Split Testing: Data-Informed Decisions On Which Version To Keep

by Joost Nusselder | Updated on:  09/12/2022

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In marketing and business intelligence, A/B testing is jargon for a randomized experiment with two variants, A and B, which are the control and treatment in the controlled experiment.

It’s often called split testing because you can usually test more than two versions at the same time, which would make it an A/B/C test or even more.

It is a form of statistical hypothesis testing with two variants leading to the technical term, Two-sample hypothesis testing, used in the field of statistics.

What is split testing

Other terms used for this method include bucket tests and split testing but these terms have a wider applicability to more than two variants.

In online settings, such as web design (especially user experience design), the goal is to identify changes to web pages that increase or maximize an outcome of interest (e.g., click-through rate for a banner advertisement).

Formally the current web page is associated with the null hypothesis.

As the name implies, two versions (A and B) are compared, which are identical except for one variation that might affect a user’s behavior.

Version A might be the currently used version (control), while Version B is modified in some respect (treatment).

For instance, on an e-commerce website the purchase funnel is typically a good candidate for A/B testing, as even marginal improvements in drop-off rates can represent a significant gain in sales.

Significant improvements can sometimes be seen through testing elements like copy text, layouts, images and colors, but not always.

The vastly larger group of statistics broadly referred to as Multivariate testing or multinomial testing is similar to A/B testing, but may test more than two different versions at the same time and/or has more controls, etc.

Simple A/B tests are not valid for observational, quasi-experimental or other non-experimental situations, as is common with survey data, offline data, and other, more complex phenomena.

A/B testing has been marketed by some as a change in philosophy and business strategy in certain niches, though the approach is identical to a between-subjects design, which is commonly used in a variety of research traditions.

A/B testing as a philosophy of web development brings the field into line with a broader movement toward evidence-based practice.

Using split testing can skyrocket growth because the results compound. Getting more traffic because of a successful test gets you more leads.

Then testing the offers to put in front of those leads gets you more conversions.

That is why A/B testing is often the key to a successful marketing campaign.

Also read: this is how I used SEO Tag Tester to test headlines and increase website traffic with 19%

In this blog post, we’ll cover split testing, how you can set up your test, and provide examples of successful split tests in marketing.

The Difference Between Conducting a Split Test and an AB Test

Split testing and AB testing are two of the most popular methods for optimizing websites.

Both involve making changes to a website to improve user experience, but they differ in how those changes are implemented.

AB testing is a method of comparing two versions of a web page or app against each other to determine which one performs better. Split testing can involve more versions (ABC testing) or can involve splitting traffic between different pages (split URL testing).

Split URL tests require more significant design changes than AB tests and thus require back-end operations that marketing teams cannot make without help from technical teams.

This test is ideal for major design changes like completely changing the home page’s layout or introducing new features to existing pages.

Split Testing vs MultivariateTesting (MVT)

Split testing and multivariate testing (MVT) are two distinct types of experiments used to measure the performance of a website.

With split testing, you create two or more page versions and show each visitor one of those versions. Best for testing single elements or whole page changes. MultivariateTesting tests each separate element change in combination with other element changes you make to see which combination of changes works best.

I tested different email opt-in positions for example, to see which combination of elements would work best:

  1. a pop-up
  2. a lightbox
  3. a sticky header bar
  4. a signup form right under the title of the article

This allowed me to see which combination had the highest sign-ups.

The pop-up won, but adding the lightbox and signup form underneath the title did little to add to the conversion, so I didn’t have to implement those.

Benefits of Split Testing

The main benefit of split testing is that it allows marketers to make informed decisions about their campaigns based on data rather than guesswork.

By running tests and analyzing the results, marketers can quickly identify what works and what doesn’t work when it comes to driving conversions.

This helps them optimize their campaigns for maximum effectiveness without wasting time or money on ineffective strategies.

There are several types of split tests that marketers can use depending on their goals and objectives.

A/B tests compare two versions, multivariate tests test multiple variables at once, funnel tests evaluate different steps in the customer journey, and personalization tests assess personalized content.

Each type has its advantages and disadvantages, so it is important to choose the right one for your specific needs before beginning your test.

Split testing is an effective way to optimize your website and maximize its potential. Next, we will explore the benefits of split testing and the different types of tests available.

Key Takeaway: Split testing is an essential tool for any marketer who wants to optimize their website and increase conversions. It involves creating two versions of the same page or campaign and then measuring how each version performs.

How to Set Up a Split Test

Split testing is a powerful tool for marketers to measure the success of their campaigns.

By running split tests, you can compare two or more versions of your website, email, or ad and determine which one performs better.

Setting up a split test requires careful planning and analysis to get accurate results.

Setting Goals for Your Test

Before starting any split test, it’s important to set clear goals that will help you measure the success of your campaign.

For example, if you’re running an email marketing campaign, decide what metric you want to track, such as the open rate or click-through rate.

This will give you something concrete to measure against when analyzing the results of your test.

Choosing the Right Variables to Test

Once you have established your goal for the test, it’s time to choose which variables you want to compare between different versions of your content.

Common elements that are tested include headlines, images, colors, and copywriting styles.

