How to Rank in AI Search: A Strategic Guide for CMOs: skincare, fashion and e-commerce
The future of SEO isn’t about page one — it’s about being chosen by AI.
When a shopper asks ChatGPT, “What’s the best clean serum under $60?” or “Where can I find a sustainable capsule wardrobe?” — will your brand show up in the answer?
We just published a new guide on how to rank in AI search, including:
✅ The new rules of Answer Engine Optimization (AEO)
✅ How to structure your product data for AI visibility
✅ Real examples of beauty & fashion brands mastering discovery on ChatGPT
✅ A roadmap for integrating agentic commerce — where AI doesn’t just recommend your product, it helps customers buy it
The future of ecommerce isn’t about being found on Google—it’s about being chosen by AI.
If you’re a CMO or VP of Marketing for a beauty, fashion, or ecommerce brand, you’re already seeing the shift: consumers are discovering, evaluating, and even purchasing products through AI-powered search and conversational engines like ChatGPT, Perplexity, and Gemini.
Your next growth frontier isn’t SEO as you know it—it’s AEO (Answer Engine Optimization), agentic commerce, and ranking in AI search.
Why AI Search Is Transforming Beauty, Fashion & Ecommerce
Traditional search rewarded backlinks and keywords. But AI search engines—like ChatGPT and Perplexity—reward contextual authority, structured data, and brand trust.
A recent McKinsey & Company report calls AI search “the new front door to the internet,” noting that over 50% of consumers now use conversational AI tools to inform purchase decisions in categories like fashion and beauty.
Vogue Business reports that beauty brands like Estée Lauder and Sephora are already piloting AI-driven discovery and recommendation flows to boost visibility across conversational agents.
Retail Dive highlights that generative AI is changing ecommerce traffic patterns—consumers are no longer browsing endless SERPs; they’re getting one smart answer.
In other words, you’re either in the answer, or you’re invisible.
What It Means to “Rank” in AI Search
To rank in AI search is to be featured, recommended, or linked within an AI-generated answer—when a user asks:
“What’s the best clean beauty brand for sensitive skin?”
“Where can I find a minimalist black dress under $200?”
If the AI agent mentions your brand, product, or content—you’ve ranked.
If not, your competitors will capture that intent—and the conversion.
That’s why leading brands are investing in AEO and agentic commerce to ensure their products appear in these AI-driven answers and recommendation flows.
The New Playbook: How to Rank in AI Search
1. Structure Your Product Data for AI
Your product feed is your brand’s new SEO. AI agents rely on machine-readable data to understand what your product is, who it’s for, and why it matters.
Action steps:
Use JSON-LD schema for all product pages (include: brand, price, availability, benefits, ingredients/materials).
Include descriptive attributes (e.g., “vegan hyaluronic acid serum” or “organic linen summer blazer”).
Keep feeds fresh—AI engines penalize outdated data.
Ensure your robots.txt and metadata allow AI crawlers like OpenAI’s Product Discovery program to access product info.
🧠 Pro tip: Treat your product catalog like an API for discovery—not just a website.
2. Create AI-Readable, Contextual Content
AI search engines surface content that answers real questions, not keyword-stuffed landing pages.
For beauty and fashion brands, this means creating AEO-optimized content such as:
“How to layer retinol and vitamin C safely.”
“5 wardrobe essentials for a sustainable capsule closet.”
“The best foundation shades for olive undertones.”
Best practices:
Start content briefs with an AI-style query (“What’s the best X for Y?”).
Use structured formatting: clear headings, bullet lists, FAQs, and comparison tables.
Cite credible sources (dermatologists, stylists, fashion editors). AI search values referenced expertise.
Connect content directly to your product feed—so answers drive commerce.
📈 AEO mindset: Write for questions, not keywords.
3. Build Authority Beyond Your Site
AI search models prioritize trusted, cross-referenced data.
If ChatGPT or Perplexity find consistent signals across your website, PR, reviews, and social presence—they’re more likely to recommend your brand.
Tactics to boost authority:
Get coverage in reputable media (Allure, Harper’s Bazaar, Vogue Business).
Encourage verified product reviews and influencer citations.
Create shareable assets (ingredient glossaries, trend reports) that build backlinks and semantic relevance.
💬 Remember: AI doesn’t just read your site—it reads the entire internet about you.
Enter Agentic Commerce: The Next Level of AI-Driven Ecommerce
Agentic commerce is where AI agents don’t just recommend products—they help users buy them.
Think of a world where a consumer tells ChatGPT:
“Order me a refill of my moisturizer from the brand I bought last month.”
Or:
“Find me a vegan leather jacket that matches my style and budget.”
And the agent executes the purchase—not just recommends.
That’s agentic commerce: AI-activated shopping flows that connect discovery → recommendation → transaction.
How ecommerce brands can leverage agentic commerce:
Enable AI integrations: Join AI shopping networks or “agentic commerce protocols” (e.g., through Shopify, Orium, or OpenAI product discovery pilots).
Design AI-friendly APIs: Allow AI agents to fetch product details, availability, and pricing directly from your feed.
Simplify conversion paths: Reduce clicks between recommendation and checkout. AI-driven carts or direct-to-agent APIs make this seamless.
Use conversational commerce tools: Integrate chatbots that mimic agent workflows—so your shoppers can “talk to buy.”
Track AI-source traffic: Tag sessions from AI referrals (e.g.,
utm_source=chatgptorutm_source=perplexity) to measure conversions from AI discovery.
💡 Agentic commerce isn’t futuristic—it’s the next ecommerce channel.
Beauty & Fashion Use Cases
Beauty Example
A skincare brand launches a “hydrating serum for travel.”
Structured data describes it as “lightweight, TSA-friendly, dermatologist-tested.”
Blog post answers: “What skincare products prevent dehydration on long flights?”
The AI search engine recommends the serum, citing the blog.
ChatGPT links directly to the brand’s site.
The user purchases within the chat flow.
Fashion Example
A DTC fashion brand releases a “minimalist capsule collection.”
Structured data emphasizes sustainability, seasonality, and fabric composition.
A style guide explains: “How to build a minimalist wardrobe with 5 versatile pieces.”
Perplexity references it in its AI summary of “best capsule wardrobe brands.”
The brand’s product feed connects to agentic commerce APIs, enabling instant purchase.
Result: AI-driven discovery → Recommendation → Conversion
Metrics That Matter
Forget “page one” rankings—AI search performance is about visibility and conversion within answers.
Track these metrics:
Mentions or citations in AI-generated results
AI referral traffic (from ChatGPT, Perplexity, Gemini)
Product click-through and conversion from AI sources
Share of AI answer voice for key queries (e.g., “best clean foundation”)
Brands that measure these today will dominate tomorrow.
The Takeaway
AI search is the new product shelf.
If you want your beauty, fashion, or ecommerce brand to be discovered and purchased through ChatGPT, Perplexity, and other generative agents, you need to master three things:
Structured, intelligent data
AEO-optimized, authoritative content
Agentic commerce enablement
Your next growth channel isn’t social.
It’s search that talks back.
Ready to future-proof your brand for AI discovery?
Sloane helps beauty, fashion, and ecommerce brands audit, optimize, and activate across AI search ecosystems—ensuring you’re not just seen, but chosen.
