A little bit of background: I have daily demand data for our product from 1 January 2017 to 31 December 2022. Sometime after Covid-19 struck say 1 March 2020, the sale of our product went up substantially (sales in 2021 were 8X sales in 2019) and the demand has sustained till date (March 2023).
Now, my manager has asked me to find out what the sales would be if Covid hadn't struck viz. if we had continued at the same sales levels we were at pre covid and find the difference between the expected sales (estimated using pre-covid numbers) and the actual sales.
I believe I'm not able to find something online since I don't know the exact area of study to look for.
I have the following questions:
- What is the broad area of study or technique that deals with the above problem? I assume it would be something like promotional analysis where one tries to model the effect of a promotion/discounts to see how the sales are affected.
- Are there any specific techniques that you would suggest that would help me solve this problem? Techniques could be statistical: based on distributions/tests or ML oriented or any other ones.