0.4% | 75 | 2 | Developing |
| 54 | Revlon | #56 | ↑2 | 26.0 | 2.7% | 0.4% | 75 | 2 | Developing |
| 55 | Prose | #32 | ↓23 | 18.5 | 2.7% | 0.4% | 75 | 2 | Developing |
| 56 | LUSH | #51 | ↓5 | 23.9 | 2.7% | 0.4% | 75 | 2 | Developing |
| 57 | Thrive Causemetics | #59 | ↑2 | 22.6 | 1.3% | 0.2% | 75 | 1 | Developing |
| 58 | Function of Beauty | #33 | ↓25 | 14.5 | 1.3% | 0.2% | 75 | 1 | Developing |
| 59 | Primally Pure | #55 | ↓4 | 20.8 | 1.3% | 0.2% | 75 | 1 | Developing |
Takeaway: A highly concentrated SOV chart signals that the top brand has compounding citation authority — the kind that gets harder to displace with every additional month of visibility.
Takeaway: High citation volume paired with high prompt reach is the strongest AI visibility signal — it shows both depth and breadth of AI recommendation.
Third-party editorial coverage is the primary signal AI models use when deciding which brands to cite. In the Beauty category, 96% of all AI citations trace back to earned sources — press coverage, industry publications, and reference sites.
Top-tier = broad national outlets with high editorial authority. Niche = category-specific Beauty publications. Together, these two layers determine citation reach and category authority.
Among earned citations, Editorial dominates at 96.4%: trade press, industry blogs, and third-party media coverage. This is the primary signal AI models use to evaluate brand authority. Direct Recommendation (3.6%) account for the remainder. Brands with citations across multiple types have the most durable AI visibility profiles.
| allure.com | 148 citations |
| vogue.com | 126 citations |
| homewisereview.com | 69 citations |
| forbes.com | 37 citations |
| glamour.com | 36 citations |
| theguardian.com | 35 citations |
| qogita.com | 19 citations |
| nontoxiclab.com | 18 citations |
22 citations (4.0% of total) reference brand-owned content. This section examines where content citations originate, which owned formats perform, and which community sources AI models draw from when evaluating brands in this space.
What this shows: The breakdown of AI citations by source type — editorial media, reference sites, user-generated content, and brand-owned pages. This reveals which content categories AI models trust most when recommending brands in this category.
Takeaway: Earned media is the dominant citation source. Brands that want to improve AI visibility must invest in third-party coverage — owned content alone does not move the needle for trust-based queries.
What this shows: AI most often cites content formats that help consumers compare options and make decisions. Listicles, comparison pages, articles, and product pages typically lead, while homepage and utility-style content play a much smaller role in shaping AI visibility.
Takeaway: AI is most likely to cite content that simplifies choice. Decision-oriented formats — listicles, comparisons, and product roundups — outperform traditional brand pages because they help consumers assess options, understand tradeoffs, and make decisions faster.
What this shows: The user-generated content platforms — Reddit threads, review sites, and community forums — that AI models cite when consumers ask about brand trust, value, and product quality. UGC is an underutilized citation signal that reflects real consumer sentiment at scale.
Takeaway: Reddit is the dominant conversation platform in this category, making it a critical environment for reputation, recommendations, and peer-validation signals. AI does not just cite official brand sources when answering trust questions — it surfaces what real users say in community environments.
Technical optimization should be treated as foundational infrastructure, not the sole explanation for category leadership. It does not create authority by itself, but it helps AI systems reliably identify, interpret, and reuse the authority a brand has already earned.
Citation position is consistent across brands in this dataset — the majority are cited in the first position when they appear. AI visibility in this category is primarily driven by breadth of citation across prompts, not by positional ranking within individual responses.
- Schema markup (Organization, Product, FAQ)
- Entity clarity and knowledge panel completeness
- Crawlability and indexability
- Page structure and answer formatting
- Page performance
- Third-party entity consistency across knowledge bases
What It Takes to Win AI Visibility in Beauty
The brands gaining ground in this category are not winning through one tactic. They are building AI visibility through an integrated system: earned authority, decision-ready content, technical readiness, and continuous measurement. The recommendations below translate the report’s findings into the core workstreams that matter most for brands trying to move from low visibility to durable category presence.
The brands most likely to win in this category will be the ones that treat AI visibility as a cross-functional discipline. PR builds authority. Content translates that authority into reusable answers. Technical optimization makes those signals easier for AI systems to interpret. Measurement keeps the whole system moving. That is the operating model this category now rewards.
Metrics, Terms & Definitions
Definitions for all metrics and scores used in this report.
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