A/B testing is the most effective way to observe users’ behavior with two or more different versions of the same screen or in-app experience. It can help you test variations of an item, generally UI based, to determine which one performs better.
Directing some users to version A and others to version B allows you to observe user behavior for each. In this way, you can:
Although A/B testing has been in use since the beginning of the web, its use in mobile products has become more popular in recent years.
The high costs and technical complexities of mobile product development leave little time for guesswork, particularly when it comes to developing an app that customers find useful.
That’s why a product analytics tool, like A/B testing, is necessary. It can facilitate better decision-making throughout the development life cycle, freeing up time and resources needed for your team to focus on their objectives.
If you want actionable insights from an A/B test, the approach to the planning needs relevant consideration. Since testing dozens of different scenarios would be costly, reducing the scenarios by collecting relevant input and research could help make the overall process faster.
The A/B testing process consists of 5 steps:
Let’s deep-dive into each of those steps:
Cases to be tested are created with input from teams connected with the process. Some of them are prioritized for testing, while others are sent to the backlog for future tests. These are used to define and inform the strategy for the implementation of the test.
All the necessary content, materials, and visuals are created for the case to be tested. The length of the test and the number of people expected to participate are determined. Targeted outputs and methods for monitoring are identified. The processes on which button to define an event, on which area of the page to watch the heatmap, etc. are clarified.
The test is now live for participant profiles. The whole process should be well monitored and the results of the analysis should be evaluated.
When the test process is complete, the outputs should be shared with all relevant teams in a transparent manner and the actions required for the necessary situations should be determined.
You’ve got the final results and feedback from your users, now it’s your turn! If you need to iterate your product according to the A/B test results, you can do it with peace of mind and you can include it in your roadmap.
Continuous testing of your product and measuring your users’ actions is a process that should always be experimented with. This process has a lot of benefits, but we’ve gathered a few of them for you:
A/B testing is the most effective method for content optimization. For example, you can compare copy options on a call-to-action button to see which has the better click-through rate. This way, you can use your budget effectively and you can quickly access user insight.
The bounce rate is very important for conversion. A/B testing reveals combinations that help customers stay longer on the site or in the mobile app. The more time customers spend on your product, the better their understanding of the value proposition you’re trying to offer; this will reduce your bounce rate.
A/B testing is an effective way to identify good content that will turn visits into signing up or purchases. Knowing what works and what doesn’t will help you convert more leads.
With an A/B test, it can be easy to discover ineffective user flows before they adversely affect your product. This way you can optimize your app which can also help avoid operational costs down the line, allowing you to ultimately manage your resources better.
One of the most critical problems among e-commerce applications is a high abandoned cart rate. It is possible to reduce this rate, but it requires tracking users very closely and understanding what works. A/B tests allow you to first test the scenarios needed to reduce this ratio and reduce your effort considerably.
In a social media application, for example, there are several different icon design alternatives that you can use on the “like” button. You can measure these alternatives by showing them to different users to see which icon is selected most often, increasing user delight, and, consequently, user engagement.
A/B testing allows you to test a page, name, title, content, images, calls-to-action, font, color, and other elements — all of which can affect engagement.
In conclusion, no matter the changes you make to your product, listen to your users and evaluate the inputs they provide. A/B testing will remain a critical tool for the entire lifecycle of your product. Together with other analytics-based strategies, like Voice of the Customer, A/B testing will ensure that each product iteration is data-driven.