The Ecommerce GEO Playbook: How to Get Your Products Recommended by AI

Technical fixes, content strategy, and a prioritized checklist for getting your ecommerce products recommended by ChatGPT, Perplexity, and Gemini.

Mersel AI Team

December 4, 2025

10 min read

TL;DR

Most ecommerce stores are invisible to AI because they're built for human browsers, not AI crawlers. The fix comes down to four things: server-side rendering, schema markup, AI-citable content, and off-site presence. This post walks through each one with a prioritized checklist at the bottom.

This is Part 2. Part 1 covered the data: 60% of searches end without a click, AI traffic converts at 9x Google organic, and 80% of ChatGPT citations don't rank in Google's top 100. Start there if you haven't.

The question every ecommerce operator should be asking: when a shopper asks ChatGPT, Perplexity, or Gemini to recommend products in your category, does your brand appear?

For most brands, the answer is no. Here's the playbook for fixing that.

Step 1: Fix Your Technical Foundation

Before content or strategy, make sure AI crawlers can actually read your store. Most can't.

Server-Side Rendering (SSR)

If your storefront runs on React, Next.js, Vue, or any client-side JavaScript framework, AI crawlers likely see empty <div> containers instead of your product catalog. Server-side rendering or pre-rendering ensures product data, descriptions, prices, and reviews exist in the raw HTML on first load.

How to check: Right-click any product page and select "View Page Source." If you see your product title, price, description, and reviews in the raw HTML, you're fine. If you see JavaScript and empty containers, AI crawlers see the same nothing.

Schema Markup

Without structured data, AI models can't extract product attributes programmatically. At minimum, implement these:

Schema Type	What It Covers
`Product`	Name, description, SKU, brand, price, availability, images
`AggregateRating`	Star rating, review count
`Review`	Individual reviews with author and date
`Offer`	Price, currency, availability, seller
`FAQPage`	Product Q&A sections
`BreadcrumbList`	Category navigation context

Validate with Google Rich Results Test and Schema.org Validator. Most Shopify themes have partial schema, which means AI gets incomplete data about your products.

llms.txt

This is the AI-era equivalent of robots.txt. Place it at your domain root to guide AI crawlers on what to index:

# llms.txt
User-agent: *
Allow: /products/
Allow: /collections/
Allow: /blog/
Disallow: /checkout/
Disallow: /account/
Sitemap: https://yourdomain.com/sitemap.xml

Make Reviews Crawlable

Your 4.8-star rating with 2,400 reviews is your strongest trust signal. If reviews load via Yotpo, Judge.me, Stamped, or another widget after page render, AI crawlers never see them.

Make sure review content is:

Rendered server-side in the initial HTML, or
Included in your structured data (Review schema), or
Both (ideal)

Step 2: Create AI-Citable Content

AI models recommend brands they can find substantive, structured information about. The content strategy for Generative Engine Optimization (GEO) is fundamentally different from blog SEO.

What AI Models Actually Cite

Based on Ahrefs (2025) and the Prerender.io AI Indexing Benchmark, AI models disproportionately cite content with:

Specific numbers and data points. "Rated UPF 50+" outperforms "great sun protection." AI surfaces specificity over adjectives.
Q&A structure. This mirrors how users query AI platforms. "What's the best running shoe for flat feet?" answered directly with structured reasoning.
Comparison format. Honest pros/cons across multiple products, including competitors. Counterintuitive, but AI trusts balanced content over self-promotion.
Original research. Customer survey results, product testing data, industry benchmarks. First-party data makes you a primary source AI wants to reference.

Content Types That Work

Buying guides in Q&A format. Structure each section around a question shoppers ask AI, then answer it directly with specifics. "How to choose a [product category] for [specific use case]." These become the reference material AI synthesizes into recommendations.

Data-backed comparison pages. Compare your products with competitors on measurable attributes: material composition, lab test results, warranty terms, price per unit. Include honest trade-offs. AI treats balanced comparisons as more authoritative than one-sided marketing.

Original data publications. Customer surveys, product durability tests, industry benchmarks. Publish the methodology and results. AI models heavily cite pages with original, specific statistics. These become primary sources that other content references, creating a citation flywheel.

What Doesn't Work

Keyword-stuffed product descriptions optimized for Googlebot
Generic blog posts with no original data or specific claims
AI-generated content farms (LLMs are increasingly good at detecting and deprioritizing these)
Content that only lives on your own domain with no external validation

Step 3: Build Your Off-Site AI Footprint

Your brand's AI visibility depends heavily on sources AI trusts. Wikipedia, YouTube, and Reddit are among the most-cited domains in Google's AI Mode. Your own website is one input. By itself, it's not enough.

Wikipedia and Wikidata

AI models reference Wikipedia heavily for entity recognition and brand information. If your brand has a Wikipedia presence, make sure it's accurate, current, and well-sourced. If it doesn't, evaluate whether your brand meets notability criteria and contribute factually if so.

AI models, especially ChatGPT, cite Reddit threads frequently. Authentic participation in relevant subreddits creates organic brand mentions that AI surfaces.

