I’m working on a classical churn prediction problem using the number of visits of a given user to a site and I thought that Poisson Regression was the right tool for modelling the future engagement of that user. When then I came across a book about survival analysis and Hazard Modelling and I don’t know which technique is best.

I don’t want to be researching both topics at the same time, so what is best for modelling user engagement using past data and demographics?

**Answer**

Brief and general answer:

- With Poisson regression, the response variable of interest is a
**count**(or possibly a**rate**). - With Cox regression (or alternative modelling strategies from survival analysis), the response variable is the
**time**that has elapsed between some origin and an event of interest. In particular, survival analysis techniques are designed to handle**censoring**. - Note that, under some assumptions, there is a link between the two.

**Attribution***Source : Link , Question Author : tonicebrian , Answer Author : Community*