A/B Paywall Experiments for Subscription Apps in Music Category

In the competitive realm of subscription-based apps implementing effective paywall strategies can make all the difference. A/B testing, a method of comparing several paywall versions to determine which performs better, is a powerful tool.

In this blog post, we discuss A/B paywall experiments tailored for subscription apps in the music category. Let’s explore how experimentation can help optimize user experiences and boost conversions with real-world examples.

Understanding A/B Paywall Experiments

Paywall A/B testing involves creating variations of key elements within your app’s paywall and measuring the impact on user behavior and revenue generation. This could include experimenting with some crucial elements like subscription pricing, duration, trial periods, CTAs, as well as UI elements and ways to show value propositions.

Key Benefits of A/B Paywall Experiments

  • Data-Informed Decision Making: A/B testing provides data on how changes in your paywall elements impact user behavior. This data enables you to make informed decisions based on real user behaviour.
  • Optimized Conversions: By fine-tuning paywall elements, you can optimize your paywall for higher conversion, resulting in higher revenue.
  • Enhanced User Experience: A/B testing allows you to identify the most user-friendly paywall configuration, leading to improved user satisfaction and loyalty.

A/B Paywall Experiments for Music Apps

Let’s explore the paywalls of the top apps in the music category and what changed in their paywall recently. They all have a lot in common: the structure, similar subscription duration, close pricing, and a trial offers (either 1 week or 1 month).

A/B Paywall Experiments

Let’s take a look at the paywalls of these apps to understand the improvements that have been implemented. By examining these examples, we hypothesize that these changes were a result of ongoing iterations of A/B experiments.

YouTube Music App A/B Paywall Experiments

Compared to the previous year, the YouTube team changed the overall layout of the paywall and positioned the call-to-action (CTA) button right in the center of the paywall.

A/B Paywall Experiments

Amazon Music App A/B Paywall Experiments

Amazon’s team also made changes to the template by placing the button higher, enhancing the value proposition, and making a slight adjustment to the price.

A/B Paywall Experiments

SoundCloud A/B Paywall Experiments  

SoundCloud underwent a significant paywall redesign and began emphasizing the key benefits of their paid subscription, namely, ad-free experience and offline listening. They also modified the pricing and trial duration.

A/B Paywall Experiments

Deezer A/B Paywall Experiments 

Similar to SoundCloud, Deezer underwent a notable paywall redesign and restructuring of its pricing approach. Consequently, they started providing various plans based on the number of accounts, and they introduced both monthly and annual subscription options on the initial paywall screen.

A/B Paywall Experiments

Quickly Launch A/B Paywall Experiments for Music Apps 

  • Identify Hypotheses: Begin by pinpointing the key areas of your paywall you’d like to test. This could be related to pricing, trial duration, or the wording of your value proposition.
  • Create Variations: Develop different versions of your paywall, each incorporating a specific change. For instance, if you’re experimenting with a trial duration, create variations with different trial lengths. We suggest beginning with the four most popular paywall structures and then generating variations by altering each element of these paywalls. Using Qonversion experiments feature can accelerate your experimentation process, as it enables you to swiftly configure these different options using JSON.
A/B Paywall Experiments
  • Split Testing: Assign users to different versions of the paywall. This helps ensure an unbiased comparison between the variations.
  • Monitor and Analyze: Track user interactions and revenue generation for each paywall variation. If you use Qonversion to run A/B experiments, you have an instant visibility in all of the most crucial subscription metrics in one simple dashboard. 
A/B Paywall Experiments
  • Determine Winning Variation: Identify the variation that demonstrates better performance. Pay attention to statistical significance of the test, make sure to get enough data to have statistically significant results.


Paywall experiments are important to successfully grow your subscription app. We see that even market leaders with a huge user base are constantly running experiments and changing their paywalls. In order to be able to do that you need the right tooling that enables you to run experiments quickly and measure the results accurately.

Qonversion’s A/B Experiments Tool enables this and makes you experimentation journey intuitive and straightforward. Qonversion Experiments solution is built specifically for subscription apps providing you the segmentation and analytics that is required for advanced A/B testing. To learn more about Qonversion’s approach to A/B experiments, check out this article.