eCommerce: Beauty
Across 60 brands, 565 AI citations, the leaders in this category are separating through trusted third-party visibility, not owned publishing alone. La Roche-Posay currently leads with 6.0% share of voice and appears in 16.0% 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 2026.
The prompt set was structured around three core category terms consumers use when researching this space: Cosmetics, Hair Care, and Skin Care.
- “Best brow products for creating fuller, natural-looking brows that actually last”
- “Top-rated concealers that beauty editors swear by for dark circles and blemishes”
- “Best lightweight conditioners for fine hair that needs moisture without losing volume”
- “Top hair care brands with refillable or zero-waste packaging options”
- “Eye creams beauty experts recommend for reducing puffiness and dark circles”
- “What are the best facial sunscreens for daily use under makeup?”
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: First Page Sage, May 2026
What This Means: Claude has emerged as the fastest-growing AI chatbot, while ChatGPT’s growth has slowed significantly. In January 2025, ChatGPT held just under 75% of the market and Claude barely topped 3%, but that gap is now starting to narrow.
Source: First Page Sage, May 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.
Text chat like ChatGPT and Claude is the dominant surface and clearest direct visibility opportunity. Users ask open-ended comparison questions and receive ranked or recommended brand answers.
AI-augmented search like Bing Copilot and Google AI Overview blends model-generated answers with linked web sources, making brand authority and source presence work together.
Voice and mobile assistants like Siri and Alexa compress choice even further, often surfacing a single answer or a very short list of options.
Agentic experiences remain early, but they point toward a future where AI systems compare, filter, and recommend financial products on a user's behalf.
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.
Brands are ranked by Avenue Z’s proprietary Z-Score, a weighted measure of AI visibility strength that combines presence, competitive share, perception, citation support, and year-over-year momentum.
Visibility is relatively distributed. The top 5 brands hold 24.0% of AI citations.
What This Means: The leading brands are not only mentioned most often, they are cited most often, giving them outsized influence over the stories AI tells about this category.
| Rank | Brand | 2025 Rank ⓘ | Δ ⓘ | Z-Score ⓘ | AI Visibility ⓘ | SOV ⓘ | Sentiment ⓘ | Citations ⓘ | Tier |
|---|---|---|---|---|---|---|---|---|---|
| 1 | #2 | ↑1 | 86.8 | 16.0% | 6.0% | 60 | 22 | Leader | |
| 2 | #1 | ↓1 | 81.2 | 16.0% | 5.0% | 60 | 22 | Leader | |
| 3 | #7 | ↑4 | 71.7 | 11.0% | 5.0% | 58 | 19 | Leader | |
| 4 | #16 | ↑12 | 69.7 | 11.0% | 4.0% | 59 | 20 | Leader | |
| 5 | #19 | ↑14 | 67.6 | 10.0% | 4.0% | 64 | 18 | Leader | |
| 6 | #21 | ↑15 | 60.9 | 9.0% | 3.0% | 63 | 20 | Leader | |
| 7 | #9 | ↑2 | 59.9 | 9.0% | 4.0% | 60 | 15 | Leader | |
| 8 | #5 | ↓3 | 59.3 | 10.0% | 3.0% | 63 | 19 | Leader | |
| 9 | #8 | ↓1 | 58.9 | 10.0% | 3.0% | 62 | 17 | Leader | |
| 10 | #6 | ↓4 | 58.1 | 10.0% | 3.0% | 71 | 15 | Challenger | |
| 11 | NYX | #24 | ↑13 | 58.0 | 8.0% | 3.0% | 66 | 16 | Challenger |
| 12 | Briogeo | #15 | ↑3 | 57.9 | 9.0% | 3.0% | 63 | 16 | Challenger |
| 13 | Neutrogena | #25 | ↑12 | 54.2 | 8.0% | 2.0% | 61 | 19 | Challenger |
| 14 | K18 | #30 | ↑16 | 52.3 | 6.0% | 3.0% | 53 | 16 | Challenger |
| 15 | Rare Beauty | #11 | ↓4 | 52.3 | 8.0% | 3.0% | 67 | 13 | Challenger |
| 16 | Charlotte Tilbury | #3 | ↓13 | 50.6 | 8.0% | 3.0% | 67 | 14 | Challenger |
| 17 | Fenty Beauty | #14 | ↓3 | 46.7 | 7.0% | 2.0% | 68 | 15 | Challenger |
| 18 | MAC | #26 | ↑8 | 46.4 | 6.0% | 2.0% | 73 | 12 | Challenger |
| 19 | Kérastase | #10 | ↓9 | 45.7 | 7.0% | 2.0% | 61 | 17 | Challenger |
| 20 | Oribe | #23 | ↑3 | 45.6 | 6.0% | 2.0% | 70 | 12 | Challenger |
| 21 | Pureology | #22 | ↑1 | 44.2 | 5.0% | 3.0% | 62 | 8 | Challenger |
| 22 | Maybelline | #4 | ↓18 | 43.0 | 7.0% | 2.0% | 68 | 14 | Emerging |
| 23 | Verb | #54 | ↑31 | 41.0 | 4.0% | 1.0% | 62 | 10 | Emerging |
