Anyone who buys traffic for their mobile app is constantly trying to find better answers to the question “how can I acquire users more effectively?” Today we’ll be outlining why and how marketers can predict success sooner, increase marketing efficacy, and find issues sooner by combining analytics and marketing datasets.
While app giants like Rovio can throw an army of data scientists at finding the optimal conversion value strategy for SKAdNetwork, it may seem like an insurmountable data science problem out of reach for most app developers. At AdLibertas we’ve put together some tips on how the rest of us can find meaningful events for making SKAN campaigns effective.
We are now supporting Amazon Athena for direct SQL access to our customer’s unified user-level data. Quickly and easily query consolidated user-level data for in-depth user analysis without building custom data pipelines.
Our newest reporting module allows filtering by user performance. Now you can quickly segment top-earning customers, understand user churn, and forecast with more confidence.
Get a better understanding of how to identify and influence user behavior.
App developers are constantly looking for methods and strategies to identify valuable users as early as possible.
AdLibertas customer and frequent contributor Geoff Hladik shares how he’s leveraging day-1 user time to identify and predict future valuable users.