One of the most potent approaches for subscription apps to boost revenue is optimizing paywalls. One way to fine-tune these paywalls for maximum effectiveness is through A/B experiments, a method that allows developers and product managers to compare different versions and identify what works best. In this article, we will explore the concept of A/B paywall experiments specifically tailored to subscription apps in the productivity category.
A/B paywall experiments involve creating and testing two or more variations of a paywall to see which one performs better in terms of conversion rates and revenue generation. The key principle behind this method is to make data-driven decisions by comparing different elements of the paywall, such as design, pricing, subscription durations, and trial options. By systematically testing these variations on real users, developers and product managers can gain valuable insights into user behavior and preferences, leading to optimized paywalls that result in higher subscription rates.
Let’s take a look at some iterations of paywalls for popular apps. Below, you can see the comparison of previous and current paywalls.
Let’s take a look at the paywalls of the top apps in the Productivity category.
VPN Super Unlimited Proxy has altered the overall design and pricing strategy.
X-VPN Premium has modified the paywall structure by including two plans on the initial screen: monthly and yearly subscription options.
You might have noticed that all these apps were trying out different ideas with the main paywall elements. Now that you know what these elements are, there’s a quick way to test things without using up a lot of your team’s time.
The basic idea is to create 4 most common paywall templates. With these templates and the ability to control their parts, you can make lots of different versions to try out.
You can do it by yourself, or, alternatively, you can use Qonversion which lets you set up all these different options quickly using JSON. You can do this with just a few clicks and test many things at the same time. This helps you work faster without putting too much pressure on your developers. To learn more about our step-by-step approach, read our Quick A/B Experimenting framework.
Understanding the results of an A/B test is crucial for improving your paywall approach. Make sure that your results are statistically significant. If you use Qonversion’s A/B testing experimenting tool, you’ll see whether your test reached the statistical significance right in the dashboard. As soon as you find the version that’s working best, you can apply it to all users without needing to launch a new app version. Then, you can keep testing new things to make your app even better.
Qonversion offers a robust A/B experiments tool designed specifically for subscription-based apps. This tool empowers you to experiment with and optimize various aspects of your paywalls, including in-app pricing, subscription durations, paywall user interface, and the utilization of custom JSON payloads. The implementation and launch of A/B tests are streamlined and efficient, seamlessly integrating with your existing subscription management solution.
It’s important to note that while processing payments through Qonversion isn’t mandatory for running A/B tests, leveraging Qonversion does provide the added advantage of highly precise subscription analytics, which are pivotal for accurate A/B test calculations. By utilizing Qonversion’s A/B testing, you can meticulously track essential metrics such as conversion rates and overall in-app revenue. Furthermore, the winning paywall variation can be seamlessly rolled out to all users instantly, eliminating the need for a new app version release on the App Store.
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Kate | Oct 20 
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Michael | Sep 04 