Your go-to resource for acronyms, jargons, terminology, and useful words for product and customer experience teams.


A/B Test

What is A/B Testing?

The purpose of an A/B test is to compare the performance of two items or variations against one another. This method is commonly used in product management to identify the best-performing option. For example, two variations of a new user interface could be tested. The variation that receives the most user engagement would be the winner of the A/B test.

A/B testing is a great way to see which version of your product will be more successful with users. This method involves showing multiple versions of your product to randomly selected users and then analyzing the results. Product managers can use A/B testing to develop products that will have the most appeal to users.

Many benefits come with using A/B tests, which include: 

  • You as a marketer (or product manager) can focus on testing particular elements 
  • The results are immediate and easy to understand 
  • Unlike surveys, where users’ answers might not be accurate, A/B tests measure real engagement with the asset

Why is A/B testing valuable?

A/B testing is so valuable because it allows teams to see how actual users respond to a single variant of an asset. This type of testing is essential because it provides accurate data that can help teams make informed decisions about their marketing strategies.

An A/B test is a great way for marketing teams to learn which of their sales messages performs better. With an A/B test, they can send out two nearly identical emails with just one small change – like the subject line or call to action – and see which element resonates more with readers. This helps teams to focus on what works and continue to create compelling content that drives results.

If a team continuously employs A/B tests to measure the effectiveness of each element, over time that team will be able to build an asset (advertisement, product, website) that resonates with the company’s user persona. This is because they will have a clear understanding of what works and what doesn’t through real-time data that they can then apply to their project. Not only will this save the team time and energy, but it will also result in a much higher quality final product.

Why should Product Managers use Testing?

A/B testing is a method of experimentation where two versions of a product feature, layout, or element are released to a randomly selected segment of users to see which one performs better. This technique has commonly been used in marketing and advertising, but product managers can also use A/B testing to build better products.

By conducting A/B tests, product managers can learn which versions of new features, layouts, or other elements users respond to most favorably, and use that information to improve their products.

How do you run an A/B test?

A/B Testing is a process that product managers use to compare two versions of a product to see which one performs better. The approach offered by Product School has five stages:

Stage 1: Determine the data you’ll be able to capture.

Before you start building your experiment and running tests, take some time to determine what types of information you can collect and analyze. This way, you won’t waste time and resources on an experiment where you can’t accurately measure the results.

Stage 2:  You will develop your hypothesis. 

Based on the data available to your team, you will want to identify opportunities for your experiment and formulate a theory about how users will react to a specific element of your product.

For example, you might assume that users will want the steps required to complete a task using your new feature to be ordered in a particular sequence. That is your hypothesis.

Stage 3: Build experiment

Now that you’ve developed your hypotheses and planned your experiment, it’s time to start building it. This will involve creating a variant of your planned feature, using the same functionality but with different steps.

During this stage, you’ll also need to generate different segments of your user base that will receive the variants of your new feature. You’ll also want to define the metrics you’re going to measure. Will you gauge user preference for one variant based on surveys after they’ve had a chance to use the product?

Stage 4: Run your test

Now that you’ve created different versions of your new feature, it’s time to send them out to your user segments and wait to see which groups respond best to each version. Your team should take into consideration how long to run your A/B test, how much data to collect, and so on. This will differ for each company, but it’s important to gather and analyze enough data so you have a statistically significant sample of your user base.

Stage 5: Measure your test

In stage 5, you will measure the results of your A/B test and decide which of the two features (or layouts, color schemes, etc.) had the most positive response or engagement from users. To do this, review the data you’ve collected and look for patterns or themes. After that, you can make a decision about which option is best for your company or product.