Measuring User Retention with Hadoop and Hive by Daniel Russo.
From the post:
The Hadoop ecosystem is comprised of numerous technologies that can work together to provide a powerful and scalable mechanism for analyzing and deriving insight from large quantities of data.
In an effort to showcase the flexibility and raw power of queries that can be performed over large datasets stored in Hadoop, this post is written to demonstrate an example use case. The specific goal is to produce data related to user retention, an important metric for all product companies to analyze and understand.
Compelling demonstration of the power of Hadoop and Hive to measure raw user retention, in an “app” situation.
Question:
User retention isn’t a new issue, does anyone know what strategies were used before Hadoop and Hive to measure it?
The reason I ask is that prior analysis of user retention may point the way towards data or relationships it wasn’t possible to capture before.
For example, when an app falls into non-use or is uninstalled, what impact (if any) does that have on known “friends” and their use of the app?
Are there any patterns to non-use/uninstalls over short or long periods of time in identifiable groups? (A social behavior type question.)