I am currently trying to develop a forecast for monthly subscriber attrition that allows me to predict for a future point in time, how many subscribers I have. I have a couple of years worth of attrition data, and every month we're recruiting new subscribers.
The difficulty I am having is that if I am wanting to predict 18 months into the future for subscribers recruited this month I am having to rely on data from subscribers recruited 18 months ago and use their attrition curve to estimate how many will be around in 18 months time.
I have noticed that the month 1 attrition for new subscribers is slightly higher than it was 18 months ago. What I am wanting to know is: Is there a way I can use the most recent months attrition data as an input to my attrition curve, rather than relying on data that is 18 months old already?
I am currently doing this in excel and need to continue in excel for the benefit of my colleagues, however I am open to reworking things in R as I suspect it will allow me greater flexibility and reproduce-ability in the future.
Thanks in advance for the guidance
UPDATE: 17/06/2015 Below is a screenshot (data available here http://pasted.co/d9d6fc5e) showing what my data looks like at the moment. The area highlighted in green is what I am using to create my attrition curve (essentially at least 18 months old - this example is older) as it allows 18 months for recruits to defect. I am wondering if there is a way for me to use more recent information as an input into my attrition curve (like that data 201411 for month 1 attrition and data from 201410 for 2 month attrition).