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Adjust Launches Subscription Tracking Product As Mobile Streaming And App Subscriptions Boom

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New Survey Commissioned by Adjust Finds American Consumers Spend an Average $20.78 a Month on App Subscriptions, With More Than a Third Using Their Smartphones to Stream Video and TV Services Every Day

As the mobile app subscription business accelerates, Adjust launches its new Subscription Tracking product to give marketers better visibility into subscription performance. This follows a broader shift toward subscription-based monetization models, with Apptopia estimates showing that app-based subscriptions generated over $200 million in August 2020 alone, and many US adults are planning to keep their subscriptions post-pandemic.

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A consumer survey commissioned by Adjust examines the intensification of subscription and streaming consumption on mobile devices in the US.
A consumer survey commissioned by Adjust examines the intensification of subscription and streaming consumption on mobile devices in the US.

Adjust’s Subscription Tracking product will enable marketers to build accurate Lifetime Value models that increase ROI. Previously, marketers were missing access to important subscription data, which impacted their understanding of the user funnel. By combining subscription measurement with attribution data, Adjust is able to inform its clients what marketing channels drive the longest-running and most valuable subscriptions. Marketers can then invest far more accurately in user acquisition and run engagement campaigns that boost loyalty and prevent churn.

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“The growth of subscription-based apps has intensified this year as users look to their mobile devices for a broader array of activities, from entertainment and e-commerce to fitness and finance,” said Paul H. Müller, co-founder and CTO of Adjust. “That’s why we are excited to offer an industry-first solution that helps mobile marketers manage their consumers’ subscription events and revenue, giving them a better understanding of how users engage with subscription models.”

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