How Beauty Brands Get Discovered in ChatGPT, Perplexity, and Google AI Mode

More shoppers are beginning product research by asking AI, not just searching Google. Here is what influences whether your brand shows up in the answer, and what you can do about it.

38%
Of Beauty Shoppers Use AI Assistants
57%
Say AI Recommendations Influence What They Buy
7x
Rise in AI-Referred Traffic to Shopify Since 2025

Sources: Criteo Shopper Survey, June 2026; Shopify Agentic Storefronts launch, March 2026.

In short: Beauty shoppers increasingly start product research inside ChatGPT, Perplexity and Google AI Mode. Each engine draws on different signals: ChatGPT leans on Shopify catalog data, Perplexity on cited editorial sources, Google AI Mode on Merchant Center feeds and organic search. Brands improve visibility by completing product attributes, writing concern-led descriptions, publishing content that answers real customer questions, and using quiz data to know which questions those are.

A shopper looking for the best vitamin C serum for sensitive skin used to open Google, click through a few results, and make a decision. In 2026, a growing share of those shoppers are opening ChatGPT or Perplexity instead, getting a synthesized answer with specific brand mentions before they visit any brand website.

This is not a small trend. Criteo's June 2026 shopper survey put a number on it, and Shopify's own referral data points the same way. The brands that show up in those AI answers are getting distribution they did not have to pay for. Brands that do not appear risk missing a fast-growing segment of high-intent shoppers.

This guide explains how each engine works, what signals determine which beauty brands get named, and what Shopify beauty brands can do right now to improve their visibility.

The AI Answer Is the New Shelf

The way shoppers find beauty products is changing faster than most brands have adjusted to. Here is the scale of what has already shifted.

💬
Shoppers are asking AI before they searchQuestions like "best clean shampoo for colour-treated hair" are going to ChatGPT or Perplexity before Google. The AI returns a short list of brands. That answer shapes what the shopper buys, often before they visit any brand website.
🛍️
Shopify brands are already inside ChatGPTShopify introduced Agentic Storefronts in its Winter '26 Edition in December 2025, and the ChatGPT integration went live for eligible stores on 24 March 2026. Product information is syndicated through Shopify Catalog to supported AI channels, as documented in Shopify's own Help Center. The question is not whether you are listed. It is whether your product data is complete enough to show up when someone asks.
📊
The brands winning are not the biggest onesIn 5WPR's 2026 US Beauty AI Visibility Index, which tested 80 buyer-intent prompts across ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews in Q1 2026, The Ordinary recorded the highest citation share at 7.0%, ahead of CeraVe at 6.0%, Sephora at 5.5%, La Roche-Posay at 5.0% and Charlotte Tilbury at 4.5%. Legacy prestige brands like Estée Lauder and Lancôme ranked well below their commercial scale, with none in the top 10 for skincare ingredient prompts. Ingredient-led independents earned 31% of all beauty citations while legacy mass brands earned 4%.
Each engine works differentlyEach engine pulls from different sources. Charlotte Tilbury is the only brand in the top 5 on both Perplexity and Google AI Overviews. A brand that performs strongly on one engine may still have limited visibility across the others.

How Each Engine Works for Beauty Discovery

Each AI engine has a different discovery mechanism. While the exact ranking systems are not fully public, each platform appears to place different emphasis on catalogue data, web content, and source authority. Knowing which signals matter where is the difference between showing up and being invisible.

ChatGPT

ChatGPT

Powered by Shopify Agentic Storefronts for product-level discovery. When a shopper asks a shopping intent question, ChatGPT searches Shopify's catalog database, which categorises and enriches product data from millions of merchants using specialised LLMs.

Brands like Glossier and Fenty Beauty are among the early partners already selling through it.

Perplexity

Perplexity

Combines a conversational answer with visible source citations. Shoppers see both the recommendation and the links that support it, making citations and mentions a key driver of visibility rather than just product catalog inclusion.

Premium beauty and luxury brands tend to perform well here. Content depth matters more than catalogue data alone.

Google AI Mode

Google AI Mode

Pulls from Google Merchant Center feeds and traditional search signals. If you already run Google Shopping campaigns, your feed is connected. Conversational product descriptions and complete structured data give incremental AI Mode visibility with minimal new infrastructure.

For brands already running Google Shopping, this is likely the lowest-friction AI discovery channel to strengthen.

EngineHow It Finds ProductsPrimary SignalHighest-Leverage Action
ChatGPTShopify Catalog via Agentic StorefrontsProduct attribute completenessFill in skin type, hair type, concern and ingredient fields on every product
PerplexityLive web search with visible citationsEditorial mentions and source authorityEarn coverage in beauty publications and review sites
Google AI ModeMerchant Center feed plus organic search signalsFeed quality and schema markupTighten your product feed and add structured data to product pages

5 Things Shopify Beauty Brands Can Do Right Now

You do not need a six-month project to improve your AI visibility. These are the highest-leverage actions available to a Shopify beauty brand today.

