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How Is SEO Split Testing Different from CRO Testing?



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In this post, we will discuss the differences between CRO (conversion rate optimization) testing and SEO split testing. This thorough overview can help you determine if SEO split-testing fits into your SEO strategy.


While these tests sound similar, there are significant differences. Distinct Differences Between CRO Testing and SEO Split Testing

CRO Testing

In CRO testing (sometimes called CRO user testing or CRO A/B testing), you duplicate a web page or an email, changing one element. You can then send traffic to both versions of the page or email. The comparative conversion rates then reveal which version provides a better conversion rate.

In CRO testing, we’re solving for a user:

  • You are testing two versions of a web page or an email.

  • You are testing for web traffic you already have or an email list.

  • You are attempting to increase your conversion rate with on page elements.

  • CRO testing provides a conversion win on one page or email.

  • A CRO test does not scale across many pages or email messages.

  • CRO testing requires a new test for each page or email you want to test. SEO A/B or Split Testing

We cannot duplicate a page in SEO split testing, which would be considered cloaking, a violation of Google’s webmaster guidelines.


This can lead to your website being entirely removed from Google’s index or otherwise affected by an algorithmic or manual spam action.


In SEO split testing (sometimes called cohort SEO split testing), we test a change across a group of URLs in the variant group compared to a control group with the intent of looking for a statistically significant result.


In SEO A/B testing, we are solving for Googlebot.

  • You are splitting a group of URLs into two groups (control and variant).

  • You are testing for an increase in organic web traffic.

  • You are attempting to increase the number of clicks from Google’s search engine results.

  • SEO split testing allows you to roll out a positive test to sections of your website.

  • SEO A/B split testing scales optimizations across enterprise websites.

  • In SEO split testing, you can have hundreds to thousands of URLs within a test.

There are several types of SEO A/B split tests:

  • Pre and Post SEO split testing

  • Cohort Analysis in SEO split testing

  • Manual SEO A/B split testing

  • SEO A/B split testing with SplitSignal Pre and Post SEO Split Testing

In this form of SEO split testing, the SEO marketer makes a change on a single page, then takes a snapshot of the change, makes a note of what the Google Analytics (GA) traffic is, and may also measure the number of clicks to the URL from Google Search Console (GSC).


The SEO then comes back a month or two later and measures for any difference in GA or GSC traffic based upon the change.


This form of SEO split testing is very close to CRO testing; it is challenging to ensure that there are not other variables in play that might affect the test result.


This form of testing does not lend itself to scaling SEO testing across your site. Cohort Analysis in SEO Split Testing

A cohort is a group that shares common characteristics, usually within a specific timeframe. In SEO split testing, the cohort characteristics are the clicks from Google’s search engine results to the URLs in the testing group. The timeframe is the 100-days before the split test. How to Conduct Manual SEO A/B Split Testing

In this version of SEO split testing, the SEO has a data science team split a group of URLs into two groups (control and variant) with an equitable traffic model for the past 100 days. This can take months to accomplish manually.

Next, the SEO has the development team make an SEO testing variant change to an element of each URL within the variant group. The extent of this task depends on the number of URLs within the variant group.

Then the SEO, development team, or analytics team sets up tracking for the test results with a dashboard such as Databox or Tableau.

Then it’s finally time to launch your test!

Upon completing your test, have your data science team analyze the data using a Casual Impact statistical model to ensure that you had statistically relevant results.

Lastly, the data science team should provide you with the analysis and results within your dashboard.

This manual process is very labor-intensive and can take many months to set up, run and analyze the test results. Cohort SEO Split Testing with SplitSignal

SplitSignal is a client-side SEO split testing platform that runs cohort analysis on tests and changes to on-page SEO optimizations.


How Does SplitSignal Run SEO Split Tests?

In SplitSignal, we take a group of URLs and equitably split them into two groups (control and variant) by organic clicks from Google Search Console. This takes minutes and is quickly done.

We then make one on-page bulk change to the URLs in the variant group via a JavaScript snippet code in the head of the web pages in the split test.

What on-page changes are available for testing in SplitSignal?

Most of the element changes are visible on the URLs within the variant group besides page title changes and meta description changes. You can have a test up and running in minutes.

Googlebot then crawls the variant group of URLs during the test (usually within the first seven days), picking up the change.

SpitSignal tests are by default set to 21 days but can run up to 42 days long.

SplitSignal employs a statistical Bayesian Casual Impact model (Google’s standard for SEO split testing) to measure whether optimizations within SEO tests will impact clicks for Google’s search engine results.

SplitSignal puts all this test data into a test dashboard with test analysis.

With SplitSignal, you can get SEO A/B split tests up and running in minutes and have tests completed within days, not months.

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