A/B testing, also known as split testing, is a method for comparing the results of two different versions of a web page or email campaign to see which one performs better. By randomly serving visitors different versions of a page (A or B), you can measure which one leads to more conversions, sign-ups, clicks, or whatever goal you’re trying to achieve.
A/B testing is an essential tool for any digital marketer who wants to improve their campaigns and website. It’s easy to set up and use, and it can provide valuable insights into what works and what doesn’t. In this article, we’ll explain how A/B testing works and show you how to get started with your own tests.
How Does A/B Testing Work?
A/B testing works by showing visitors two different versions of a web page or email (Version A and Version B). The version that performs better is the winner, and the one that performs worse is the loser.
To run an A/B test, you need to create two versions of a web page or email (one version with the change you want to test, and one without the change). You then need to show each visitor a randomly selected version (A or B) and track which version performs better.
A/B testing is a powerful tool, but it’s important to understand the limitations. First, A/B tests can only test one change at a time. So if you want to test two changes (e.g., a new headline and a new call-to-action), you need to run two separate tests. Second, A/B tests can take a long time to reach statistical significance (usually a few weeks), so you need to be patient.
What Can You Test With A/B Testing?
Almost anything! Here are some examples of things that you can test with A/B testing:
-Web page elements: headlines, calls-to-action, images, etc.
-Email subject lines
How to Set Up an A/B Test
There are two parts to setting up an A/B test: creating the versions of the web page or email, and then setting up the test itself.
Creating the versions: To create the versions of the web page or email, you need to make a copy of the original (Version A) and then edit the copy to create Version B. For example, if you’re testing a new headline, you would create two headlines and then randomly show each headline to visitors.
Setting up the test: Once you have the two versions of the web page or email, you need to set up the test. There are a few different ways to do this, but the most popular method is to use an A/B testing tool.
There are several A/B testing tools available, but some of the most popular ones are Google Analytics, Optimizely, and Visual Website Optimizer.
To set up the test, you need to create a “experiment” in your chosen tool and then specify the web page or email that you want to test. You also need to specify the goal of the test (e.g., increased conversion rate), and how long you want the test to run for.
Once the experiment is set up, the tool will take care of showing visitors the different versions of the web page or email and tracking the results.
Common Pitfalls of A/B Testing
A/B testing is a powerful tool, but there are a few common pitfalls that you need to be aware of:
–Not enough traffic: A/B tests require a significant amount of traffic to reach statistical significance. If you don’t have enough traffic, the results of the test will be unreliable.
–Change fatigue: If you run too many A/B tests, visitors will become “change fatigued” and begin to ignore the changes. This can lead to inaccurate results and make it difficult to interpret the data.
-Local optimum: It’s easy to become fixated on small changes that have a big impact on the results of the test. However, these changes are often not scalable or sustainable in the long-term.
–Incorrect conclusion: A/B tests can be tricky to interpret, and it’s easy to reach the wrong conclusion. Be sure to consult with a statistician or experienced A/B tester before making any decisions.
Best A/B Testing Tools
A/B testing is a crucial tool for any digital marketing campaign. By testing different versions of your website or app, you can learn what works best for your customers and make sure that your campaign is as effective as possible. There are a number of different A/B testing tools on the market, but not all of them are created equal. To help you choose the right tool for your needs, here are a few of the best A/B testing tools for digital marketing campaigns:
• Google Optimize: Google Optimize is a free tool that makes it easy to run A/B tests on your website. It integrates with Google Analytics, so you can easily track your results.
• Visual Website Optimizer: Visual Website Optimizer is a powerful A/B testing tool that includes a wide range of features, such as heatmaps and click maps. It’s available as a free trial or paid subscription.
• Unbounce: Unbounce is an A/B testing tool that specializes in creating landing pages. It offers a range of features, including built-in templates and integrations with popular email marketing platforms.
• AB Tasty: AB Tasty is an A/B testing platform that includes features like behavioral targeting and real-time reporting. It’s available as a free trial or paid subscription.
A/B testing is a powerful tool for any digital marketing campaign. By testing different versions of your website or app, you can learn what works best for your customers and make sure that your campaign is as effective as possible. A/B testing is a crucial tool for any digital marketing campaign. By testing different versions of your website or app, you can learn what works best for your customers and make sure that your campaign is as effective as possible.
How do I set up an A/B test?
To set up an A/B test, you need to create a “experiment” in your chosen tool and then specify the web page or email that you want to test. You also need to specify the goal of the test (e.g., increased conversion rate), and how long you want the test to run for.
What are some common pitfalls of A/B testing?
Some common pitfalls of A/B testing include: not enough traffic, change fatigue, local optimum, and incorrect conclusions.
What is the best A/B testing tool?
There is no one “best” A/B testing tool. However, some popular A/B testing tools include Google Optimize, Visual Website Optimizer, Unbounce, and AB Tasty.
How do I interpret the results of an A/B test?
It’s important to consult with a statistician or experienced A/B tester before interpreting the results of an A/B test. This is because A/B tests can be tricky to interpret, and it’s easy to reach the wrong conclusion.
When should I stop an A/B test?
You should stop an A/B test when the results are statistically significant and you’ve reached a decision point. For example, if you’re testing different versions of a landing page, you would stop the test when one of the versions has a significantly higher conversion rate than the others.