It’s important not to change too many things at once so that each variable can be evaluated on its own merits without being influenced by other changes in the design or content.

Once a split test runs for several weeks, it is time to analyze the results. Compare each version based on the metric chosen before starting the test (e.g., open rate).

Suppose there is a significant difference between the two versions.

In that case, this indicates which should be used going forward and provides valuable insights into what works best with customers/audience members who received those emails/ads/websites, etc.

By setting clear goals, choosing the right variables to test, and analyzing the results of your split tests, you can effectively optimize your niche website for better performance.

Now let’s look at how to ensure your split tests are successful.

Key Takeaway: Split testing is an important tool for marketers to measure the success of their campaigns. When setting up a split test, it’s essential to set clear goals and choose the right variables to test, such as headlines, images, colors, and copywriting styles.

Examples of Split Tests in Marketing

It allows them to test different versions of their website or marketing materials to see which performs better.

By running split tests, marketers can optimize their campaigns and increase conversions.

Email Subject Line Tests

Email subject lines are an important part of any email campaign. Split testing allows you to compare two different subject lines and determine which one will get more opens and clicks from your audience.

For example, suppose you’re sending out an email about a new product launch. In that case, you could test two different subject lines such as “Introducing Our New Product” versus “Unlock the Power of Our New Product” to see which one resonates with your audience more.

Landing Page Tests

Landing pages are essential for converting visitors into leads or customers.

With split testing, you can try out different page designs or copywriting styles on your landing page to find the most effective version that drives the highest conversion rate possible.

For instance, if you have a signup form on your landing page, you could test two versions – one with just basic information fields like name and email address versus another with additional questions such as job title and company size – to determine which form yields higher quality leads for your business.

Call-to-action button tests are an essential part of any online marketing campaign, as they encourage people to take action on whatever you want them to do (e.g., buy now).

Split testing can be used here, too, by comparing two variations of call-to-action buttons – such as color scheme (red vs blue), shape (square vs round), or text (buy now vs add cart) – to determine which works best for motivating people to act quickly and easily without hesitation.

Split testing is an essential tool for any marketer, as it helps to ensure that campaigns are optimized for maximum success.

Key Takeaway: Split testing is an important tool for marketers to optimize their campaigns and increase conversions. It allows them to test different versions of their website, marketing materials or call-to-action buttons to determine which ones perform better.

Best Practices for Running Effective Split Tests

Split testing is an important tool for marketers looking to optimize their websites and campaigns.

Split tests, also known as A/B tests, compare two versions of a web page or campaign against each other to determine which one performs better.

By running split tests, marketers can make informed decisions about improving their websites and campaigns based on data-driven results.

When it comes to running effective split tests, some best practices should be followed to get the most out of your experiment.

Test large ideas

People will tell you to test small changes and see what effect that has. But that’s the trap.

Sure, you don’t want to test making several changes at once, but it’s best to test a whole concept at once instead of just one tiny element.

Test the look and feel of your page, not just the color of the call-to-action button. Test what emotional responses you can trigger by tweaking the whole design and get far better results.

Don’t just change the text on the call to action button. Test what action you want to drive and change your whole header copy to match the idea you have for the call-to-action.

But whatever you do, don’t change two different concepts at once. That’s what people (should) mean when they say to test small things at a time.

When conducting a split test, it’s important not to make too many changes at once, as this could lead to inaccurate results or confusion when interpreting the data.

So don’t test both the email opt-in and a product sale in one test but test those separately.

Use Statistical Significance To Make Decisions

Once you have run your split test for long enough so that you can draw meaningful conclusions from it, it’s important then use statistical significance when interpreting your results in order to ensure accuracy and avoid false positives or negatives due random chance factors influencing outcomes during shorter time frames where sample sizes may be smaller than ideal.

In general, 95% confidence level is considered statistically significant, but this varies depending on individual circumstances, so always consult experts if unsure about any aspect related to statistics before concluding your experiment’s data points.

While optimizing conversions is a key goal for any marketer running split tests, it is also essential not to forget user experience.

If users do not find value in interacting with website elements, they will not convert no matter how well-optimized those elements might be technically speaking.

Therefore, it is important to always keep the user experience as the top priority while conducting experiments; otherwise, all efforts may end up being wasted effort regardless of how much optimization was done beforehand.

Split testing is an essential part of optimizing a niche website.

By following the best practices outlined in this article, you can ensure that your split tests are effective and yield meaningful results.

Key Takeaway: Split testing is an important tool for marketers looking to optimize their websites and campaigns. To ensure accurate results, it’s best practice to: 1. Start with small changes and measure the impact of each one; 2. Use statistical significance when interpreting data; 3. Prioritize user experience over-optimization goals.

Common Mistakes When Running Split Tests

However, if done incorrectly, it can be a waste of time and resources. Here are some common mistakes to avoid when running split tests:

Not Setting Clear Goals Before Starting the Test

It’s important to have clear goals before you start any split test. Ask yourself what you want to learn from the test and how that information will help improve your campaign performance.

Without having specific objectives in mind, it will be difficult to measure success or failure after the test has been completed.