Category	Key Subreddits
Beauty / Skincare	r/SkincareAddiction, r/AsianBeauty, r/MakeupAddiction
Fashion	r/MaleFashionAdvice, r/femalefashionadvice
Electronics	r/BuyItForLife, r/audiophile, r/buildapc
Home	r/HomeImprovement, r/InteriorDesign

This cannot be faked. Reddit communities detect and punish astroturfing quickly. The approach is genuine, helpful participation: answering questions, sharing honest product experiences, contributing useful information without a sales pitch.

Third-Party Reviews and Publications

A single genuine review on Wirecutter, Byrdie, CNET, or a respected niche publication carries more AI citation weight than 100 blog posts on your own site. These are the "sources" AI models cite when recommending products.

Pursue editorial coverage through standard channels: send products for review, build relationships with category editors, respond to roundup requests (HARO, Qwoted, Terkel).

YouTube

Video content is relatively insulated from zero-click dynamics. YouTube is the second-largest search engine, and AI models increasingly cite video content. Product reviews, tutorials, unboxings, and comparisons on YouTube create AI-accessible brand mentions that compound over time.

Step 4: Measure What Matters

Traditional SEO tools like Ahrefs, Semrush, and Google Search Console don't track AI visibility. You need different metrics:

Metric	What It Measures	How to Track
AI mention rate	How often your brand appears in AI responses for your category	Manual testing across ChatGPT, Perplexity, Claude, Gemini
AI sentiment accuracy	Whether AI's descriptions of your products are correct	Manual review of AI responses
Citation share	Your brand's percentage of AI mentions vs. competitors	Competitive AI query testing
AI referral traffic	Visitors from AI platforms	Analytics, segmented by referral source (chatgpt.com, perplexity.ai)
AI conversion rate	Purchase rate of AI-referred visitors	Ecommerce analytics with source segmentation

Brands Already Doing This

Kendra Scott added 8,000 new pages specifically optimized for AI search. 5% of annual web traffic now arrives through AI-optimized pages, with 27% of those pages also ranking on Google's first page (Digital Commerce 360).

Batteries Plus actively monitors AI citations and updates Wikipedia, BBB, and Reddit to improve AI mention accuracy. About 1% of referral traffic now comes from AI sources. That's small, but growing and highly engaged (Digital Commerce 360).

Prioritized Checklist

This Week

AI visibility audit. Ask ChatGPT, Perplexity, Claude, and Gemini product recommendation questions in your category. Note whether your brand appears and whether the information is accurate.
View Page Source. Check 3 product pages. Is product data, reviews, and pricing in the raw HTML?
Schema validation. Run top 5 product pages through Rich Results Test. Document what's missing.

This Month

Implement or fix server-side rendering for all product pages
Complete schema markup: Product, Review, Offer, FAQ on all product pages
Add llms.txt to domain root
Create 3 to 5 comparison/guide pages in Q&A format for top product categories
Audit off-site presence. Map brand mentions on Wikipedia, Reddit, YouTube, and review sites. Identify gaps.

Ongoing (Monthly)

Track AI referral traffic, segmented by ChatGPT, Perplexity, Claude, and Gemini in analytics
Publish one piece of original data: customer survey, product benchmark, or category trend report
Build third-party coverage: editorial reviews, influencer content, community participation
AI mention accuracy review: quarterly check across all major AI platforms, correct misinformation

The Window Is Closing

AI search traffic to retail is growing at 4,700% YoY (Adobe). But it still represents a small fraction of total ecommerce traffic. That's the window.

The brands that structure for AI now build compounding advantage. AI models learn which brands to trust and recommend. Once those citation patterns are established, latecomers struggle to break in. It's the same dynamic as Google SEO, where it takes years to outrank an established competitor, except harder because AI models don't show you a ranked list where you can see your position.

The question isn't whether AI search will matter for ecommerce. The data already proves it does. The question is whether your brand will be in the answer.

FAQ

What exactly is GEO? Generative Engine Optimization. The practice of making your brand discoverable and accurately represented in AI-generated answers from ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews. It's the AI-era complement to SEO.

Do I need GEO if my SEO is already strong? Yes. 80% of URLs cited by ChatGPT don't rank in Google's top 100. Strong Google rankings are a weak predictor of AI visibility. The two systems pull from different signals and different sources.

What's the first thing I should do? Start with the technical audit. Ask AI platforms product questions in your category and view your page source. Those two tests, combined with schema validation, tell you within 30 minutes how visible (or invisible) your store is to AI.

How long does it take to see results? Technical fixes (SSR, schema, llms.txt) can show visibility improvements within 2 to 4 weeks. Content and off-site strategies compound over 2 to 6 months. AI models update their knowledge bases on varying schedules, so consistency matters more than speed.

Is this relevant if I'm on Shopify / WooCommerce / custom? Yes. The problems (client-side rendering, incomplete schema, invisible reviews) exist across every ecommerce platform. The specific implementation differs, but the strategy is platform-agnostic.

Mersel AI helps ecommerce brands get recommended by AI search engines. We handle the full GEO stack: technical setup, content optimization, and ongoing monitoring across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. Your storefront stays exactly the same for customers. Book a free AI visibility audit and we'll show you how AI currently sees your store and what it takes to fix it.