Ratings and reviews are the star scores and written feedback that past customers leave about a product or seller, and in e-commerce they function as social proof that shoppers weigh alongside price, images, and description before deciding to buy. Platforms like Google Shopping, Meta, and most marketplaces let merchants attach aggregated rating data directly to a product listing through the feed, turning what used to live only on a retailer's own site into a signal visible at the exact moment a shopper is comparing options in an ad or search result.

Why Ratings and Reviews Matter for Feed Performance

A listing with visible star ratings tends to earn a higher click-through rate than an identical listing without them, simply because the trust barrier is partly cleared before the shopper ever reaches the product page. This creates a real disadvantage for new or low-review products competing next to established ones with hundreds of reviews, even if the newer product is objectively just as good. It also raises the stakes on feed accuracy: if the fields that carry rating and review count are missing, malformed, or out of sync with what's actually on the product page, no stars will display at all, silently erasing a trust signal the retailer has already earned through customer feedback.

How Ratings and Reviews Work

Reviews are typically collected through post-purchase email surveys, on-site widgets, or third-party platforms like Trustpilot, Yotpo, or PowerReviews, then aggregated into a rating and a count that gets published either inside the main product feed or through a separate product ratings feed submitted alongside it. Because rating data is one of the clearest markers of a complete listing, it's treated as a core input to listing quality scoring, alongside title completeness and image standards. Retailers also lean on e-commerce analytics to measure exactly how much a rating threshold — say, moving from 3.8 to 4.3 stars — actually moves conversion rate, which helps prioritize which products most urgently need a review-collection push.

Example

<item>
  <g:id>SKU-63410</g:id>
  <title>Adjustable Standing Desk Converter - 28 Inch</title>
  <link>https://example-shop.com/products/standing-desk-converter-28in</link>
  <g:price>149.00 USD</g:price>
  <g:availability>in stock</g:availability>
  <g:review_count>312</g:review_count>
  <g:rating_value>4.6</g:rating_value>
</item>

The review_count and rating_value fields here are what render as stars beneath the listing; if either is absent, the platform simply omits the rating display regardless of how many reviews actually exist on the retailer's site.

Related Concepts

Ratings and reviews are one of several inputs into overall listing quality, and they carry particular weight on price comparison pages where a well-reviewed seller can win the click even without the lowest price. Tracking their real impact on conversion is squarely the job of e-commerce analytics, which turns a star rating from a nice-to-have into a measurable driver of revenue.