GEO for E-commerce: Getting Products Recommended by AI
By Damiano Mastrangioli, Co-Founder of Oltre.ai | Published December 2025
A customer asks ChatGPT: "What's the best running shoe for flat feet under $150?"
ChatGPT recommends three products. Yours isn't one of them.
That customer clicks through, reads reviews, and buys from your competitor. You never knew they were shopping. This is happening at scale: AI-driven traffic to retail websites has increased 4,700% year-over-year, and 38% of US consumers already use AI for shopping decisions. By the end of 2025, that number is expected to exceed 50%.
If your products aren't being recommended by AI, you're invisible to a rapidly growing segment of shoppers.
To get products recommended by AI, optimize product pages with detailed specifications and clear benefit statements, build reviews across multiple platforms, create buying guides and comparison content, and ensure strong presence on comparison sites. AI shopping assistants are growing rapidly, with 38% of US consumers using AI for shopping in 2025, and they favor detailed, well-reviewed products from authoritative sources.
The AI Shopping Revolution Is Already Here
This isn't experimental. The biggest retailers recognize the shift and are investing heavily.
| Retailer | AI Shopping Assistant |
|---|---|
| Amazon | Rufus |
| Walmart | Sparky |
| ChatGPT | Shoppable product carousels (April 2025) |
| ChatGPT | In-app Instant Checkout (Late 2025) |
The numbers are staggering:
- 4,700% year-over-year growth in AI traffic to retail sites
- 38% of US consumers already using AI for shopping
- 58% rely on AI for product recommendations
- 50%+ expected by end of 2025
How AI Shopping Assistants Work
When users ask AI for product recommendations, these systems:
- Understand the user's needs and preferences
- Search across multiple sources (product databases, reviews, comparison sites)
- Synthesize information to provide recommendations
- Cite sources and may include direct purchase options
What influences these recommendations? Product reviews and ratings, presence on comparison sites, detailed and accurate product information, brand authority, and content matching specific use cases.
5 Strategies to Get Your Products Recommended
1. Optimize Product Content
AI systems need detailed information to make confident recommendations. Thin product descriptions won't get cited.
For each product, include:
- Comprehensive specifications (dimensions, materials, compatibility)
- Clear benefit statements (not just features)
- Use case descriptions ("perfect for...")
- Honest comparison to alternatives
- Pros and cons (yes, including cons, since it builds trust)
Structure for AI parsing:
- Use clear headings and bullet points
- Include a product summary at the top (40-75 words)
- Present specs in scannable format
- Implement Product schema markup
2. Build Review Presence
Reviews are a primary signal for AI product recommendations. Products without reviews rarely get recommended.
| Platform | Priority | Notes |
|---|---|---|
| Google Reviews | High | Visible across Google ecosystem |
| Amazon | High | For Amazon sellers, essential |
| Industry-specific sites | High | Varies by category |
| Your own site | Medium | Verified reviews add credibility |
Review optimization:
- Actively encourage customers to leave reviews
- Respond to reviews (positive AND negative)
- Include diverse review perspectives
- Never fake or inappropriately incentivize reviews
3. Create Buying Guides
AI systems often draw from buying guides when making recommendations. These are high-value content assets.
"Best [Product] for [Use Case]" matches how users actually ask AI for recommendations. Examples: "Best running shoes for flat feet" or "Best laptops for video editing."
"How to Choose a [Product]" helps users understand what to look for. This positions you as an authority and gets cited when AI explains decision criteria.
"[Product] Buyer's Guide" provides comprehensive coverage of everything a buyer needs to know. Great for capturing long-tail queries.
"[Product A] vs [Product B]" comparison content is heavily used by AI when users ask about alternatives. Be fair and balanced.
Guide optimization:
- Be genuinely helpful, not just promotional
- Include multiple options (not just your products)
- Provide clear recommendation criteria
- Update regularly as products and prices change
4. Ensure Presence on Comparison Sites
AI systems heavily rely on comparison sites and listicles for product recommendations.
