Why doesn’t retention my match? Why are daily active users different? How many installs did we actually get?
Every mobile app developer has struggled in getting a reliable source of truth from their data. Today we speak to how you can establish a source of truth across multiple, sometimes conflicting data sources.
In the never-ending quest for growth, mobile apps often turn to paid user acquisition. The golden measure for success is the return on your ad spend. In this article we outline the frameworks for how mobile app developers today are measuring return on ad spend (ROAS) and include reference material for those interested in getting more effective results from paid UA.
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.
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.