How do you A/B test for SEO?

- Identifying Variables: Choose elements like title tags, meta descriptions, or content to test. - Creating Variations: Develop alternative versions for each element to test. - Setting Metrics: Define key performance indicators (KPIs) such as click-through rates (CTRs) or organic traffic. - Running Tests: Use A/B testing tools or platforms to serve different versions to users randomly. - Analyzing Results: Compare performance metrics between variations to determine the most effective. - Implementing Changes: Deploy the winning variation based on test results. - Iterating: Continuously refine and test different elements to optimize SEO performance over time.

1. Choose Elements to Test 2. Divide Pages and Run the SEO Test 3. Measure Results Best use cases for SEO A/B testing 1. Title tags 2. Meta descriptions 3. Schema markup 4. Internal links 5. New content 6. Large groups of pages 7. Information architecture 8. Site migrations

Always good to have a working theory. But don’t be afraid to try some crazy ideas. You never know what users will like, or what language they will resonate with.

For any single URL that has less than 1000 organic visitors per month (which will be most of your sites) the ONLY thing worth testing will be: Meta Titles & Meta Descriptions, because it's the first thing searching users will see - anything else will just catch a few eyes and definitely not a statistically relevant amount that is either actually producing insights or impact, considering that we're talking about quite the effort here that is supposed to result in noteworthy return Doing A/B Testing on Metadata: - Choose a set of URLs (that has 1000+ organic visitors/ month) - Write titles & descriptions in different styles (emotional, claim-based, numbers based, sensational, USP based, positive, negative, formal, informal) - check CTR

What is this article even about? If you want to run conversion optimization experiments then the tools listed are ok. In that case, you shouldn't be concerned about SEO because most search crawlers like GoogleBot won't execute the testing tool JavaScript nor send hits to your web analytics. Of course, it never hurts to check that your A/B testing variants aren't crawled and indexed by search engines. But in my 10+ years of experience, that never happened. However, if you need SEO A/B (split) testing - to verify your SEO strategy and ideas for better SERP rankings, then none of the mentioned tools will be suitable. For that, you should use SEO A/B testing tools like SEMRush SplitSignal or SearchPilot. (I have no affiliation with either)

Let's assume the catalogue of your shop has thousands of products and you want to verify if a different page title impacts rankings. You start by splitting your product catalogue randomly into group A and B. Your development team or content management teams change the page title for one group. Assuming you have the right monitoring capabilities, you can now monitor how the ranking improves.

The purpose of SEO A/B testing is understanding the impact of site changes on organic traffic. The tools listed here look at user behaviour. With SEO A/B testing, there are not multiple versions of a webpage as, unlike all the users coming to your site, there's only one Googlebot. The guidance provided in this section is misguided, for example, why would you prevent the indexation of a test page if the purpose of the test is to measure the impact on organic search? Before considerations of selecting a tool for SEO A/B testing, it's important to understand that user testing splits users and SEO testing splits pages into buckets with one being used as a control and another as variant to measure the impact of site changes on traffic.

I never heard of seo AB TEST. You can test CRO not seo … if you test the same page you will have duplicate content and google will decide the one to index and rank .. maybe that is the idea

These tools are all not suitable for SEO A/B testing. Better use Splitsignal by Semrush to devide page groups evenly and test things like titlestags.

These are the primary steps for setting up an SEO A/B test: 1. Select the site section you want to test. This requires a section of the site that is using the same template, ideally with a high volume of pages. 2. Bucket the pages into statistically similar groups. You'll want to rank the pages from highest to lowest traffic, consider other signals in your analytics data, and ensure that both buckets are similarly impacted by external factors like seasonality, algorithm updates, competitor behaviour, etc. 3. Select your hypothesis and apply changes only to the variant pages. The criteria to measure an SEO A/B test is traffic. Your analytics platform is best. GSC, due to the way they group pages, isn't recommended.

It's important to note the "sufficient period of time" because it does take, sometimes months, to see actual movement from your changes. Don't abandon the project too early!

If you’re also responsible for conversion metrics, SEOs should consider running CRO tests as well. Test your CTAs, headline copy, checkout flow. If you’re responsible for moving metrics like free trial sign-ups or product purchases, then you should be testing those or working closely with the team who does. Review your key pages for points of friction, conduct user research if you can, and make a list of ideas to test. Increasing traffic with a title test is good, but increasing conversion rate on a key page is great.

We know click through rates (based on title tags and meta descriptions) are a signal to google, which means you can quickly test headlines via ppc ads. If it performs there’s a good chance it will work organically.

With Google's increased focus on experience signals like Core Web Vitals, A/B testing for SEO in 2024 involves creating page variants that differ in user experience factors - load times, layout shifts, interactivity, etc. Traffic is split, and the variant providing a better searcher experience based on engagement metrics like dwell time and bounces gets rolled out. This aligns with Google's prioritization of rewarding great digital experiences over just optimizing content.

It's vital to follow best practices to avoid potential SEO issues. Always use 'rel=canonical' tags on variation pages, directing search engines to the original version to prevent duplicate content issues. You shouldn't mix canonicals (to another URL) with the noindex tag. Monitor your tests closely, assessing organic traffic and rankings regularly. Once you conclude the test, implement the winning variation site-wide as soon as possible to minimize disruption to your SEO. Also, don't hide your test from Google.

Ensure you do not show one type of content to users and a different one to Googlebot. For example, don't always display the original content only when you detect the user-agent 'Googlebot.' This practice is known as cloaking, and it's against Google spam policies.