My dataset is on revenues from subscription-based (no commitment, can cancel any time). We have people signing up every year, continue paying for a few years and then gradually cancel the subscription.
Total revenue for a year comes partially from subscribers who joined in the previous years (and are still active) and also from those who joined this year.
In this scenario, how can I forecast the revenue for a coming couple of years? In the sample data shown below, we can see how those who joined in FY2003/04 & FY2004/05 are contributing towards revenue for years till FY2017/18.
One possible method I could think of is to add revenues for each Revenue Year and then do a simple time series forecasting for years FY2018/19 & FY2019/2020. But we might be missing valuable information like people who joined very early (during FY2003/04s) tend to stay longer than those who joined in the recent past.
I would appreciate if anyone can suggest any appropriate method to handle this. I am comfortable with Excel, R & Python and most generic machine learning algorithms. Thank you