A/B Testing

A/B testing pits two options against each other to compare their performance and discover what gives the best-performing option its edge.

Obtaining objective and reliable information about what customers want can be difficult. When developing a product, it is very easy to fall in love with the solution and forget that your users might not see things the same way you do. A/B testing gives you an objective view of how customers see and use your assets by pitting variations against each other in a one-on-one contest.

If you want to find ways to get great data for improving your products, A/B testing is for you. This article will review what it is, how it benefits product managers, and how to perform it.

What is A/B Testing?

Also known as split testing, A/B testing is a method for comparing two items or variations of an element. This apples-to-apples comparison allows you to determine which one performs better and why.

A/B testing is most popular in marketing and advertising. The practice allows marketers to identify the ads, marketing emails, or web pages that offer the best conversion rates. Analyzing a test’s results helps you deduce objective facts from subjective user behavior to improve your marketing strategies.

A/B testing’s ability to simplify subjective user behavior into qualitative and quantitative data like this makes it a valuable part of every product manager’s toolbox. Unlike a survey, which generates theoretical data, A/B testing tools measure real engagement with an asset. Thereby producing immediate and easy-to-analyze results.

The information derived from A/B testing is a very useful source of insights for designing better products. That is why companies such as Microsoft and Google each run north of 10,000 A/B tests each year on their products. And, as the examples below will show, it is also an effective tool for evaluating product features of every type.

Examples of A/B Testing in Product Management

How can A/B testing benefit you as a product manager?

Here are some examples of how you might use this testing method to produce better products for your end-users:

Improve User Interactions With Components on an Interface

Software development teams often use A/B testing to improve their products. This is because deploying and monitoring two slightly divergent variants of a piece of software to different users is pretty easy to do with the right A/B testing tools.

One example of how you might use A/B testing in software product development is moving or changing the size of a button to determine which variant causes more users to click. Another example might test two different arrangements of options in a menu to determine which pattern users find more intuitive.

Make Using a Tool More Tactile and Intuitive

A/B testing is a routine occurrence in software development. However, it also has a role to play when it comes to creating better physical products.

A/B testing in hardware product development can be more difficult and costly to pull off than it is with software. However, using it to compare variations of physical products can produce better insights than any 3D representation might on a computer.

For example, when designing the handle of a tool, you can have test participants try two different handle configurations. Interviewing them to find out which version they like best (and why) can help you come up with ideas for improvements. Then, the product design team can incorporate them in future releases.

Study the Effects of Design Choices on User Behavior

A/B testing is also useful for determining how abstract features affect user attitudes toward a product. You can, for example, test how two different design languages might affect your users’ perception of a product.

When used in this way, A/B testing might not seem at all distinct from focus group testing. However, there is one key difference: A/B test participants have the opportunity to test the product over a longer time. This allows them to arrive at conclusions that go beyond first impressions, whereas focus groups usually just give you an idea of their first impressions.

What are the Benefits of A/B Testing?

Are you still wondering why you should use A/B testing as a product manager? Here is a non-exhaustive list of benefits that might help you determine if it is right for you and the product that you own:

  • Its results reflect the actual response that the majority of users have to the tested asset.
  • It offers a true one-to-one comparison between different asset variants. This comparison significantly simplifies analysis and, if there is one, returns a clear winner.
  • It produces qualitative and quantitative data from otherwise subjective user impressions of your product.
  • It is repeatable. So, you can use it iteratively on an asset to guide its development toward a form that best resonates with your company’s user persona.

How Do You Perform an A/B Test?

A lot of different factors can influence the design, creation, and execution of an A/B test. These factors include the granularity of what’s being tested, the requirements of your A/B testing tools, and the type and amount of data you derive from your tests.

How you set up your test will depend on what you are testing, but A/B tests often include the five steps listed below. You can add steps to handle more complex testing, but more elementary tests can also use a simplified version of this format:

1. Determine What Data You Can Capture

Start by looking at your product and identifying the kinds of information you might be able to collect during an A/B test. Skipping this step can lead to wasting time and resources on experiments that might not deliver usable results due to measurement inaccuracies.

2. Develop a Hypothesis

Using the data you know will be available from the test, develop the hypothesis your test will investigate. Identify the opportunities for product improvement your experiment might create. Then, detail your assumptions of how users might react to the elements of your product that you’re testing.

3. Build the Experiment

Craft an experiment that investigates the hypothesis you developed. This step might require the involvement of other members of your team who can create element variants.

During this step, you also need to decide what metrics you want to collect and design methods for collecting your data. Selection of the A/B testing tools you’ll use also occurs at this stage.

Finally, use this stage to segment your user base and decide who receives different variants of the asset you are testing.

4. Run the Test

After building your experiment and verifying that it collects the right data, distribute the different versions of the asset to your user segments. Then, wait to see how the users in each group respond to the different versions.

How long you decide to run your test for and how much data you collect will vary based on several factors. However, it is important to gather enough data to see statistically significant results. If, for example, only ten users respond to an experiment sent to a pool of 100 participants, any insights you derive from the results might not reflect the actual preferences of your user base.

5. Analyze the Results

Finally, review the data that you collected from the A/B test and determine which of the two variants performed better. Supplementary data from interviews, surveys, or heat maps can help you figure out why the winning variant performed better.

Compare and Improve

A/B testing should never only be a tool for your organization’s marketing and advertising departments. As an objective way to measure your team’s theories about your product against real-world data, it gives you access to the information you need to create something your customers will love.