I've recently began work as a commercial analyst for a large company after graduating from university 3 months ago with a first class Bsc in Business Economics. On my course we covered a lot of time-series econometric modelling, however I'm not even close to being an expert by any means. I digress:
My manager for an extremely long period of time now has been working on a way to measure the incremental impact of a promotional campaign (i.e. this item was only £1.99 for this period of time, how many sales were driven as a result of this). Unfortunately, there's about a million and one roadblocks that he keeps running in to, as well as the fact he has virtually no history in statistical modelling (which is why he wants my help).
The problems include, let's say item x is on promotion, this almost always means that item y is not on promotion, and vice versa. This needs to be taken in to account, in order to create some kind of benchmark to be used for each product when there is "no promotion" (for example it may look like everyone stops buying item x when it is off promotion, but they have simply moved to item y which is now on promo). The final goal is to have something that the business can use as a tool to try and gauge the effectiveness of a particular promotion should they choose to implement it (so a predictive/forecasting tool).
There are also elements of seasonality (around xmas etc), as well as increases in sales in particular weeks over the year where certain catalogs go out to clients etc.
Essentially just wondering if anybody has any ideas on how we can go about this. Just general brainstorming ideas. How a regression can be set up to try and take this in to account, and what other assumptions will need to be made in order to create a tool such as this.