I have a timeseries of monthly sales data, by account for a single product. It looks something like:
I'm trying to quantify the impact of a new marketing campaign in June. Some of the accounts have high historical volume, others have low. I've looked into ARIMA models, but not sure that this is the right application of those, given that I know exactly when the event occured.
My current thinking is to just look at average order volume before June and after June and to run a t-test to determine if the means are not significantly different (by account). My concern is that this only accounts for the means of the same data before and after June, and might understate the importance of the data immediately around the event.
Any suggestions on other mathematical tools I can use to statically quantify the impact of a marketing campaign on product volume sales?