Welcome back to another edition of Alpine Data Lab’s Workout of the Week! This week we’ll be looking at some Product Activity data using a simple linear regression algorithm. In less than 10 minutes, we’re going to take some raw product data and produce a model that tests the long-held belief that more product adoption = longer lifetime.
Data: Product Activity Data
Analysis: A particular service has seen members join for varying amounts of time over the last two years with different types of licenses and varying adoption of two add on products. In this churn analysis, we will look at how users can be broken into different groups based on the number of days they have been a member. How do these groups vary in terms of the licenses held and products which have been added on? Additionally, we’ll show how you can build a quick linear regression to look at the effect the license and add-ons have on the number of days an account has been active.
Video: Check out the video to see how we performed the analysis and what the data told us!
Join us on Wednesday, February 13th at 11am PST/2pm EST for our next Workout of the Week webinar as we explain the analysis in greater detail and answer your questions. Register now to reserve your seat! And in the meantime, feel free to submit your analysis on our Data Science Crossfit page on Tumblr or email us a link to your video at email@example.com. If you don’t already have Alpine, sign up here to get started!
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