Data science is becoming an increasingly important part of a mobile app’s growth. But what exactly does a Data Scientist do at a mobile app company? How do they do to help mobile apps grow?
We sit down with Data Scientist Andre Cohen who’s led data strategy for years for some of the most advanced mobile applications in the world to ask his take and experience.
This article outlines various methods for calculating a pLTV model for your apps, ranging from back-of-the-envelope to the most advanced computational models available.
This article is designed to help you choose what types of events to include in your app to measure and predict user behavior helping you facilitate growth for your apps.
Growth is a universal goal for app developers – but how do you get started?
At first, this may seem a daunting task: this article aims to give app developers some tips from the iterations we’ve seen from our customers.
Being able to predict user-behavior of users in your app will help you predict churn, increase user LTV, and increase effectiveness of user acquisition.
We’ve put together a four-step guide to finding, measuring and refining your app’s events with the hopes you too can start to quantify – and predict –user behavior.