First

more product research now starts in an AI engine

Before Google Shopping, before Amazon, before your site

Pre-sold

AI-referred shoppers often arrive ready to buy

They arrive pre-sold on your category, not just browsing

New

AI referrals are an emerging revenue channel

Track how much of your category demand AI engines now influence

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Step 1: The Shift
How AI Engines Have Changed Product Discovery
Two years ago, a shopper researching running shoes would Google "best running shoes 2024," scan 10 links, and click through to a review site. Today, they ask Perplexity or ChatGPT and get a confident answer naming 3–5 specific products, with brief explanations of who each is best for.
Your brand either gets named in that answer (with a recommendation for the right buyer) or it doesn't exist to that shopper. Google Shopping, Amazon rankings, and paid ads don't help you here. This is a different channel with different rules.
The zero-click problemIn traditional search, even if you ranked #3, you still got some clicks. In AI search, there is no page 2. If your brand isn't named in the AI's answer, the shopper never knows you exist.
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Step 2: Query Types
The 5 Query Types That Drive Product Recommendations
Not all queries drive equal purchasing intent. Understanding the query types AI engines answer in your category helps you prioritize where to optimize first.
Category recommendation
""best running shoes for marathon training under $150""
Highest volume: AI engines answer these with specific product recommendations
Comparison query
""Nike Pegasus vs Brooks Ghost for wide feet""
High purchase intent: user is in final decision stage
Problem-solution
""what mattress is best for back pain""
Brand-agnostic intent: AI engines recommend category leaders
Gifting / occasion
""best kitchen gadgets to gift a home cook""
Seasonal: spikes before holidays, Valentine's, Mother's Day
Alternative search
""alternatives to Dyson vacuum under $200""
Displacement opportunity: if competitors own this, you can capture it
Start with category recommendationsCategory recommendation queries ("best X for Y") have the highest volume and the clearest path to optimization. Ranking in these answers is the AI equivalent of winning a Wirecutter review: sustained, high-intent traffic with no recurring ad spend.
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Step 3: Optimisation
What Makes Products Get Recommended
AI engines recommend products based on a combination of signals: structured content, review sentiment, citation frequency on trusted sites, and how clearly your product page answers the "is this right for me?" question.
Product page checklist
- Lead with a direct-answer product description: what it is, who it's for, key specs
- Include named comparisons: "vs [competitor product]" with honest differentiation
- Add Product schema with offers, aggregateRating, and brand fields
- Publish reviews that AI engines can quote: specific use cases, named benefits
- Create a dedicated "best [category] for [use case]" landing page for each key query
- Add FAQPage schema to category pages answering top product comparison questions
Category landing pages beat product pagesAI engines answer category queries with content from editorial-style pages, not product detail pages. A well-structured "best [category] for [use case]" landing page, with direct-answer copy and FAQPage schema, consistently outperforms individual product pages for category queries.

Step 4: Seasonal

Seasonal AI Visibility Strategy

AI recommendation patterns shift seasonally. The brands that win during peak periods start publishing optimized content 6–8 weeks before the surge, not after.

Period	Key query types	Action
Jan–Feb	Valentine's Day gifts, New Year fitness products, tax season home office	Publish gifting guides and occasion-specific landing pages 6–8 weeks ahead
Apr–May	Mother's Day, spring gardening, graduation gifts	Update occasion landing pages and check competitor share-of-voice
Jul–Aug	Back to school, summer outdoor gear, early Black Friday research	Launch product comparison content for high-volume category queries
Oct–Dec	Black Friday, Christmas gifting, holiday kitchen, year-end deals	Peak season: your plan cadence keeps running (daily on paid plans, weekly on free), and you can scan on demand between refreshes; turn on competitor alerts

Track seasonal queries before peak seasonAdd your key seasonal prompts 8 weeks before each peak period, so the scans have a baseline to compare against. If a competitor starts dominating AI recommendations for "best Christmas gifts under $50," you want the first scan that shows it to land in October, not December.

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Step 5: Dashboard
Your E-Commerce Toolkit in LLM Metrix
LLM Metrix tracks AI visibility on the product and category queries you choose to follow, the signals that correlate most directly with AI-driven e-commerce revenue.
Category & Product Query Tracking
Track the category and product queries that matter as prompts, and see brand mention rate, answer position and sentiment for each one, per engine.
Category Share-of-Voice
How often your brand appears vs. competitors in category recommendation queries, the metric that correlates with AI-driven revenue.
Scan-Over-Scan Alerts
Each completed scan is compared with the one before it, so you hear when your score moves, a competitor gains share of voice, or a new source starts getting cited.
GEO Content Recommendations
Prioritised action briefs built from the gaps in your latest scan: which engines and queries you are missing, and the concrete next step for each.
Your first 5 actions