Why ecommerce teams pick us
Shoppers in 2027 ask AI engines for recommendations before they ever hit a category page. The answer they see, "the 5 best running shoes for flat feet are...", is the new top of funnel. If your brand isn't in that list, the click never happens. We track which brands, retailers and review sites get named, per engine, per locale.
The shopper prompt set
Three classes of prompts to track from day one: category prompts ("best X for Y"), comparison prompts ("X vs Y"), and buying-decision prompts ("is X worth it" / "what should I know before buying X"). Each class has different winning content patterns and different schema requirements.
Pattern
Schema and feed audit
AI engines pull structured product data the same way Google Shopping does. We audit Product, Offer, AggregateRating and Review schema on every tracked URL, plus your Merchant Center feed health. Missing GTIN, MPN or shipping fields will keep you out of AI shopping answers in 2027 the same way they keep you out of Google Shopping today.
The seasonal cadence
Step 01
Q1: baseline category, comparison and buying-decision prompts. Audit schema and feed.
Step 02
Q2: ship the editorial content AI engines actually cite. Engage with reviewer sites and Reddit threads strategically.
Step 03
Q3: pre-peak schema sweep. Validate every PDP for Product/Offer/Review/AggregateRating completeness.
Step 04
Q4: monitor daily, react fast. Citation churn is highest during peak. The teams who watch the dashboard daily ship the fastest fixes.