"What's the best wireless keyboard under $100?"
That question used to go to Google. Increasingly, it goes to ChatGPT, Perplexity, or Gemini. And the answer isn't a list of ten blue links. It's a direct recommendation: "Here are three great options..."
If you sell products online, this shift matters. A lot. When an AI recommends your product by name, you skip the entire click-compare-bounce cycle. The customer already trusts the recommendation before they reach your site.
The challenge? Getting your products into those AI responses requires a different approach than traditional e-commerce SEO. That's where Generative Engine Optimization (GEO) for e-commerce comes in.
How AI recommends products differently than Google
When someone searches Google for "best wireless keyboard," they see ads, comparison articles, and product pages. They click, browse, and compare.
When someone asks an AI the same question, the AI synthesizes an answer from dozens of sources. It reads reviews, comparison articles, product descriptions, forum discussions, and expert content. Then it produces a recommendation.
The implications for e-commerce:
AI doesn't just look at your product page. It looks at what the entire web says about your product. Reviews, Reddit threads, blog mentions, YouTube reviews. Your product's overall web presence matters more than any single page.
Specificity wins. AI is great at matching products to specific needs. "Best keyboard for programmers who work long hours" is a query that AI handles well. If your product page explicitly addresses that niche, you're more likely to be the recommendation.
Trust signals are weighted heavily. AI platforms don't want to recommend products that will disappoint. They look for consistent positive signals: good reviews, expert recommendations, editorial mentions.
1. Audit your product's AI visibility
Start by asking all the major LLMs about your product category. Use the exact language your customers would use:
- "Best [product category] for [specific use]"
- "What [product type] should I buy for [situation]?"
- "Top [category] under [price point]"
- "[Product A] vs [Product B]" (your product vs competitors)
Document what you find. Are your products mentioned? Are competitors dominating? Which AI platforms mention you and which don't? You can also run a free product page audit to check whether your product pages have the structured data (Product schema, Offers, Ratings) that AI crawlers rely on.
Mentionable automates this tracking across ChatGPT, Perplexity, Gemini, Grok, and Claude, so you can monitor ongoing visibility without manual testing.
2. Optimize product descriptions for AI understanding
Most e-commerce product descriptions are written for humans scanning a page. AI needs something slightly different.
Be explicit about use cases. Don't just list features. State clearly who this product is for and what problem it solves. "Designed for remote workers who spend 8+ hours typing" gives AI a clear signal for matching.
Include specific comparisons. If your product is better than alternatives in certain ways, say so clearly on the page. "Unlike most mechanical keyboards, this model includes built-in wrist rest support." AI uses these comparison points when generating recommendations.
Address common questions directly. Add a thorough FAQ section to product pages. "Is this keyboard quiet enough for a shared office?" with a clear answer gives AI exactly what it needs.
Use natural language. Write like you're explaining the product to a friend, not filling in a spec sheet. AI understands conversational descriptions better than bullet-point specifications alone.
3. Build category content that establishes authority
Your product pages alone won't cut it. You need content that proves you're an authority in your category.
Create honest comparison guides. "Best wireless keyboards for 2026: Tested and reviewed" type content, where you include your product alongside competitors, builds credibility. Biased content that only promotes your products will be disregarded by AI.
Publish buyer's guides. "How to choose the right wireless keyboard" helps AI understand that your brand knows this space deeply. These guides also become sources AI cites when answering informational queries.
Write use-case specific content. "Best keyboards for gaming," "Best keyboards for writers," "Best keyboards for small desks." Each piece targets a specific query AI users ask, and gives AI a clear recommendation to extract.
Share real customer stories. Case studies and use-case spotlights show AI how real people use your products. "How our keyboard helped a freelance writer reduce wrist pain" is the kind of specific content AI can reference.
4. Maximize review signals
Reviews are one of the strongest trust signals for AI product recommendations.
Encourage reviews on multiple platforms. Amazon reviews, Google Reviews, G2 (for software products), Trustpilot, and niche review sites all feed into AI's understanding of your product quality.
Respond to reviews. Active engagement with reviews, both positive and negative, shows that your brand is present and responsive. AI can pick up on this pattern.
Seek expert and editorial reviews. A review from a respected publication or YouTuber in your niche carries more weight than dozens of anonymous reviews. Reach out to relevant reviewers and offer samples.
Don't ignore negative reviews. Address them publicly and honestly. A brand with 4.3 stars and thoughtful responses to criticism can outperform a brand with suspicious 5-star-only ratings.
5. Optimize for "best X for Y" queries
These are the highest-value queries in e-commerce AI. They signal buying intent.
Map out every "best X for Y" combination relevant to your products. Best [product] for [audience]. Best [product] for [use case]. Best [product] under [price]. Best [product] in [category].
Create dedicated content for each combination. A single product page can't rank for every variation. Build landing pages or blog posts that directly address each specific query.
Include clear recommendations. Don't be afraid to say "This is our top pick for [use case] because..." AI needs extractable recommendations.
Use structured data. Product schema, Review schema, and FAQ schema help AI platforms understand your content and products more precisely.
Common mistakes in e-commerce GEO
Relying only on product pages. Product pages are transactional. AI needs informational content too. You need the full ecosystem: product pages, guides, comparisons, reviews, and category content.
Thin product descriptions. A five-line description with basic specs isn't enough for AI to understand why it should recommend your product over alternatives. Add depth, context, and use cases.
Ignoring third-party presence. What others say about your products matters as much as what you say. If your competitor has 500 reviews on Amazon and you have 12, AI will lean toward the competitor.
Generic content. "We sell the best keyboards" tells AI nothing useful. "Our TK-200 is the quietest mechanical keyboard we've tested, hitting just 35dB" gives AI a specific, citable fact.
Not tracking visibility. You can't improve what you don't measure. Without monitoring which AI platforms mention your products and for which queries, you're optimizing blind.
Building your product review ecosystem
For e-commerce specifically, the review ecosystem is a multiplier. Here's a priority order:
- Your own site reviews with verified purchase badges
- Amazon/marketplace reviews if you sell there
- Google Shopping reviews for Gemini visibility
- YouTube video reviews from creators in your niche
- Blog/editorial reviews from publications your audience reads
- Reddit and forum discussions where real users mention your product
Each source feeds different AI platforms. ChatGPT and Perplexity heavily reference editorial content. Gemini leans on Google properties. Grok picks up social discussion. Covering all channels maximizes your overall AI visibility.
Realistic expectations
E-commerce GEO takes time because review and authority signals build gradually.
Month 1: Audit AI visibility. Optimize product descriptions. Identify content gaps.
Month 2-3: Publish category content (comparison guides, buyer's guides). Reach out for expert reviews.
Month 3-6: Build review volume. Strengthen backlink profile. Create use-case specific content.
Ongoing: Monitor AI recommendations. Update content as products and competitors change. Keep review profiles active.
The brands that invest in this now, while most e-commerce businesses are still focused exclusively on Google Shopping and Amazon ads, will have a significant head start as AI-driven product discovery grows.
Your next moves
Pick your top 5 best-selling products. Ask each major AI assistant for relevant recommendations in those product categories. Document where you stand.
Then start with the highest-impact actions: improve product descriptions, create one comparison guide, and work on building your review presence.
Track changes with Mentionable to see which AI platforms start recommending your products as your efforts take effect.
