Hello Data Scientists,
I have a requirement of deriving causal factors for my target Product (SKU) sales. I have the weekly sales of the product for last 3 years along with its competitor sales along with promotional data. The business wants to know if there an effect of pantry loading (Add Stock?). Suppose below is my data set.
I can regress independent variable price on dependent variable volume to find the co-effecients of price. We are using Log Linear Regression model to capture the impact of the price on the volume.
Now, I would like to understand how we can model the Pantry loading effect variable. We can see that week of 14 in 2013, the price was made closer to your RRP, the sales dipped significantly. want to capture that effect in the variable so that I can then regress it against the volume to see the positive co-efficient. ( The more price drop on the previous week, the less sales week after)
Does anyone has done this before who can guide me?