Actions:
- Ensure inclusion on relevant "best of" lists
- Submit products to comparison sites in your category
- Maintain accurate listings across all platforms
- Monitor competitor placements
5. Optimize for Specific Queries
Users ask specific questions. Create content that answers them directly.
| Query Pattern | Content to Create |
|---|---|
| "Best [product] under [$price]" | Price-tiered recommendations |
| "Best [product] for [specific use]" | Use-case specific guides |
| "[Product A] vs [Product B]" | Direct comparison pages |
| "Is [product] worth it?" | Value analysis content |
Technical Implementation
Product Schema
Implement comprehensive product schema including:
- Name, description, brand
- Price and availability
- Reviews and ratings (aggregated properly)
- SKU and product identifiers
- High-quality images
Rich Content Requirements
| Element | Why It Matters |
|---|---|
| High-quality images | AI may reference visual quality in recommendations |
| Video demonstrations | Builds trust and engagement signals |
| 360-degree views | Particularly important for fashion, furniture |
| Size/fit guides | Essential for apparel, reduces returns, builds trust |
Site Performance
- Fast page loads (max 3 seconds)
- Full mobile optimization
- Clean, intuitive navigation
- Easy-to-find product information
Category-Specific Considerations
Consumer Electronics: Detailed specifications are critical. Comparison content performs well. Keep content current as models change rapidly.
Fashion & Apparel: Size and fit information is essential. Styling guides help. User-generated content with photos drives trust.
Home Goods: Room-specific recommendations matter. Emphasize dimensions. Assembly and installation information builds confidence.
Beauty & Personal Care: Ingredient information matters. Skin type and concern matching is expected. Before/after content drives decisions.
Measuring E-commerce GEO Success
Traffic Metrics
| Metric | What to Track |
|---|---|
| AI referral traffic | Sessions from AI platforms to product pages |
| Guide traffic | Traffic to buying guides and comparison content |
| Growth trends | Month-over-month AI-sourced visit growth |
Engagement Metrics
| Metric | Target |
|---|---|
| Time on product pages | Higher than organic search average |
| Add-to-cart rate | Compare AI traffic vs. other channels |
| Pages per session | Should be strong if content is relevant |
Conversion Metrics
| Metric | Why It Matters |
|---|---|
| Purchase conversion | AI traffic should convert at or above average |
| Revenue attribution | Track total revenue from AI sources |
| AOV comparison | Often higher from AI-sourced visitors |
Visibility Metrics
- Citation rate for product queries
- Presence in AI shopping recommendations
- Share of voice vs. competitors
Common E-commerce GEO Mistakes
| Mistake | Impact | Fix |
|---|---|---|
| Thin product descriptions | AI can't confidently recommend | Add comprehensive details, benefits, use cases |
| Ignoring reviews | Products without reviews don't get cited | Build review solicitation program |
| Missing comparison content | Competitors fill the gap | Create fair, balanced comparison guides |
| Outdated information | Wrong prices/availability damages trust | Implement regular content audits |
| Over-optimization | Spammy content gets filtered | Write for humans, structure for AI |
Implementation Roadmap
This Week: Audit and Baseline
- Test product queries in ChatGPT and Perplexity
- Document what competitors are being recommended
- Identify top products with thin descriptions
- Check current review presence across platforms
This Month: Quick Wins
- Enhance descriptions for top 20% of products
- Implement product schema site-wide
- Create one buying guide for a key category
- Launch review solicitation campaign
This Quarter: Build Out
- Build comprehensive buying guide content library
- Ensure presence on key comparison sites
- Create comparison content for top competitors
- Track and optimize based on results
Ongoing: Maintain and Expand
- Update product content as inventory changes
- Refresh guides with new products and prices
- Monitor AI citations weekly
- Expand to new product categories
The Emerging AI Commerce Landscape
AI shopping is evolving rapidly. Here's what's coming:
Conversational commerce. Users will increasingly complete purchases within AI interfaces, not your website. Your product information needs to be good enough to sell without your site.
Personalized recommendations. AI will get better at matching products to individual needs and preferences. Detailed product attributes become even more important.
Visual search integration. AI will recommend products based on images users share. High-quality product photography matters more than ever.
Voice commerce. Shopping through voice assistants will increase. Product names and descriptions need to work when spoken aloud.
Transactions may increasingly happen outside your site. Brand recognition, product quality signals, and presence across platforms AI trusts become critical for getting recommended, even when you don't control the checkout.
The Bottom Line
AI is becoming a primary product discovery channel. The e-commerce brands that optimize for AI recommendations now will capture share as this channel grows exponentially.
The fundamentals aren't complicated: detailed product information, strong review presence, helpful buying guides, and visibility on platforms AI trusts. But execution requires deliberate focus on AI as a channel, not just an afterthought.
The shopping assistant revolution is happening. Make sure your products are part of the conversation.
Get Your Products Recommended by AI
Oltre.ai helps e-commerce brands track their visibility across ChatGPT, Perplexity, and AI shopping assistants. See which products are being recommended, and which are being missed.
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