Do higher review scores lead to higher organic product rankings in Google?

The review score and ranking connection

Product review scores (typically displayed as star ratings) serve as a key quality signal for both consumers and search engines. Google's algorithm considers review ratings as an indicator of product quality and customer satisfaction, which can influence how products are ranked in Shopping results.

However, review scores work in conjunction with other factors. While higher ratings can contribute to better visibility, Google also weighs relevance, price, review volume, and other trust signals. It's worth noting that the number of reviews may have a different impact than the average rating score alone.

Understanding the heatmap

The heatmap above visualizes how review scores correlate with vertical position on the search results page, scaled to 0–100% within each SERP. Lower percentages indicate higher positions on the page. Review scores are grouped into bins of 0.5 stars to show broader patterns.

Look for patterns where certain rating ranges cluster at specific page positions. This can reveal whether products with higher ratings tend to appear higher in results, or if rating scores have less impact on ranking than other factors like relevance or price.

It's important to note that lower-reviewed products might not show up in this data analysis, since we're only looking at products ranking on the first page of Google. Products with very few or no reviews may not appear in these results at all. For more information about review counts and their distribution, see our review count distribution insights page. Review scores can impact rankings, but they work alongside many other ranking factors.

Key takeaways

• Review scores are one quality signal among many that Google uses for ranking
• Products with lower ratings can still rank well if other factors are strong
• Maintaining high review scores over time can contribute to improved visibility
• Both review quality (scores) and quantity (count) matter for rankings
• Review scores alone don't guarantee top rankings—relevance and other signals matter

How we normalize page depth per SERP

Some search result pages are far taller than others because of extra SERP elements. To compare positions fairly, we normalize depth within each SERP: Relative Depth = (pixel_y - min_pixel_y) / (max_pixel_y - min_pixel_y) * 100. This scales vertical position to 0–100% per SERP and avoids skew from unusually tall pages.