A/B Testing Service
Determine the best performing version of your product
A/B testing, also known as split testing, is a method of comparing two versions of a web page or app to determine which performs better.
Essentially, UX researchers show two or more of a digital product’s features to users at random. Then, they analyze the results to see which version performs better for a given conversion goal.
These features often include:
Make targeted changes to your product
Running A/B tests allows you to ask focused questions about changes to your website or app and collect data about the impact of those changes.
Instead of making assumptions about your users, you can gather real-time data. This helps you make better decisions about how to move forward with your product to get the results you want.
Enhance your online customer experience with data
Companies of all sizes in every industry can benefit from A/B testing. It can help you reach your audience in the most effective way. It is also one of the most cost-effective solutions out there. Discover more of the benefits that A/B testing can offer you below.
Low-risk, high-return modifications
If you’re unsure whether a new feature or element of your digital product will perform as well as you hope, you can conduct an A/B test to see how your users will react.
Frictionless pathways to conversions
Find out which type of content is likely to lead your visitors to convert into leads or make purchases. Better understand your users in order to create the most impactful digital experiences.
Continuous, rapid improvements
A/B testing is a repeatable, ongoing process that keeps your online presence moving forward. It ensures that the changes you make to your products are the ones your users want, so that you can build customer loyalty and keep ahead of the competition.
Our simple 5-step A/B testing process
Identify testing goals
Whether an A/B test is for an application, a web page, or an email, every A/B test needs a clear goal. For example, if your goal is to generate more leads from an advertisement, then the A/B test might look at which offer text generates the most submissions.
An A/B hypothesis is an assumption on which to base a test. It should include what you want to change and what you guess might happen as a result. For example, if you want to generate more leads from advertisements, your hypothesis could be: “Reducing the length of the offer text will generate more leads.”
After that, we create variations to test the hypothesis. Changing multiple features is possible. Known as multi-variant testing, it increases the complexity of the test. Many features or changes can be tested. However, we advise starting with something simple that is likely to have a large impact.
The next step is to commence testing. At this point, visitors to your website or application are randomly assigned to either the control or variation of what is being tested. The test should run long enough to have meaningful results that are statistically significant.
Once we run the test enough times, we can analyze the results. These results can then be used to help you make decisions with confidence and make changes to help you reach your goals.
Meet our team
At Morphosis digital consultancy, we have a vibrant team of marketing experts who deliver impactful results for our clients. The needs and desires of end-users are at the forefront of everything we do. Let us help you grow your business. To find out more about how we can help you grow your business in the digital age, get in touch with our team today.