Case study: Sleep Cycle x Adjust

Sleep Cycle is a sophisticated sleep tracker app designed to enhance sleep quality. Leveraging advanced sound analysis technology, there is no need for wearable devices or anything under the pillow. The app monitors sleep patterns, detecting snoring, sleep talking, coughing, and other nighttime sounds. Its core feature is an intelligent alarm clock, which aims to wake users during the lightest sleep phase, emulating a natural wake-up process for a more refreshing start to the day.

The Sleep Cycle team wanted to scale their marketing efforts to achieve sustainable growth within the competitive health and wellness vertical. To do so, they needed to protect their strong organic traffic and ensure their organic installs were not cannibalized by paid campaigns.

The implementation of Apple's SKAdNetwork (SKAN) also introduced complexities in measurement and tracking for iOS, necessitating innovative solutions to understand foggy figures. Additionally, the team’s objectives of product innovation and hyperlocalization required finite insights to successfully appeal to prospective users in niche markets. These challenges underscored the need for a comprehensive mobile measurement partner (MMP) to navigate the intricacies of app marketing at scale.

Enter: Adjust’s latest product. Sleep Cycle has been a client of Adjust’s for over seven years, and now it was time to take their insights up a notch. Through Adjust’s Incrementality early access, Sleep Cycle was able to determine the irrefutable effect of individual marketing activities.

These revealing insights facilitated experimentation with new channels and marketing strategies. Adjust's unparalleled incrementality analysis empowered Sleep Cycle to make informed decisions on continuing or discontinuing marketing efforts based on their incremental value.

This is especially critical in a post-device ID landscape, where traditional tracking and measurement are more challenging. Adjust's ability to create synthetic control groups enabled Sleep Cycle to compensate the limitations imposed by working with SKAN data, providing a robust framework for evaluating the effectiveness of marketing initiatives that will be easily applicable to any privacy-centric, aggregated data sets in future.

With Adjust’s Incrementality testing, Sleep Cycle was able to:

• Set effective strategies to avoid organic cannibalization, after unveiling up to 50% cannibalization through incrementality testing, including the selection of campaign type and optimization targets.
• Test an 80% budget increase with one channel, revealing that it was best geared towards installs over events.
• Uncover which partner was contributing to incremental lift of Android installs, but having the opposite effect with iOS.

Armed with these insights, Sleep Cycle can confidently allocate investments into channels that are now known to yield a positive incremental lift for either iOS or Android. Furthermore, Sleep Cycle can hyper-optimize campaigns with regard to placement and optimization targets, leading to significantly stronger performance overall. They can also reduce the time and financial investment required for testing new marketing campaigns, thereby enhancing their agility in response to market changes.

This strategic advantage has proved pivotal in enabling Sleep Cycle to continue its growth trajectory, optimize its marketing campaigns, and adapt its strategies in the ever-evolving digital landscape, all while maintaining a focus on privacy-conscious marketing practices.