| 24 | e.l.f. Cosmetics | #18 | ↓6 | 39.1 | 6.0% | 1.0% | 69 | 13 | Emerging |
| 25 | Color WOW | #50 | ↑25 | 38.9 | 4.0% | 1.0% | 67 | 5 | Emerging |
| 26 | L'Oréal | #13 | ↓13 | 38.0 | 5.0% | 1.0% | 68 | 21 | Emerging |
| 27 | Urban Decay | #12 | ↓15 | 37.2 | 6.0% | 2.0% | 54 | 8 | Emerging |
| 28 | LANEIGE | #44 | ↑16 | 36.1 | 4.0% | 1.0% | 65 | 4 | Emerging |
| 29 | Rhode | #46 | ↑17 | 34.8 | 3.0% | 1.0% | 66 | 5 | Emerging |
| 30 | Huda Beauty | #34 | ↑4 | 34.3 | 4.0% | 1.0% | 58 | 7 | Emerging |
| 31 | Estée Lauder | #27 | ↓4 | 34.0 | 4.0% | 1.0% | 60 | 11 | Emerging |
| 32 | Hourglass | #31 | ↓1 | 33.3 | 3.0% | 1.0% | 68 | 13 | Emerging |
| 33 | Supergoop | #42 | ↑9 | 33.0 | 3.0% | 1.0% | 70 | 3 | Emerging |
| 34 | IT Cosmetics | #45 | ↑11 | 31.3 | 2.0% | 1.0% | 65 | 7 | Emerging |
| 35 | Laura Mercier | #35 | – | 29.8 | 3.0% | 1.0% | 67 | 5 | Emerging |
| 36 | First Aid Beauty | #38 | ↑2 | 29.7 | 3.0% | 1.0% | 58 | 5 | Emerging |
| 37 | ColourPop | #36 | ↓1 | 28.1 | 2.0% | 1.0% | 67 | 6 | Emerging |
| 38 | HAUS Labs | #41 | ↑3 | 27.2 | 2.0% | 1.0% | 65 | 4 | Emerging |
| 39 | OLAY | #39 | – | 27.1 | 2.0% | 1.0% | 64 | 4 | Emerging |
| 40 | SkinCeuticals | #17 | ↓23 | 26.7 | 3.0% | 1.0% | 62 | 9 | Developing |
| 41 | Tarte | #20 | ↓21 | 25.7 | 3.0% | 1.0% | 59 | 7 | Developing |
| 42 | OSEA | #47 | ↑5 | 25.6 | 1.0% | 1.0% | 62 | 5 | Developing |
| 43 | Too Faced | #29 | ↓14 | 24.8 | 2.0% | 1.0% | 58 | 7 | Developing |
| 44 | Tatcha | #28 | ↓16 | 23.9 | 2.0% | 1.0% | 64 | 5 | Developing |
| 45 | Native | #58 | ↑13 | 23.9 | 1.0% | 0.0% | 61 | 4 | Developing |
| 46 | Sol de Janeiro | #60 | ↑14 | 22.6 | 1.0% | 0.0% | 64 | 2 | Developing |
| 47 | Glow Recipe | #37 | ↓10 | 22.5 | 1.0% | 1.0% | 63 | 5 | Developing |
| 48 | Benefit Cosmetics | #49 | ↑1 | 22.0 | 1.0% | 0.0% | 74 | 4 | Developing |
| 49 | Prose | #32 | ↓17 | 21.3 | 1.0% | 1.0% | 64 | 2 | Developing |
| 50 | Function of Beauty | #33 | ↓17 | 20.7 | 1.0% | 1.0% | 67 | 1 | Developing |
| 51 | Summer Fridays | #52 | ↑1 | 20.5 | 1.0% | 0.0% | 64 | 4 | Developing |
| 52 | Primally Pure | #55 | ↑3 | 20.0 | 1.0% | 0.0% | 62 | 1 | Developing |
| 53 | Glossier | #40 | ↓13 | 19.7 | 1.0% | 0.0% | 64 | 5 | Developing |
| 54 | Jones Road | #53 | ↓1 | 18.6 | 0.0% | 0.0% | 76 | 2 | Developing |
| 55 | Aesop | #57 | ↑2 | 18.5 | 0.0% | 0.0% | 65 | 2 | Developing |
| 56 | Drunk Elephant | #48 | ↓8 | 17.6 | 1.0% | 0.0% | 55 | 4 | Developing |
| 57 | Revlon | #56 | ↓1 | 17.6 | 0.0% | 0.0% | 56 | 3 | Developing |
| 58 | Thrive Causemetics | #59 | ↑1 | 17.6 | 0.0% | 0.0% | 64 | 1 | Developing |
| 59 | LUSH | #51 | ↓8 | 14.9 | 0.0% | 0.0% | 57 | 2 | Developing |
| 60 | Clarins | #43 | ↓17 | 9.9 | 0.0% | 0.0% | — | 0 | 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 63.2%: trade press, industry blogs, and third-party media coverage. This is the primary signal AI models use to evaluate brand authority. Corporate (26.0%) and UGC (5.5%) and Reference (4.2%) and Competitor (1.1%) account for the remainder. Brands with citations across multiple types have the most durable AI visibility profiles.
| allure.com | 154 citations |
| glamour.com | 81 citations |
| vogue.com | 76 citations |
| goodhousekeeping.com | 42 citations |
| forbes.com | 37 citations |
| theguardian.com | 35 citations |
| homewisereview.com | 33 citations |
| qogita.com | 19 citations |
22 citations (3.9% 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.
What This Means: Competitor websites and UGC account for a smaller share of total citations, but they represent some of the most actionable visibility opportunities in the category. These are the places where brands can influence how they are compared, discussed, and validated beyond traditional editorial coverage.
What this shows: AI most often cites content formats that help consumers compare options and make decisions. Listicles lead by a wide margin, followed by comparison pages, articles, and product pages, while homepage and utility-style content play a much smaller role in shaping AI visibility.
What This Means: AI is most likely to cite content that simplifies choice. Listicles and comparison pages 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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