🧾
Audit and complete your product attributesAdd skin type, hair type, concern, key ingredients and finish to every product. Complete attributes match more queries. Thin data matches fewer. This is one of the clearest actions brands can take to improve how accurately AI engines read their catalog.
✍️
Rewrite product descriptions in concern-led languageShoppers ask for the best serum for redness-prone sensitive skin, not the best serum. Write descriptions using the exact language of the problem, not just the ingredients. Concern-led copy aligns more closely with how shoppers phrase questions in AI search than traditional marketing copy.
📚
Build content that directly answers beauty questionsRoutine guides for dry sensitive skin, ingredient education pages and concern explainers give AI engines something to cite. Specific, well-structured content performs better than generic brand content.
🔍
Use your quiz data to learn how customers describe themselvesQuiz responses give you the concerns and terminology shoppers use in their own words. Brands using Tangent AI can see the most common concerns, ingredient preferences and gaps across their customer base. See how to collect zero-party data on Shopify.
Build your review footprint consistentlyEncourage detailed reviews that mention concerns, product use and outcomes. These give AI engines and shoppers more useful context than generic star ratings alone.

A Practical AI Visibility Workflow

The changes above only compound if you run them in the right order and measure the result. This is the sequence.

1
Baseline where you currently appearWrite down 20 buyer-intent prompts your customers would actually type. Run them across ChatGPT, Perplexity and Google AI Mode and record which brands get named. That is your starting position.
2
Measure your attribute coverageExport your Shopify catalog and calculate what percentage of products have every required field filled. Track that number. Gaps here limit every engine at once.
3
Fix the catalog before the contentCatalog work comes first because it feeds ChatGPT and Google AI Mode at the same time. Content work compounds on top of it, not the other way around.
4
Rank your customer concerns by volumeSort quiz completions by concern frequency. That ranking is your content priority order, decided by data rather than by guesswork.
5
Work down that list, not across itPublish one thorough page per concern, starting at the top. Depth on a few concerns beats thin coverage across many.
6
Re-run your prompt set every quarterAI answers shift as engines update. Running the same 20 prompts every quarter shows whether your visibility is improving and which engine still needs work.

Why First-Party Data Is Your AI Discovery Advantage

The brands winning in AI search have something in common: they know exactly what their customers need, and their content reflects it precisely.

Every Tangent quiz completion tells you the customer's skin type, concerns, ingredient preferences and routine goals. That data powers Klaviyo flows and recommendations, but it also reveals the concerns and terminology customers are likely to use when researching products through AI assistants.

A brand that knows 38% of its quiz completers report redness can build content specifically around that concern. Those pages match AI queries more precisely than generic copy. The quiz is not just a personalization tool. It is market intelligence that feeds every channel, including AI search. See how quiz data connects to Klaviyo flows.

AI discovery rewards brands that have done the work: clear answers, specific attributes, and real customer data. That starts with knowing your customer. Knowing your customer starts with asking them.

The Data Layer These Brands Built First

These results come from personalization, not from AI search rankings. They are here because the same asset drives both: a structured, current picture of what each customer needs and how they describe it.

Skincare

Three Ships Beauty

Quiz-captured skin type and concern data used to power personalized routine recommendations and Klaviyo flows from day one.

+208%
AOV increase from quiz-referred purchases
Read case study →
Skincare

Luzern Labs

AI skin analysis and zero-party profile data connected to personalized lifecycle flows, turning one-time buyers into repeat customers.

2.5x
Revenue growth with AI skin analysis and routines
Read case study →
Haircare

Bondi Boost

Hair profile data from AI selfie analysis and quiz synced to Klaviyo, powering post-quiz flows across US and Australian markets.

74%
Email open rate from quiz-powered flows
Read case study →
Haircare

Moroccanoil

Zero-party hair profile data collected across 8 European markets from a single quiz, powering localized flows and segment-targeted campaigns per market.

85%
First-time orders from quiz-referred purchases
Read case study →

Source: Tangent AI customer data.

Questions We Get Asked a Lot

Shopify introduced Agentic Storefronts in late 2025 and expanded ChatGPT commerce capabilities in March 2026. Merchants can syndicate product information through Shopify Catalog to supported AI channels. Showing up well generally requires complete product attributes and a content footprint AI engines can draw from.

GEO stands for Generative Engine Optimization. It is structuring your content, product data and brand signals so AI engines cite your brand when shoppers ask beauty questions.

Criteo's June 2026 shopper survey found 38% of shoppers globally already use AI assistants when shopping for beauty and personal care. Among them, 57% say AI-recommended products influence what they buy.

In 5WPR's 2026 US Beauty AI Visibility Index, The Ordinary led at 7.0% citation share, followed by CeraVe (6.0%), Sephora (5.5%), La Roche-Posay (5.0%) and Charlotte Tilbury (4.5%). Rankings vary by prompt set, timing and engine, so treat them as directional.

Indirectly, yes. Quiz data tells you the exact words customers use to describe their concerns. That language feeds better attributes, descriptions and content, which are the signals AI engines read.

Perplexity shows visible source citations, so editorial mentions and backlinks drive visibility. ChatGPT's Shopify integration draws directly on Shopify Catalog, making complete and accurate product attributes especially important.

Start with knowing your customer

Turn Customer Questions Into
Better Product Discovery

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  • Capture rich zero-party customer data
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