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I have data of 5000 customers over time series (monthly) which looks like:

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This is my first time dealing with time series data. Can someone explain some strategies for Churn prediction probability (3 months, 6 months) in advance?

I am confused because for every customer churning probability 3 or 6 months in advance will be zero (according to target). So should I see some trends or create lag variables?

But I still don't know if regression, what will be the target variable.

bazinga
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1 Answers1

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you can use lag function and then define churn and use predictive model to churn. As I can see buying product category, so you can take lag for last 3 month for unique customer id and then define the churn for 3 months

Nikhil
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  • This should be a comment not an answer, i know you don't have enough reputation yet but have patience !! I appreciate your efforts for answer. thanks – Dev Jul 28 '19 at 14:09