I have weekly data per single SKU and for more than 500 point of sales. Data embeds base price, quanity sold, holidays, temperature, market activities (cut-price, display, leaflets) and so on.
I want to run a regression model (OLS) to capture the effect of changes of base price on sellout controlling for all the other exogenous factors. I am thinking of running a regression using all the data from my point of sales but of course the higher the dimension and potential of a shop, the higher the sellout of that product. As of now, I have added as a avariable in the regression model the potential of the point os sales (share of volume of sellout amon all the population of shops) to capture the different potentiality but I am not shure about this method.
I also cannot aggregate data per week because i would lost all the in store activities (i.e. cut-price) that of course have a great impact o sales.
How can I proceed?