Not Allowing Enough Time for the Test To Run

Split tests need enough time to run to collect enough data for accurate results.

If you don’t give them enough time then there won’t be sufficient evidence available for analysis which could lead to wrong conclusions being drawn about why certain changes affected conversion rates or not.

Make sure that each test runs long enough so that all variables are considered before making decisions based on its results.

Once your split test has been completed, it is essential to analyze the results correctly to make informed decisions about what changes should be implemented for future campaigns or projects.

Consider metrics such as click-through rate (CTR), bounce rate, average page views per visitor, etc., as well as qualitative feedback from customers through surveys or interviews to gain a better understanding of how successful each variation was during the experiment period.

Make Changes Based on Your Results

Split testing is a great way to determine what works best for your website.

By running tests, you can determine which elements of your site are most effective in converting visitors into customers or leads.

It’s important to remember that if one variation of the test turns out to be more successful than the others, then it should become the default version on your website.

On the other hand, if no variations perform better than any others, then it’s time to move on and try something else.

To get started with split testing, decide on a variable or group of variables you want to test and create different versions of your page accordingly.

For example, maybe you want to see how numbers in headlines affect conversions – so create multiple versions with different headline formats and track their performance over time.

Once you have enough data from these tests, analyze them carefully and make changes based on what works best for your audience.

You may also consider running AB tests as part of split testing – this involves comparing two versions side-by-side against each other rather than just measuring individual elements separately.

This can help give an even clearer picture about which version performs better overall when compared directly against another option.

Additionally, don’t forget about multivariate testing where multiple variables are tested at once – this could provide valuable insights into how various combinations work together for maximum impact!

Finally, keep in mind that split testing isn’t just limited to websites either; it can be used across many marketing channels such as email campaigns or social media posts too!

So take advantage of all available opportunities by tracking results closely and making changes based on those findings – after all, why not use every tool at our disposal?

Split testing is an important tool for marketers, but it can be easy to make mistakes that could harm the success of your test.

Key Takeaway: Split testing is a great way to optimize marketing campaigns, but it’s important to avoid common mistakes such as not setting clear goals before starting the test and not allowing enough time to run.

Statistical Modeling: Bayesian vs. Frequentist Approach

Split testing is a powerful tool for marketers to understand what works best for their target audience.

It’s essential to understand the statistical modeling on which all experiments run, as it can have a significant impact on the outcome of your test.

The two main models used in split testing are the Frequentist and Bayesian approaches.

The Frequentist model draws conclusions based on how many times an event has occurred throughout an experiment, requiring a larger sample size to ensure statistically significant results.

This approach isn’t ideal for pages or websites with low traffic since it requires more time and data collection than other methods.

On the other hand, Bayesian statistics rely on predicting likelihood rather than counting occurrences.

Tests conducted using this model don’t require as much data or time as those done through Frequentism – meaning they can be completed faster and still provide actionable insights even if you have low website traffic numbers.

For these reasons, we at VWO advocate using Bayesian statistics when running split tests over any other method available today.

FAQs about Split Testing

What is the meaning of split tests?

It involves showing different versions of the same page to different visitors and measuring how each version affects user behavior such as click-through rate or conversion rate. Marketers use split tests to optimize their website for maximum performance and improve the overall user experience. By running split tests, marketers can identify which elements on their website are most effective in achieving desired goals and make changes accordingly.

Why is split testing important?

Split testing is an important tool for marketers as it allows them to measure the performance of different versions of their website. By comparing results from two or more variations, they can determine which version works best and optimize their website accordingly. Split testing also helps marketers identify areas that need improvement and make informed decisions about changes to their websites in order to increase conversions and maximize ROI. Split testing is an invaluable tool for marketers as it allows them to make data-driven decisions that can have a significant impact on their website’s success.

What is split testing in a laboratory?

It involves randomly showing different versions of the same webpage or feature to users and then measuring how each version affects user behavior such as clicks, purchases, sign-ups etc. Split testing allows marketers to optimize their website or product by understanding what works best for their target audience. This helps them make informed decisions on design changes that will improve customer experience and ultimately lead to higher conversions.

What is split testing in ads?

Split testing in ads is a method of comparing two or more versions of an advertisement to determine which one performs better. It involves running multiple versions of the same ad simultaneously and measuring their performance against each other, such as click-through rate, conversion rate, cost per acquisition etc. Split testing helps marketers identify what works best for their target audience so they can optimize their campaigns for maximum ROI.


Split testing is a great way to optimize your marketing efforts and get the most out of your campaigns.

It allows you to test different versions of content, products, or services to find out which one performs best with your target audience.

By understanding what works and what doesn’t, you can make better decisions about how to market effectively.

Split testing requires some effort upfront but it’s worth it in the long run as it helps you maximize ROI from every campaign.

So if you’re looking for ways to improve your marketing performance, split testing is definitely something worth considering!

Also read: these are the best tools for A/B testing your niche site reviewed

Joost Nusselder is The Content Decoder, a content marketer, dad and loves trying out new tools en tactics. He's been working on a portfolio of niche sites since 2010. Now since 2016 he creates in-depth blog articles together with his team to help loyal readers earn from their own succesful sites.