SEO A/B testing featured image.

SEO A/B Testing is often neglected, but ignore it and we can guarantee you’ll leave money on the table. It takes time and careful thought to set up the tests, and there is no guarantee that the tests you do will prove productive. Not only that, as there are no instantaneous results, and the time spent on them can seem boring and tedious. That’s why we make no apology for starting this article by emphasizing the importance of doing split tests!

SEO A B Split Testing: How Coderwall Grew 57% with one A/B test

Ever since Distilled has started talking about SEO a/b testing, the subject has been much debated in SEO circles. Many, many posts have been written on the virtues of SEO split testing. If you want to get hooked, just watch this series of videos by Dominic Woodman.

However, about 3 years ago it became clear just how easy it could be for even the most experienced marketers to neglect SEO a/b split testing. This happened when Coderwall did their tests long after everyone assumed they would have been doing them, and they experienced a huge surge in their business growth just through a very minor (or so it seemed) change in their meta-tagging.

Coderwall was already pretty advanced in their SEO, with a rich backlink profile and 130,000 pages of user-generated landing pages generating organic search traffic at the time. Nevertheless, they still achieved growth of a legendary 57% with one A/B test!

How to Split Test Without Harming Your Site’s SEO

Blindly following SEO best practice may actually be harming our websites, say some well-respected SEOs. As with articles on most other digital marketing channels, a great many SEO guides, Checklists, and How-Tos include no more than a line, paragraph, or short section about testing. They often glibly state that their students should make sure that they A/B split test any changes made to any website. They often say it is advisable to constantly test various optimizations to find the ones with the biggest impacts. Whatever you’re doing, testing is an integral part of digital marketing, they say. But what exactly does it mean to “test” something for SEO? It means that you have to test almost all aspects of your blog, from the wording of your ads to the very themes and even CMS you are using.

Image shows a diagram of the SEO A/B Testing process.The problem is that SEO doesn’t lend itself to standard test methods, and a lot of SEO actions don’t have either a rapid effect to measure or a clear comparative method for the assessment of the most successful outcome. It’s fortunate for other marketers that they have it easier when it comes to split testing. paid marketing is pretty straightforward to test: split test an ad, landing page, or offer and draw a direct line between change and ROI improvements. Unfortunately for SEOs looking to increase search rankings, search engines operate as “black boxes”, and rank sites relative to each other and the search term.

Split Testing vs AB Testing: What Are the Types of Tests?

A/b testing, aka “SEO A/B split testing”, is the practice of comparing two versions of a webpage or app against one another to determine which performs better. Think of it as a scientific experiment and always make sure you minimize the number of variables in any test. Typically limit the “split” to one to two webpage elements.

The truth is that running split tests can be scary, especially if you’re running them on a huge website with lots of potentials for things to go wrong. In Linkedin’s write up of the common a/b testing challenges in social networks, they stated that :

“Running large scale a/b tests is not just a matter of infrastructure and best practices; establishing a strong experimentation culture is also key to embedding a/b testing as part of the decision making progress.”

What we have certainly found is that to make SEO split-testing work for you, you need to practice. Provide your team with lots of opportunities to run experiments — so long as they’re done correctly and safely. As Linked In explained, you need to build an experimentation culture.

First, it’s important to understand that user experience and design come before link building. Put simply, these factors increase the value of traffic from any source, including search engines. If you aren’t doing split tests and usability tests to maximize the value of your site, what’s the point of doing SEO in the first place? But there’s even more to it than that. You can use traditional tests like these to improve your “pure” SEO. First off, if you don’t know anything about split testing, take a look at this beginner’s guide. It should be easier to follow than some of the more advanced stuff we’ve been talking about today. I also have to say that I completely agree with many of the gurus. You should test strategies, not page elements.

Start with a hypothesis and how you think the recipients will react and from that how you think each variant will perform. The actual experiment follows from that point, showing the different variants to users at random. Once the data is in, its the turn of analysis. In other words, using your metrics and data to determine which performed better. When done well, running a/b tests can help take the guessing out of website optimization and give you a real insight into changes you’re looking to make. Not only can you test variations, but you can collect actual data to back up your decisions.

A/B Split Test All Aspects of Your Business!

A chart showing the result of an a b split test.Convert is perfect for small to medium-size clients and businesses doing in-house optimization. It is well-loved for its exceptional customer support over live chat. Convert operates using an intuitive drag and drop system. You can create a/b, multivariate, multipage, and split tests using the provided visual editor and break out more the more advanced style sheet editor for dynamic pages, giving you full control of your content. It also boasts a smooth onboarding process of your CMS and eCommerce platform and seamless integration with Google Analytics. Personalization is also an option with over 35 different elements you can use to build customer profiles.

