Predicting Customer Activity Absence



Hi everyone,

Could you please assist me with to following question?

I have a customer activity dataframe that looks like this:

It contains at least 500.000 customers and a “timeseries” of 42 months. The ones and zeroes represent customer activity. If a customer was active during a particular month then there will be a 1, if not - 0. I need determine those customers that most likely (+ probability) will not be active during the next 6 months (2018 July-December).

Could you please direct me what approach/models should i use in order to predict this? I use Python.

Thanks in advance!


Hi scnkd,
This problem can be solve through classification models. take last 6 month(Jan18 to June 18) as a target and check for each month’s the accuracy. Based on your model accuracy, can predict for next 6 month(Jul 18 to Dec 18).

Reference(Churn model):

Hope it will work!


Thanks rock_bt,

I’ll look into that!