Does Schema Markup Impact SERP Rank?

The original methodology was an 8-page Google doc and has been reformatted into collapsible sections in the Methodology section of the original schema study.

For the sake of context, I’ll include the shorter version of it here.

A background of our agency and the study

A quick background of our agency gives more context to the study and why this industry was chosen for the experiment.

We’re a digital marketing agency for landscaping and lawn care businesses (as well as other green and outdoor living businesses). Our clients are strictly local and are extremely similar in scale, strategy, and services.

On top of this, we require nearly all new clients to have their site built or rebuilt by us using a templated site theme we built on WordPress. The only real difference between the sites is the branding, images, content, and localization.

The purpose of this study was to determine whether or not schema markup was an effective method for improving rank for our clients, given their local business classification.

The schema markup we used

One of the main considerations for this was determining which schema to use. While some client sites had blog posts, FAQs, and job listing pages, others did not. We needed schema markup that could be consistent with every test subject.

So with that, we went with LocalBusiness markup from schema.org. We had even consulted with Jarno Van Driel, Yoast, and Moz on the items and types within the LocalBusiness markup to be used in this study.

The biggest consideration in the schema markup used was the idea that we wanted to isolate the mere fact of the schema being added to the site, which affects rank, and not the idea that a higher click-through-rate (CTR) through rich snippets affects rank.

Aside from JobPosting schema, there isn’t much in the local service industry that produces rich results, especially with FAQ rich snippets being deprecated completely and only used on government and health organizations after August of 2023.

With that in mind, we avoided any schema markup that aided in producing rich snippets that were still applicable, such as priceRange or reviewRating schema.

The full markup used can be found in the original study under the “Methodology” section.

The pre-test & client sorting

With any controlled experiment, the hardest part is determining subjects that are eligible for the test. Out of our 50 clients, we found 29 that were eligible.

These 29 were:

• Only on our base-level SEO services
• Located in the US
• Had a site built by us (WordPress using Divi)
• Were not producing new or regular content
• Had been continuously working with us for six months or longer

These 29 clients would then be sorted into two groups:

The Control Group would have all SEO efforts paused and no schema added to their site. The Test Group would also have all of their SEO efforts paused; only this group would receive the LocalBusiness schema. 

A unique challenge with our industry is that search volume and competition are seasonal. Knowing that we were conducting this experiment between February and April, it’d be landing right at the beginning of the spring rush. Our Southern clients don’t feel that rush as much as our Northern clients coming out of a snowy winter.

To control the seasonal variable, we’d ensure both the control and test groups would have an equal number of clients in various US geographical locations.