A/b testing sometimes referred to as split testing, is the process of comparing two versions of the same webpage, email, or other digital assets to determine which one performs better. This process allows you to answer important business questions, helps you generate more revenue from the traffic you already have, and sets the foundation for a data-informed marketing strategy.

A/b testing is usually used to refer to when you experiment with two or more landing pages at the same time, comparing the data to see which page performs best for your business. Although the process is called a/b or “split” testing, it can be performed on as many pages as you need. Doing the split test means that you’re going to show slightly different versions of your site to a segment of your traffic, and compare the results. If the varied sample shows the best result after a significant number of hits you consider the test successful and from then on adopt the new, more successful of the tested variants. To begin a/b testing, first, you must determine the areas of your landing page that you want to test. Then, you will need to create new versions so that you can experiment with these elements. Areas of your landing page that may benefit from a/b testing include the text, the images, the layout, the font and font size, use of color, etc.

Split Testing Buttons By Color

While most marketers recommend that you must start your experimentation journey by running small a/b tests on your website to get the hang of the entire process. But, in the long run, sticking to plain vanilla a/b testing method won’t work wonders for your organization. For instance, if you are planning to revamp one of your website’s pages entirely, you ought to make use of split testing. Meanwhile, if you wish to test a series of permutations of CT buttons, their color, the text, and the image of your page’s banner, you must use multivariate testing.

Engaging page design improves user experience with amplified site quality and rankings. Clean, impressive layouts can either guide the eyes effortlessly down the page or fail to retain visitors — and SEO testing can determine which your current design is. You can select your two layouts from a range of column widths, appealing fonts, and color schemes. However, you’ll probably only make minor changes in layout rather than substantive design modifications. Consider split testing your buttons and forms, too, during layout checks. Implementing an SEO tester for design can control the path that people take as they scan your content, giving you a higher chance of converting users.

Now that you’ve successfully optimized our site it’s time to look at some great tools around the web that you can implement to continue making improvements. In the world of e-commerce, making minor tweaks to the design and layout of your site can have a huge impact on the number of sales that you make. While this type of testing isn’t directly related to search engine optimization, learning how to a-b-test design tweaks on your site can clarify exactly how to present your information to visitors that you’ve worked so hard to acquire.

What Is The Difference Between A/B Testing, Split Testing, and Multivariate Testing?

Seo testing is essentially the same as hypothesis testing in CRO, but with a couple of key differences. First, we’re not sampling users landing on one page, but rather two or more sets of pages. Second, we don’t get to use a statistical test like chi-squared or the two-sample t-test. One of the biggest differences is that we’re comparing the two-time series and not comparing two averages.

A/b testing is the process of creating two completely different versions of given landing pages, (homepage, product page, promotional offering), and allows companies to determine the impact of differences to key landing page elements such as design, content, functionality, product pricing, and functionality changes. Creating multiple versions of a specific landing, and splitting the traffic between the two unique pages provides insight for companies to identify which specific design, content, or pricing point differences is providing the most impact and driving higher sales and conversions.

Ab testing (also known as split testing or multivariate testing) is a web design and development term that’s used­ to describe the testing of different elements on a website. It involves changing different website elements, where the impact of the different changes can be measured towards reaching a certain goal. A/b testing is too often ignored or overlooked by designers and developers as a way to improve a websites’ design and aid in its development. Whether its the landing page or checkout page, ab testing can help optimize the whole customer journey from start to finish. When done right, ab testing is a very effective method of increasing the conversion rate on a website.

The Power of Split Testing

A/b testing is a powerful technique that helps you improve your website with real data. Instead of guessing whether a design or post title is the best option, you can simply test it and know for sure. But if you want to run these tests, you’re going to need a WordPress a/b testing plugin to help you create and track your experiments.

The v/c splitter pro plugin adds a/b split testing options helpful for anyone using the powerful page builder. The VC splitter testing module is available when building visual composer layouts. Simply create your variations within the module and give your split test a name. To check performance, all you have to do is go to the page editor and click on the VC splitter module – it will update with new stats each time you open/view it.

Conducting an SEO split test

Google backs split testing in Google Analytics.

Google backs split testing in Google Analytics.

A/b testing allows you to determine which version of your website is working better in terms of reaching your goals. Ultimately resulting in increases in leads, hits, click-through rates, etc. It allows you to conduct an experiment on virtually anything and implement the outcome that engages the majority of your consumers – enabling you to optimize your website to exactly what increases your conversion rates. Google backs split testing and offer the option to conduct an experiment through Google Analytics. However, we do end up wondering what Search Engine Robots see on your site when you’re conducting an a/b test!

