Understanding Trends in Monthly Usage Data

[Scussett]

Hi Folks,

I'm trying to figure out the best way to look at changes in usage data from my customers.  We have a hosted technology platform, and we get reports on how many transactions each customer uses per month.

I have a table broken down by CustomerName, UsageMonth, and BilledTransactions.

Customers can start using in various months, and could cancel (stop using) in any month.  I want to be able to predict who will cancel based on whether or not their usage is declining - either year over year (seasonally adjusted if possible), or if a string of months in a row shows decline over the prior year.  Something similar to an exponentially smoothed model - where we forecast where they should be and then compare that against where they actually fell might work as well.

Does anyone have ways of doing these things?  Are there any guides out there to doing an example in R?

[v-huizhn-msft]

Hi @Scussett,

For your requirement, you'd better create a sample table and list the expected result. You can share your sample table by private message. So that we can post possible solution which is close to the results. Thanks for understanding.

Best Regards,
Angelia