Schema Markup Case Study: What Happened After We Fixed It

TL;DR:

I audited an established ecommerce website and found significant problems with its structured data, including missing Breadcrumb and LocalBusiness markup and errors in its Product schema. After those issues were fixed, Google began detecting the changes and the site saw improvements in click-through rate, average position, impressions and clicks. The timing of those improvements closely aligned with Google processing the schema changes, making this a useful real-world example of the impact a better structured data implementation can have on organic search performance.

The schema issues identified in the SEO audit

In the not too distant past, I carried out an SEO audit for an established ecommerce website.

The site was already performing reasonably well in a competitive niche, with good page-one rankings across a number of important search terms. The client wanted to understand whether there were opportunities to improve its organic performance further and whether there were any underlying SEO issues holding it back.

The initial audit gave the website an overall organic performance score of 64%. Structured data stood out as one of the clearest opportunities for improvement, scoring just 45%.

There were opportunities elsewhere, including crawl optimisation, but the structured data issues were relatively straightforward to address and affected a significant number of pages across the site.

The main issues identified were:

• Organisation / LocalBusiness schema: there was an opportunity to provide clearer structured information about the business. I’ve covered Organisation schema implementation separately here.
  
• Breadcrumb schema: the site already used breadcrumbs for navigation but wasn’t applying BreadcrumbList structured data. I’ve covered BreadcrumbList implementation in this guide.
  
• Product schema: Product and Offer structured data was already present, but the implementation contained errors. The required name property was missing, and Product markup was also being generated on category pages. Despite the site having around 18,000 products, Google Search Console was detecting approximately 153,000.

The developer corrected the Product markup and implemented the missing structured data. Google Search Console then gave us a useful timeline showing when Google began detecting and processing those changes.

Google starts detecting the new schema markup

Once the developer had implemented the changes, Google Search Console started reporting the new and corrected structured data.

This gives us a useful timeline for comparing when Google detected the changes with what subsequently happened to organic search performance.

Breadcrumb Schema

Google Search Console first started detecting the new Breadcrumb markup on 5 March, with the number of valid items increasing significantly by 12 March.

LocalBusiness Schema

The LocalBusiness structured data was detected over a similar period, confirming that Google had processed the new markup.

Product Schema

At the same time, Google processed the changes to the existing Product structured data, including the removal of markup that had previously been generated unnecessarily across category pages.

By this point, we had a reasonably clear indication in Search Console that Google had discovered and processed the main structured data changes.

The interesting part was what happened to organic search performance over the same period.

What happened to organic visibility after the schema changes?

The impact on organic visibility is clear.

From 11 March, shortly after Google Search Console began detecting the structured data changes, the site started to see improvements across several organic search metrics.

Comparing 11 March to 2 May with the preceding period showed:

• an increase in average position
  
• an increase in click-through rate
  
• an increase in search impressions
  
• an increase in organic clicks

The improvement wasn’t isolated to one or two URLs either. It could be seen across a large number of pages on the site, suggesting a broader improvement in organic search performance.

The timing is particularly interesting. Google Search Console began detecting and processing the structured data changes at around the same time that the site started to see improvements in average position and click-through rate, alongside increases in impressions and clicks.

For me, the impact is clear. Fixing the site’s structured data implementation coincided with a measurable improvement in organic search performance across a significant number of pages.

Schema markup shouldn’t be treated as an afterthought, particularly on an established site where implementation errors or missed structured data opportunities can affect thousands of pages.

What this schema markup case study demonstrates

This case study is a good example of why structured data is worth reviewing as part of an established site’s SEO.

The website was already performing well, but its schema implementation contained errors and missed opportunities across a significant number of pages. Once those issues were corrected, Google began processing the changes and we saw improvements in average position, click-through rate, impressions and clicks.

The biggest lesson for me is that schema shouldn’t simply be implemented and forgotten about. It needs to accurately describe the content on the page, use the appropriate schema types and avoid generating unnecessary or invalid markup across the site.

If you’re unsure whether structured data is implemented correctly on your website, it’s one of the areas I review as part of a website SEO audit.

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