Answer engine optimizationfor ecommerce.Your products, named and clicked.

AEO for ecommerce is answer engine optimization applied to a product catalogue rather than a service business. When someone asks an AI assistant which product suits a specific need, budget or use case, the assistant returns a small number of named products. AEO for ecommerce is the work that gets your products into those answers, and gets the resulting click to land on your own site rather than a marketplace listing of the same item. It covers product feed and identifier quality, product schema, comparison and use-case content, review depth at product level, and category pages built as entity anchors.

Ecommerce SEO competes for positions on a results page, where the buyer still compares options themselves. Ecommerce AEO competes to be one of the products named inside the answer. The practical difference is where the work sits. Traditional SEO focuses heavily on category page rankings and content volume. AEO puts far more weight on the machine-readable quality of your product data, on comparison material that a model can extract directly, and on review depth at the individual product level. The foundations overlap, so your organic performance improves alongside, but the priorities are genuinely different.

Your feed is the most structured thing a model can read about what you sell. Every other source requires interpretation. A feed states the brand, the identifier, the category, the attributes, the price and the availability as explicit facts. Most feeds were built to satisfy the minimum requirements of a shopping channel rather than to be quoted, which means titles use internal naming conventions, most attributes are blank and identifiers are inconsistent. A model reading a thin feed has very little to work with, so it recommends whichever competitor gave it more. Rebuilding the feed is usually the highest-leverage first move in an ecommerce engagement.

An assistant can name your product and then send the buyer to an Amazon or marketplace listing of that same product rather than to your own page. You get the mention, somebody else takes the margin. This happens because marketplace listings often carry more reviews, richer structured data and stronger domain signals than the brand own product page. It is the biggest and least discussed problem in ecommerce AEO. The fix is making your own product page the richest and most citable source for your own products, which means review depth, complete structured data and content the marketplace listing does not have.

Yes, and at product level rather than brand level, because that is the level an assistant is weighing. Four thousand brand reviews do nothing for a line with six. Using the same outbound infrastructure Deligatr runs for its managed outbound clients, we reach out to your past purchasers on your behalf, at the right point after delivery, and bring reviews in against the specific products you want recommended. Everything is written in your voice and approved by you before it goes out. Most agencies hand you a review request template. We run the campaign.

Comparison content, by a wide margin. Direct this-versus-that pieces between two named options get extracted almost verbatim because their structure already matches how the question was asked. After that, best-for-a-specific-use-case content, where the framing is narrow and honest rather than claiming to be best overall. Then buying guides that give a model an actual framework of criteria it can apply. Generic category copy and brand storytelling get almost nothing, which is where most ecommerce content budget currently goes.

Yes, and platform is rarely the limiting factor. We work across Shopify, WooCommerce, BigCommerce, Magento, custom builds and headless setups. What matters is whether we can control the feed, add proper product schema and publish content, and every mainstream platform allows all three. Some make certain work faster than others, and a small number of heavily locked-down setups impose real limits. Where that applies to you we say so on the first call rather than after you have committed.

The first two months go on the data foundation: feed rebuild, identifier and attribute cleanup, product schema across the catalogue, and resolving conflicts between your feed and your pages. That work is unglamorous and little is visible while it happens, but everything after it depends on it. Comparison content and review outreach run from around month two. Products start appearing in AI answers from roughly month three, with traceable revenue typically between month three and month five. Anyone promising faster than that on a catalogue of any size has not looked at your feed.

Almost never, and we will usually argue against it. Most catalogues have a minority of lines carrying the majority of the margin, and those are where the work belongs. Broad shallow coverage across thousands of SKUs produces less than deep work on the lines you actually want recommended. On the second call we go through which products are worth prioritising and which we would leave alone entirely. Paying us to optimize a long tail you do not care about is not a good use of your money.

We track how often your products are named and cited in AI answers across the shopping queries that matter in your category, and how that compares with the competitors and marketplace listings being named instead. Alongside that we track AI referral traffic as its own channel, separating visitors arriving from ChatGPT, Perplexity, Gemini and Copilot from ordinary organic search, and tie that to revenue rather than sessions. Most ecommerce brands cannot currently tell you whether AI sends them anything, because it is buried inside organic in their analytics.

Honestly, and by not building for any single one of them. Shopping surfaces inside assistants are new and get rebuilt frequently, so we will not promise placement in a specific feature that may not exist in six months. What we will say is that every one of these surfaces rewards the same underlying things: accurate and complete product data, agreement between your sources, genuine review depth and content that answers a comparison question directly. Those do not change when a surface does, which is why the work holds its value through the churn.

We do not work with gambling, casinos or 18+ businesses. We also decline regulated advice categories, which for ecommerce most commonly means supplements and health products making medical claims, since Google classifies those as Your Money or Your Life and holds them to an evidence standard requiring genuine verifiable credentials. We also decline counterfeit and grey market goods. And we will tell you honestly if you are dropshipping a catalogue you do not control, because we cannot build product authority on data and reviews that belong to somebody else.