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AI Visibility (GEO)

AI Visibility Report for Cosmetic Brands — September 2026

We measured how the four major AI engines answer cosmetics sector queries across 13 rounds: 97 valid query-answer pairs, 3 different cosmetics queries. The results show what actually works for the AI visibility of cosmetic brands and their agencies.

The AI Visibility Report for Cosmetic Brands is a data study that tracked, over 13 weeks, how ChatGPT, Gemini, Claude and Perplexity answer agency and service queries aimed at the cosmetics sector. It is the first AI visibility measurement published specifically for the cosmetics vertical in Turkey.

Three findings stand out:

  • 79% of the answers that cited sources in cosmetics queries included at least one directory or listicle page — noticeably higher than in the education vertical (71%).
  • 100% of those same answers also relied on at least one agency or brand site; the two layers work together.
  • The sites of e-commerce platform providers (such as Ticimax) show up as sources in cosmetics queries — a behavior not seen in the education vertical.

Methodology

Measurement periodJuly 31 – September 21, 2026 · 13 weekly rounds
EnginesChatGPT (GPT-4o, web search enabled) · Gemini 2.5 Flash · Claude (Haiku 4.5) · Perplexity (Sonar)
Queries3 cosmetics queries: an agency for a cosmetics brand, an agency to improve ROAS in cosmetics e-commerce, and moving from contract manufacturing to one's own brand
Data volume108 query-answer pairs; 11 runs that returned technical errors were excluded, leaving 97 valid answers for evaluation
Source countingSearch redirects and the engines' own infrastructure links were excluded from the count

Finding 1 — In Cosmetics, the Directory Layer Carries More Weight

Of the 61 answers that cited sources in cosmetics queries, 48 (79%) relied on at least one agency directory or listicle page. In the education vertical that figure was 71%. The gap may look small, but it points in a clear direction: in cosmetics, “best cosmetics agencies” style list content plays a more decisive role in the engines' answers.

The likely reason is on the supply side: cosmetics is one of the verticals agencies produce the most content for, and a large number of list articles circulate in this space. Where multiple sources repeat the same name, the engine pushes that name forward.

Finding 2 — The Most-Cited Sources in Cosmetics Queries

RankSourceCitationsType
1techdatareklam.com61Agency site / list content
2survivor.com.tr50Agency site
3edvido.com37Agency directory
4smartkid.agency36Agency site (the agency publishing this report)
5pazarlamaturkiye.com35Industry press
6vayes.com.tr34Agency site
7kozmetikajans.com27Sector-specific agency site
8agencies.semrush.com20Agency directory (global)
9uhealth.com.tr19Industry site
10ticimax.com16E-commerce platform provider

Transparency note: The site of the agency that ran this measurement sits fourth on the list. Competing agencies' sites rank above ours and we are publishing that exactly as it is — the value of the report is not in who is ahead, but in showing what the engines read.

Finding 3 — Engine Behaviors

EngineAvg. sources/answerBehavior in the cosmetics vertical
Perplexity16.9The engine with the highest source density; uses an agency's industry page and list content side by side.
Claude10.3Works directory-first; frequently shows sources such as edvido and the industry press.
ChatGPT2.2Behaves selectively; uses Google Maps data for local queries.
Gemini0Shares no source links; visibility is measured only by whether the brand name appears in the answer text.

What Does This Mean for Cosmetic Brands?

  • Directory presence is more critical in cosmetics. Appearing in sector directories and list content is the fastest route into the answer in this vertical.
  • It does not work without your own content. Every answer that cited sources contained a brand or agency site; a directory gets you onto the list, your content keeps you in the answer.
  • Platform providers are sources too. The content pages of e-commerce platforms are cited in cosmetics queries, which is why partner programs carry visibility value.

The Takeaway for Agencies

In the cosmetics vertical, two layers have to be built together: your own content dedicated to the sector (with sub-segments such as dermocosmetics, cosmetics e-commerce and contract manufacturing treated separately) and a visible presence in the directories the engines read. Neglecting either one means getting into the answer without being able to hold your place.

For the methodology and broader findings, see the Turkey AI Visibility Report; for our approach on the cosmetics side, see our cosmetics e-commerce and dermocosmetics pages.

Frequently Asked Questions

Which sources does AI read in cosmetics queries?

In our measurement, 79% of the answers that cited sources included at least one directory or listicle page, and 100% included at least one agency or brand site. The most-cited sources include agency sites, directories such as edvido, the industry press and e-commerce platform providers.

What does it take for my cosmetics brand to appear in AI answers?

Two layers: your own content dedicated to the sector and your product category, plus a visible presence in the directory and list content the engines read. In cosmetics, the directory layer is more decisive than in other sectors.

Why is the directory share higher in cosmetics than in education?

Cosmetics is one of the verticals agencies produce the most list content for; “best cosmetics agencies” style pages circulate in abundance. Engines tend to push a name forward where multiple independent sources repeat it.

Which engine cites the most sources in cosmetics queries?

Perplexity leads with an average of 16.9 sources per answer; Claude is second at 10.3. ChatGPT behaves selectively at 2.2 sources, and Gemini shares no source links.

How was this measurement carried out?

Weekly, between July 31 and September 21, 2026, by asking the same three cosmetics queries to four engines. A total of 108 query-answer pairs were recorded; 11 runs that returned technical errors were left out of the evaluation. The measurement is run on infrastructure Smartkid built in-house and continues on a weekly basis.

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