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Could you please assist me with to following question?

I have a customer activity dataframe that looks like this: enter image description here

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!

Andrei
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1 Answers1

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The most direct analysis would be a survival model characterizing the customer's return over time: https://towardsdatascience.com/survival-analysis-in-python-a-model-for-customer-churn-e737c5242822

If you have more information about the customer besides the time series, you can augment your model with additional signals.

jspcal
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