Clean color cosmetics brand

A 33% share of voice made a clean cosmetics brand the most-cited name in AI answers for its category

A clean color cosmetics brand became the most-cited name in its category across AI answer engines, with a 33.28% share of voice, while AI-driven revenue rose 56% and AI search sessions 52%, April 2026 vs April 2025.

Published October 2026 · Results for April 2026 vs April 2025

Services: GEO, SEO, Technical SEO, Content
Worked with: Managed Service
Focus channel: AI answer engines

The results

AI share of voice in category: #1; About a third of category mentions, ahead of ILIA Beauty and L'Oréal.
AI-driven revenue: +56%; Year over year. Revenue attributed to traffic from AI search.
AI search sessions: +52%; Year over year, converting into 295 purchases in April alone.
Branded search impressions: +68%; Year over year, as discovery in AI answers fed searches for the brand name.

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About the client

A clean color cosmetics brand built on certified-organic, named-ingredient formulas. Its hero products are formulated around a short list of natural ingredients, and that ingredient story, specified down to each component, is what sets it apart in clean beauty.

The brand's authority was real. What it lacked was visibility in the new front door of discovery: the AI answer engines and AI-summarized communities where buyers now ask which clean makeup to trust. A year earlier, that channel was not measured at all.

The challenge

Discovery moved into AI answers

Shoppers stopped scrolling and started asking. Queries like 'best toxin-free makeup' and 'clean skincare' are now answered by ChatGPT, Copilot, Gemini and Reddit's AI, and those answers were being written without the brand.

A clean story the machines couldn't read

The brand had the most specific ingredient story in the category, but AI engines cite structured, extractable content. Its authority simply wasn't in a format the engines could quote.

No share-of-voice measurement

There was no measure of how often the brand appeared in AI answers against ILIA or L'Oréal. Without that data, the channel could not be defended, grown or even seen.

What we did

Structure the content, build a citation moat around the ingredients, seed the community sources AI engines read, and track the share.

Structure
Blog visibility +79%
Rebuilt key blog and product pages with FAQ schema and clear H2/H3 answers, the extractable format AI engines and People Also Ask boxes pull from when writing a response. Blog visibility rose 79% year over year. Pages became eligible for AI Overview and People Also Ask citation.
Cite
100 verified AI citations
Deepened ingredient content so AI engines quote the brand word for word, naming each certified-organic component. The work earned 100 verified AI citations across 27 pages, and two hero products alone hold 37 of them. One of them alone earns 19.
Seed
9 cited Reddit threads
Placed ingredient-led, non-promotional contributions in nine Reddit threads AI engines cite for clean and toxin-free makeup. Those community sources sit behind the answers, so the brand now surfaces in Reddit-sourced AI answers for toxin-free makeup and clean skincare.
Track
5 platforms tracked
Stood up AI visibility tracking across five platforms: OpenAI, Google, Copilot, Perplexity and Claude. AI search went from a blind spot to a managed, measured channel, with the brand now appearing across 25 winning clean-beauty queries. Combined mention volume across those queries reached 8,935.

The outcome

AI search is now a managed revenue channel. The brand is the most-cited clean beauty name across AI answer engines, AI-referred visits engage at a 74.5% rate, and its share of voice is tracked and defended every reporting cycle.

Why it worked

AI engines cite what they can extract and verify. Structure made the brand citable, the named-ingredient detail made the citations stick, and seeding the community threads the engines already trust fed the answers; measuring share of voice turned that position into a channel the brand can manage.