AEO for ecommerce: how do product brands get cited by AI search?

Ecommerce AEO operates on a different stack than B2B because the dominant query shapes are "best [product]", "[product] vs [product]", and "is [brand] worth it" — and AI engines now route many of these into product-comparison answers with structured cards. Winning here means optimizing both your own product pages and the third-party review ecosystem AI engines retrieve from.

Six tactics that move ecommerce citation share: (1) Implement Product schema with aggregateRating, review, offers, brand, and gtin — this is the single highest-leverage technical move; AI Overviews and Perplexity shopping cards both consume it directly. (2) Earn long-form reviews on Wirecutter, Tom's Guide, RTINGS, The Strategist, and category-specific publications. These are over-indexed in AI retrieval for product queries. (3) Build a presence in product-relevant subreddits (r/BuyItForLife, r/headphones, r/skincareaddiction, etc.). Reddit citations now appear in 30–40% of ChatGPT "best of" answers post the Reddit-OpenAI deal. (4) Maintain consistent product NAP and identifiers — same GTIN/UPC, same product name across your site, Google Merchant Center, Amazon, and review sites. (5) Publish detailed FAQ pages per product with FAQPage schema. (6) Refresh prices and availability — stale price data is a retrieval downrank signal.

The honest constraint: ecommerce AEO is more competitive than B2B because every category has saturated review coverage. Brands that win usually do so by owning a specific sub-niche (e.g., "best running shoes for plantar fasciitis") rather than the head term.