Myth: Conversion Rate Optimization equals SEO A/B Split Testing

The biggest myth that most split testers frequently adhere to is that conversion rate optimization equals a/b split testing. But this is not true. Testing is an important way to validate your ideas and make sure that they improve website performance. But if you refuse to occasionally redesign your whole site experience, or add new capabilities to your marketing technology stack you won’t gain the biggest possible benefits, Some will change their whole business model including the nature of their customer touch-points and back-end workflows, they see their testing as that important. Do you testing in a narrow sense and you will never be likely to unlock the true value of your business. By relying only on testing, and focusing on the testing velocity you will do what is familiar and the easy, and continue to fight with one hand tied behind your back.

Beginner’s Guide to SEO Split Testing

G2crowd reports that:

“60 percent of companies believe a/b testing is highly valuable for conversion rate optimization. ”

A/b testing is an effective way to optimize your business systems. Simple page testers simplify the set up for split tests. It’s an easy-to-use WordPress plugin for beginners because it requires no coding. Plus, you don’t have to worry about tests affecting your SEO rankings. The tool creators follow strict guidelines and recommendations from the Google Webmaster site. You also can track unique visitors to each variation in your split test. To get even more value, try the premium version of the plugin. It comes with in-built conversion tracking and automatic statistical confidence calculations. With an easy onboarding process, you will be testing in just a few minutes.

What is Split Testing?

A/b testing (also known as split testing or bucket testing ) is a method of comparing two versions of a webpage or app against each other to determine which one performs better. Ab testing is essentially an experiment where two or more variants of a page are shown to users at random, and statistical analysis is used to determine which variation performs better for a given conversion goal. Running an ab test that directly compares a variation against a current experience lets you ask focused questions about changes to your website or app, and then collect data about the impact of that change.

Consumer-focused companies have typically been ahead of the curve when it comes to search engine optimization, including SEO split testing. The practice was pulled further into the spotlight by Pinterest when growth engineer Julie Ahn shared a famous post on their successful SEO a/b testing framework. According to Julie, SEO is one of Pinterest’s biggest growth drivers, but in the past, it had been difficult to manipulate it for predictable growth.

“You might have a good traffic day or a bad traffic day and not know what really triggered it,”

she wrote recently,

“which often makes people think of seo as magic rather than engineering. ”.

A/b testing, also known as split testing or bucket testing, is a tried-and-tested tool in the SEO toolbox. Essentially, when you make a change to a web page, you need to compare different versions of the page to see which performs best and isolate the changes that are more valuable than others. By serving users with different versions of a page at random, you can better determine which version of the page performs better. You will no longer have to wonder whether or not your changes are making a difference, and this certainty can help drive further changes, which you can trust to turn into further revenue.

The Benefit of Split Testing

The most surprising thing about a/b split testing for me was finding out I could easily get 10x results by doing “stupid” things. For example, the only difference in the test may be something nominal and unlikely to even be noticed such as reversing line 2 and line 3, that’s it. One may never know the precise reason why, but my theory is, the 2nd ad puts the benefit first before it tells you the form you receive the benefit in. That makes a lot of sense to me.

Consistently test your CTA button text copy as your buttons are elements that visitors will definitely read before clicking on them. The copy on any CTA button has to most importantly be very clear. Site visitors have to understand what it is you want them to do before they can determine how completing this CTA will benefit them. When creating a hypothesis to split test the copy for CTAs, always keep the users and their needs in mind. Try to keep the CTA copy consistent with your business persona and products or services.

Seo can take a long time to pay off, so you might be waiting a while for results to start coming in before you find the winner. But who said that SEO split-testing had to rely completely on organic strategies? Danilo Godoy of search evaluator uses Google Ads data to run his split tests before mapping the changes over to organic efforts And, here we quote him:

“While the results of an a/b test for paid marketing can generally be assessed within a few days, SEO is a long game, [in] which [the] rules are more complex and constantly evolving. Google deploys minor changes in the algorithm daily.”

SEO A/B Testing Summary

SEO A/B testing (sometimes referred to as split testing) is the type that gets the most attention, but there are other types of tests that you can run to get information on how your visitors behave.

It’s just a way of comparing two versions of a webpage or program contrary to one another to identify which performs better. This type of testing is an experiment where several variations of a full-page have been shown at arbitrary for users. Statistical analysis can be subsequently employed to ascertain which version works for a conversion objective. Running an a/b evaluation that directly contrasts a version against a current experience enables you to ask focused questions regarding changes to your website or program, then collect data.

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