As a UX designer, your goal will always be to make a user-friendly and desirable digital product to ensure you meet the objectives of the users and that the product reaches the targeted audience. A well-designed digital product will meet the purpose it was meant for, thus maximizing profits.

The elements that make a UX product are usability, valuable, desirability, findability, accessibility, and credibility. However, how do you ensure your digital product meets all these elements? It can only be through AB testing. This guide explores all the details you need to know about AB testing and how to achieve the processes.

What is AB Testing?

Also known as split testing, AB testing is a simplified test where UX designers randomly show end-users two different versions of a design variant (can be font size, font page image, or a homepage CTA copy) to get the best version based on the feedback they get. The design in which the users choose to take the next action is regarded as the better version, and the other one is disposed of automatically. Ideally, you can test anything in UX through AB testing.

Benefits of A/B Testing

Sometimes, it can be hard for the UX team to make a final decision or to choose between different UX design variants throughout the product design process. To avoid guessing, the UX team performs AB testing to get accurate results.

In the end, you create a product that meets the user’s needs, which is the main goal of the whole process. Some of the benefits of AB Testing include the following:

• Conversion rates optimization
• Settling a disagreement between the team designing the digital product
• Enhancing overall use experience
• Getting measurable analytics about your design
• To get the best UI elements
• To make useful decisions
• To avoid repeating the whole process

AB Testing Stats

Below are some of the AB testing stats you should know

• The AB testing software market is expected to reach $1.08 Bn by 2025.
• About 60% of organizations rely on AB testing to optimize their conversion rates.
• AB testing made the Obama campaign reach $75 million.
• If the AB testing is done the right way, it can lead to up to 50% revenue increment per visitor for eCommerce platforms.
• In about 1 out of 8 cases, AB testing brings a positive change in an organizations.
• According to statistics, AB testing in the top CRO method.

A/B Testing Tools

Of course, you will need to evaluate and analyze the AB testing results before making a viable decision. These tools help simplify the whole AB testing process. There are many tools you can use, but the popular ones include the following:

• Unbounce

With Unbounce, you don’t need coding knowledge to create and publish landing pages. The tool enhances better traffic conversion rates, and it is faster and easy to use.

• Google Analytics

You will get both real-time and website digital marketing reports with Google Analytics. The tool helps you evaluate and analyze how users interact with the digital product as you note the areas you need to work on to improve user experience.

• Google Optimize

Google Optimize will help you customize AB tests. With this tool, it can recommend the best option you should use for your design instantly.

• Visual Website Optimizer

If you want to conduct A/B testing as a beginner or when you don’t have adequate knowledge of AB testing, use the visual web optimizer tool for accurate results.

• Adobe Target

With adobe target, you will know the kind of messages, offers, and actions users prefer the most,

AB Testing in UX Process

Once you are ready to conduct an AB test, you should take the following steps to ensure you are moving in the right direction.

• Data collection

The whole process begins with getting useful data. Measure and evaluate how the current design is performing based on the user’s feedback. Through site analytics, you will be in a better position to identify areas that require immediate optimization. Is it the home page? Or is it the background image? Or is it the font/color? etc.,

• Define Your Goals

Once you’ve gathered enough information, you already know the exact area that requires optimization. The goals you set, guided by the simple decision tree, will enable you to make informed decisions and get the desired results after optimization.

For instance, your goal would be to increase more subscribers to the blog, increase CTA buttons for more clicks, or to have users interact with the website for a longer time. With the exact goals in mind, you already know the exact changes that will create a positive impact.

• Create a Hypothesis

Your hypothesis is the assumption you need to make to improve the user experience and achieve your goal. Therefore, you can build a hypothesis based on how the users interact with the site and website analytics. To create a viable hypothesis, you must do some research. You can ask the users their main problem, why they enjoy purchasing the products, or what they could love to be done differently.

Note: While you can create many hypotheses, you can only test for one. For instance, if it’s about colors, you can only work with one test to get accurate results.

• Create A & B Versions of Design

Once you understand the behavior of people and how they interact with your digital products, use the AB testing tools to determine useful data that will help you choose the appropriate design elements for testing. Choose the variant that will help you reach your target clients and achieve a higher conversion rate.

With the testing variants, use a tool to divide them into two with different elements. The users should be able to see two different design versions to choose the best.

• Start Testing

With the design two design versions, you will be able to track how users interact with the platform. AB testing tools will help you transform their activity into useful information to evaluate and analyze later on before selecting the most appropriate design. The experiment’s timeframe varies depending on the amount of data collected for AB testing.

• Analyze the Results

Once the AB test is done, you will have to evaluate and interprets the results by collecting and comparing what you’ve gathered from the two versions. A careful study is required to ensure the designer interprets accurate results. You will then select the option that helped the company achieve the required results and discard the other option.

Things to Consider for Accurate AB Testing Results

Of course, when doing the AB testing, you want the outcomes to be as accurate as possible, and this will enable you to achieve the desired results. Therefore, all you need to do is consider the following elements:

• Perform the test options at the same time

For the results to be valid, you need minimum variables. Minimum variables will limit the chances of irrelevant data changing the appropriate outcomes. For instance, doing ads in different months means different seasons. Since the trends adjust based on the season, you might get the wrong interpretation of the final results. In this case, you should run the ad tests on the same month and the same period when all other determinants are constant.

• Your test shouldn’t run too long or too short

When the tests run for too long, the chances of something unrelated to the test happening and adjusting the results are higher. Similarly, when the tests take a shorter time than anticipated, you risk leaving more useful information unattended. The outcomes will be skewed results.

As a designer, you can always estimate the average number of users you need to get accurate results. Once you have an idea of the average number of users required to interact with your app, you can then estimate the appropriate time frame to accomplish the test.

Note: Most AB testing software establishments have accurate models that simplify the statistical data and give you the appropriate duration to accomplish the test.

• Define what you’re looking for

Before you perform the AB test, you must be sure of what you want. When your questions are more specific, you increase the chances of getting the required results. Once you define the exact question, think of the percentage level you can rule out the results as accurate, as seen below:

Conclusion

AB testing is, without any doubt, the best option for companies that want to save on budgets during the designing phase. It helps cut down the costs of starting the design process from scratch in case something goes wrong along the way. AB testing helps design the product by involving the users. This ensures the end product is accurate and meets the requirements of the clients.

For more information connect with our software testing company : Aalpha information systems.