Everything you need to know about App Revenue Growth

Everyone who relates to subscription apps understands the importance of delivering a great user experience and maximizing user engagement. One of the best ways to achieve this is through A/B testing.

In previous articles, we've covered the basics of paywall testing and best practices for designing and executing experiments. However, an equally important part of a successful A/B test is a good hypothesis.

In order to have top-notch subscription apps in your portfolio, you need to choose the best combination of paywall subscriptions and have a near-perfect onboarding and paywall itself.

The mobile app market continues its rapid development, accompanied by growing competition among applications. In such an environment, it is necessary not only to attract traffic to your app but also to monetize it.

In this case study, we will describe how our client, AEZAKMI Group, increased the conversion rate and maximized their subscription apps’ revenue by launching A/B experiments in Apphud.

Paywall is a key element influencing the purchase and the user's decision to use the app. Whether a new user becomes a loyal user depends on the effectiveness of the paywall.

At each stage of product development, from launching to scaling, the burning question is how to make an app profitable, and how to increase revenue with no big budgets.

In this article, we'll tell you about the Pricing and Paywall experiments feature update, improved Renewals Revenue Segmentation, and New calculation type in ARPPU. Curious to find out more? Here we go!

In this article you will find out how to work with Firebase A/B tests in Apphud using the User Properties feature.