Pixelcut

Pixelcut is one of the most popular AI photo editing apps on the App Store. With its background remover and a wide range of AI tools, Pixelcut has everything you need to produce high-quality content quickly and efficiently.

The Challenge

Bottlenecks Slowing Down A/B Testing and Iteration

The Pixelcut team faced significant challenges when attempting to test different paywalls and pricing strategies. The complexity of building A/B tests and understanding how those tests affect longer-term customer value hindered their ability to experiment quickly and find the best-performing variants.

“We had rolled out our own in-house A/B testing framework using our analytics provider. Mixpanel and Google Analytics gave us data on initial conversions, but we weren’t able to see down-funnel metrics to get the full picture.”

They needed a solution that allowed them to test, measure and iterate on their monetization strategies without needing to constantly engage engineering resources. 

The Solution

Intuitive A/B Testing and Precise Segmentation with RevenueCat

When Pixelcut’s team started using RevenueCat’s Experiments feature, it transformed their approach to A/B testing. RevenueCat Experiments allows mobile apps to optimize their subscription pricing and paywall design with remotely configurable A/B testing. With Experiments, Pixelcut was able to deploy A/B tests on different pricing tiers and paywalls with just a few clicks right from the RevenueCat dashboard, bypassing the need for time-consuming engineering work.

“RevenueCat allowed us to focus on what we do best, which is building products, without needing to worry about the infrastructure around purchases and experimentation.”

Unlike their in-house solution, RevenueCat Experiments offered full-funnel insights. Beyond just initial conversions, pre-built data visualizations in the RevenueCat dashboard make it easy to understand the actual impact of your tests. This allowed the Pixelcut team to track each variant’s performance based on the lower-funnel metrics, like realized lifetime value, giving them confidence in pricing strategy.

“RevenueCat’s Experiments provided us with a clear look into the control and test variants. The ability to see associated lifetime value (LTV) metrics for each variant was a game-changer for our monetization strategy.” 

Pixelcut ran a test to see whether weekly or monthly subscriptions led to the highest LTV. 

After identifying that weekly subscriptions outperformed monthly, Pixelcut leveraged RevenueCat’s Targeting feature to roll out the winner to the right audience. RevenueCat Targeting allows developers to segment their users by country,platform, app version and custom attributes and serve a custom paywall for that audience. For Pixelcut, this meant they could easily ship the optimized paywall to their desired audience of new users only. 

“RevenueCat’s Targeting was the perfect solution to ensure our paywalls were tailored to the right audience without additional engineering work.” 

The Results

A 16% Increase in paying customers

By using RevenueCat Experiments to test and measure different pricing options and RevenueCat Targeting to seamlessly roll out the winning variant, Pixelcut saw tremendous results.

“Using Experiments, we ran a test between a weekly and a monthly subscription offering, and the weekly offer resulted in 16% more paying customers.”

The experiment paid off, covering the costs of using RevenueCat.

“This A/B test alone paid for all of RevenueCat’s costs. Being able to find a variant that produces a 16% increase in subscribers definitely makes RevenueCat worth it” 

RevenueCat’s Experiments and Targeting enabled Pixelcut to set up and run experiments without relying on engineering while also measuring the experiment success beyond initial conversion. This allowed them to optimize their monetization strategy faster so they could focus on building great products instead of dealing with the complexities of subscription management and experimentation.