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.
-
-
- June 7, 2022
- Best Practices New Product
Introducing User Report Filters: identify and understand your top-performing users
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.
-
- May 23, 2022
- Best Practices Case Study
Case Study: Can a user’s day-1 time predict their future value?
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.
-
- May 18, 2022
- New Product
Statistics & Forecasting Modules
We’ve recently launched two new modules for User Level Audience Reporting, both designed to help with better understanding your audience and more accurately predicting future outcomes (LTVs) of your measurements.
-
- May 6, 2022
- Best Practices
Predicting campaign performance for apps supported by in-app advertising.
Marketing performance articles tend to focus on apps focused on IAP and subscription revenue. Apps that have a meaningful amount of revenue earned by in-app advertising face different sets of challenges. We aim to add clarity and provide feedback on some successful methods for managing campaigns on ad-supported apps.