As the shift to digital accelerates with each passing day, marketers are working hard to find the most effective strategies for search engine optimization. A big part of success here is understanding of how users respond to your website.
And the best way to find this information involves a range of website testing methods.
These tests enable us to experiment with multiple factors and extract the best outcome. By putting a control page against a test group, we can check for impact to conversions and UX.
A/B and multivariate testing are popular testing styles, helping thousands of SEO experts globally. This post will discuss the right way of performing these tests and also includes some bonus tips.
So, let’s begin:
Commonly known as split testing, A/B testing involves changing page elements and analyzing their impact. It means that we alter some aspects of the page and compare them with the original page when various audience segments view it.
Here, the original page (former page) is variant A, and the new one is variant B.
This simple test helps know the key elements responsible for higher conversions. When the test compares two pages and highlights conversion rates, the page with higher conversions is ideal.
Furthermore, we usually check CTA messages and color changes through this test. It clears the doubts and gives us accurate results.
For instance, let’s say you are optimizing a website for cleaning, and you are unsure what the best CTA messages might be. Instead of taking a risk, test the three messages, which were:
- Claim Your Free Service
- Try for Free
- Learn More
Out of these three, the first one led to the highest conversions on our own A/B Test.
In comparison to A/B testing, multivariate testing is complex. Instead of just telling us the success of an entire page, it analyzes different combinations of a page. Therefore, it is a better and more helpful approach.
Additionally, it eradicates the limitation present in A/B testing, which is about one element’s impact on another. Since it works on studying the combinations, it helps us understand which parts work together. Furthermore, we gain an understanding of the relation of multiple elements.
Some common uses of multivariate testing include testing for body texts, buttons, images, and headlines.
Impact of Multivariate and A/B Testing on SEO
Although both of these tests help improve the web pages and conversion rates, we should be aware of their negative aspects. Yes, many SEO experts are unaware of the adverse outcomes of these tests.
It is essential to understand that such tests involve duplicating pages with just a slight difference. Besides this, they also change the page content.
Have a look at some common issues that can arise due to improper use of these testing methods:
Cloaking appears when search engines notice a different version of the page available to the audience. Various test versions can also cause cloaking.
This is against the rules of Google Webmaster. Thus, it can result in permanent site removal from the search results or decrease the rank drastically.
A/B testing involves different versions of the URL. This creates confusion for the search engines as the search engine might get different URLs at other times.
Thus, the search engine fails to understand which version is the primary page. Consequently, it raises problems in indexing.
A/B testing can sometimes create duplication issues. If we do not manage things properly, we will fail to discriminate one page from another. Since search engines strictly discourage duplication, they can permanently hinder your SEO efforts.
Best Advice from the Search Engines
Be it Google or Bing; every search engine gives us some guidelines about website testing. Let us have a look at these recommendations:
Google always appreciates professional, consistent, and high-quality sites. It will never appreciate if your site will show a different version every time.
Being the top global search engine, it wants to make sure that the page shown to the audience is original. Furthermore, it will investigate that the user sees the same page as promised by the search engine, every time someone clicks through to it on the SERPs.
You show well-written and comprehensive content to Google. However, when the users visit your site, they only see a few lines along with a single image.
This will directly impact the reliance of users on Google. Therefore, Google advises all of us to show the real picture of the site.
In the case of A/B testing, we should show such pages that most users will see. For more details on testing, you can have a look at the best practices for website testing.
This is a comprehensive guide given by Google and covers almost every aspect.
For understanding the critical rules of other search engines, I got in touch with Fabrice Canel. He is a Program Manager at Bing, and his recommendations are as follows:
- Always give version A to the search engine.
- Bing does not consider slight differences as cloaking.
Additional Tips for Testing
- Be sure that you are giving your primary content to Google. Also, consider tags, titles, and internal links.
- Remember not to make drastic differences between the variant and the real page. If the variant shows content related to life insurance and the real page is about travel, it will raise a red flag.
- Use the canonical tag to show a signal of a real page for indexing.
- Always make the content pages on the original page.
- Never over-do your testing. Also, perform it weekly, monthly, or as required.
- Never perform tests during the migration of a site.
In short, A/B and Multivariate testing can help you select the best elements for your web pages. However, these testing methods come with various limitations. We should understand the risks of running such tests.
Problems like cloaking, page duplication, and inconsistent redirects can arise. For resolving such issues, we should understand the guidelines given by the search engines.
Furthermore, showing the real page, avoiding drastic differences, using canonical tags, and avoiding tests during site reconstruction are a few tips for better results.
Feature Image Credit: CC4.0, via SEObility.net
Disclaimer: The views and opinions stated in this post are that of the author, and Return On Now may or may not agree with any or all of the commentary.
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