Case Semrush: How Negative Review Snippets Can Affect SEO Performance

Case Semrush: How Negative Review Snippets Can Affect SEO Performance

21%
Increase in clicks
After 6 days
Significant result
95%
Statistical reliability

What?

Using A/B testing, we examined how negative reviews affect SEO performance.

Rich search results with reviews are important for your website's visibility and CTR. But what happens if those reviews are negative? We investigated the impact of low review scores on SEO performance.

Voorbeeld negatieve recensie SEO

How?

Strategic approach via A/B testing with the Semrush tool SplitSignal

We tested the effect of removing rich results for products with a review score lower than 3 stars. With A/B testing, we could precisely measure what this did to organic traffic. The hypothesis: low review stars lower the CTR. By omitting the structured data for these products, we placed less emphasis on negative reviews and encouraged users to click through. This gave them the chance to find more product information on the site—and possibly other relevant products.

Resultaten Verwijderen van lage reviewsterren

Result?

Removing low review stars significantly increases click behavior

Excluding the aggregateRating for products with a score lower than 3 stars led to a 21% increase in clicks. After just six days, this increase proved statistically significant at the 95% level. By using predictive models and control pages, we could exclude external influences and demonstrate the actual impact of the change. A powerful reminder that smart adjustments in structured data can have a direct effect on your organic performance.

What now?

Test and optimize your search results

This test shows that rich search results are not always successful; low ratings can attract negative attention. The test led to a higher CTR for the tested product pages, but the impact on total traffic was limited by the number of low review scores. Split testing helps SEOs discover what works and build strong business cases for improvements. Test and prioritize what has the most effect.