Strategy for A/B testing within SEO

A/B testing is an essential part of an SEO strategy. These tests make it possible to systematically test different parts of a Web site. This gives insight into which aspects are working and which need a little more attention, so that the website keeps getting better. As a result, the website will rank higher and higher in Google.

The significance of A/B testing within SEO

In A/B testing within SEO, you create two versions of a web page, version A and version B. Both versions are tested by a similar target audience. The results obtained are compared. Based on the results, you can see which version of the website works better and thus which can be better deployed. Using the right version of the website can improve both user experience and SEO.

A/B testing applies not only to entire websites, but also to components of the website, such as page titles, meta descriptions, images or headers.

The impact of A/B testing

Small changes have a big impact on SEO performance. SEO specialists make good use of this by systematically testing website performance and measuring the impact of changes. This has a positive effect on both the user experience and results in Google.

Moreover, A/B testing allows you to secure your search engine rankings more. Any modification on a Web site can potentially result in a lower ranking in search results. For a Web site that is in the top three search results, this is too great a risk. Websites that come out a lot lower in search results are less at risk when their position in search results drops. In that case, an A/B test is not always necessary.

Risky adjustments

Not all changes you make to a Web site are equally risky. Some adjustments pose more risks than others to your position in Google. Content-related changes are especially impactful, think text, images, videos and on-page SEO.

Always consider what risks fit within the boundaries of the SEO roadmap. For a website that is in the top 3 of Google’s search results, it is a big risk to change the title or meta description of the website. The position may fall sharply, but a rise is also possible. Moreover, after these changes, Google revisits the page and reevaluates the website as well, leading to additional risks.

How A/B testing works.

At its core, A/B testing is an experimental approach that pits two versions of a Web page against each other I begin an A/B test for SEO optimization by choosing a Web page and selecting a specific element I want to test, such as the layout or header. On the B version of the website, I make the changes. I then present both versions of the website to a portion of the website’s audience and review the results. I analyze the results using tools like Google Analytics.

Programs like Optimizely make analyzing an A/B test relatively easy. Previously – until September 2023 – Google Optimize was used for this purpose. The operation of both tools is similar.

Difference between A/B testing and multivariate testing

A/B testing focuses on one variable at a time, while multivariate testing tests multiple variables and combinations thereof at the same time. In some cases, the interactions between different elements of a page are interesting. In that case, a multivariate test is very appropriate.

Multivariate tests, however, are more complex to perform. In addition, this type of test requires more traffic to generate significant results.

Focus on user experience

A major reason I use A/B testing is to improve the user experience. User experience has a direct correlation to SEO performance. The better the user experience, the longer visitors are on the website and the lower the bounce rate is.

A/B testing can help analyze and optimize various aspects of the user experience, including content readability, page load speed and navigation. I experiment with different elements to find the best combinations to attract more visitors to my website.

So an A/B test for SEO purposes is often more focused on improving the user experience, but also has an indirect effect on SEO. For the website’s final position in search results, all user metrics matter. SEO specialists must provide as much value to the visitor as possible and ensure that Google recognizes this from the user metrics.

Optimize conversion

For a successful website, good conversion rates are very important. A/B testing helps with this, too. The test results can be used to analyze which elements of a website lead to higher conversion rates. For example, test different colors on a website or place a call-to-action button. By continuing to test and analyze each change, you will eventually end up with a website with a good conversion rate that will also rank higher in search results.

When applying a conversion strategy, it is important to distinguish between the different conversions you want to generate. I personally always set at least 2-3 different conversions, in different places on the website. For example, I use a contact form or add a button to download a white paper.

Higher ranking in search results

Like increased user experience, conversion rates have an indirect effect on position in Google search results. Websites with a good user experience and conversion rate are prioritized in search results. Thus, A/B testing is less focused on the direct effects on SEO position, but more and more on the indirect influence. This then also leads to higher sales.

What are the objectives?

For the highest possible results, it is important to properly define and set the goals for running the A/B tests. Make sure these goals are achievable and measurable. Some examples of measurable goals include increasing the time visitors spend on a Web site or increasing the number of people who sign up for a newsletter.

Make sure the goals are aligned with the organization’s OKRs. Learn more about this topic in this article.

Hypotheses to improve performance

In addition to setting objectives, I set hypotheses in which I predict the effects on the objectives made and how I realize them. If one of the goals is to improve conversion rates, I can predict, for example, that a larger and more visible call-to-action button will lead to more clicks.

Formulating hypotheses leads to a more focused approach. For example, create a longlist or shortlist that includes the hypotheses that might increase website conversion or SEO. Inventory well in advance which hypotheses need to be tested.

I include the following reason when determining which hypotheses to test:

• Qualitative audience research;
• Quantitative audience research;
• Brainstorm with departments such as sales/marketing;
• Testing the site among the target audience.

Testing certain elements

After setting goals and hypotheses, you need to determine which elements you want to test – think meta descriptions, titles and content structure. In doing so, choose the elements that will have the greatest impact on the objectives and hypotheses.

Systematically select different elements to have a good idea of the elements that have the most impact on the website. You should not change these too often, because a change can also have major negative effects.

Perform this section as follows: determine the objectives, then formulate the hypotheses and determine which elements will be tested. Then keep testing systematically.

Valuable insights

The results of A/B testing are very valuable, even if they are a bit less concrete. In addition to insight and knowledge about what works and what doesn’t and what changes to make, you will learn a lot about the preferences and behavior of the target audience. You can apply these results to future marketing and SEO strategies.

Not only can the negative results be acted upon, the positive results also provide much useful information. Implement the changes consistently on all relevant pages, thus improving uniformity of SEO performance. Whether it’s small changes to the content itself or larger changes to the appearance of the website. It is important to implement the positive changes quickly.

With the understanding of what works and what doesn’t, you can also determine the accuracy of the preconceived hypotheses. Prepare a summary of the hypotheses made, for example in Excel, and write the result along with it. This way, you can also check in the future which hypotheses have already been made and therefore do not need to be tested again.

Keep testing

The SEO world is constantly changing, so A/B testing must also be continuous. I implement the positive changes and immediately start new tests again to further optimize the website. Only a constantly improving website can handle the fierce competition in the dynamic SEO world.

Especially with large B2B websites, constant testing is necessary. Testing this website is more complicated as it consists of many different elements.

Summary

A website must constantly be improved and adapted to the target audience, so testing must be continuous. Only in this way will a website continue to count in the future.