Search results stopped being ten blue links a while ago. A product now competes for a result with a price, a star rating, and stock status attached, and increasingly for a citation inside an AI-generated answer. Both draw on the same thing: ecommerce structured data, the machine-readable labels that tell a search engine and an answer engine what the words on your page actually mean. The mechanics of the markup are a subject of their own, covered in our guide to ecommerce SEO; this piece is about the stores that get the labelling right.
Why most ecommerce stores leave rich results on the table
Most stores leave that money on the table. When we scanned 80,000 stores across the four major ecommerce platforms in early 2026, 33,148 of them, 41.4 percent, carried no return-policy schema: the policy was on the page for a shopper to read, but no machine-readable markup told a search or answer engine it was there. The share missing it ran from 2.7 percent of Shopware stores to 66 percent of PrestaShop stores. That is one structured-data field among many, and four stores in ten do not label it.
The stores that win rich results are not writing more content. They are labelling the content they already have so a machine can read it without guessing. Here is how a few of them do it.
Four stores that label what is already there
Magic Spoon
On the Apple Cinnamon oatmeal product page, Magic Spoon ships complete commerce markup in a single JSON-LD block: a Product carrying an Offer with price, currency, and availability all present, and an AggregateRating with both a rating value and a review count. Google’s Rich Results Test confirms three eligible types on the page: Product snippets, Merchant listings, and Review snippets. Because the price and the rating are labelled rather than merely printed on the page, the listing can show price detail and stars instead of a plain blue link.
Our Place
On the Cookware Set+ product page, Our Place backs its Product and Offer markup with a BreadcrumbList and customer reviews, and declares ten hreflang alternates (en-US, en-GB, en-CA, en-AU, en-FR, fr-FR, and an x-default among them). The Rich Results Test confirms four eligible types: Product snippets, Merchant listings, Breadcrumbs, and Review snippets. The breadcrumb and review eligibility give the listing more to show in the result, while the hreflang set means each market is shown its own URL rather than the store’s regional versions competing against one another.
KoRo
On the premium-cashews product page, KoRo injects its commerce markup client-side, and it still renders cleanly in the Rich Results Test, which runs JavaScript, coming back eligible for Product snippets, Merchant listings, Breadcrumbs, and Review snippets. The standout here is reach: KoRo runs the most thorough multi-region setup in the roster, 23 hreflang alternates spanning de-DE, de-AT, de-CH, de-BE, de-LU, en-DE, en-CH, da-DK and more. With every language-and-country pair declared, Google can serve the correct localized URL to each market, so the language versions stop cannibalizing one another in search and it raises the odds that an AI answer surfaces the version matching the asker’s language and market.
Gymshark
On the Vital Seamless Shorts product page, Gymshark marks up Product and Offer and goes a step further on reviews, labelling individual Review items with their author and rating rather than only an aggregate score. The Rich Results Test confirms three eligible types: Product snippets, Merchant listings, and Review snippets. Marking up the individual reviews and not only the average gives search engines and AI systems more structured detail to work with, including specific, attributable quotes an AI answer can draw from rather than a bare number.
What stores that win rich results get right
Structured data does not make your content better. It makes your existing content legible to the machines that now stand between you and the shopper. The stores that win rich results are not the ones writing for the crawler; they are the ones labelling what is already true on the page, so the price, the rating, and the availability can be read without inference. The same labelling also helps an AI answer interpret and cite your content accurately rather than guessing at it. The principle is simple: do not write for the machine, label for it.
The single thing to check on your own store: run one product page through Google’s Rich Results Test and confirm that Product snippets, Merchant listings, and Review snippets come back as Valid, not merely present. Markup that is on the page but invalid, missing a required field like price or availability, earns nothing, and that gap is the most common reason a store with good products gets plain blue links while a competitor gets stars.
Run a free scan to see whether your ecommerce structured data is valid, where it is missing, and which listings qualify for rich results.