Ideas for model selection for predicting sales at locations based on time component and class column

Question

I am trying to build a model for sales prediction out of three different storages based on previous sales. However there is an extra (and very important) component to this which is a column with the values of A and B. These letters indicate a price category, where A siginifies a comparetively cheaper price compared to similar products. Here is a mock example of the table

week	Letter	Storage1 sales	Storage2 sales	Storage3 sales
1	A	50	28	34
2	A	47	29	19
3	B	13	11	19
4	B	14	19	8
5	B	21	13	3
6	A	39	25	23

I have previously worked with both types of prediction problems seperately, namely time series analysis and regression problems, using classical methods and using machine learning but I have not built a model which can take both predicition types into account.

I am writing this to hear any suggestions as how to tackle such a prediction problem. I am thinking of converting the three storage sale columns into one, in order to have one feature column, and having three one-hot encoder columns to indicate the storage. However I am not sure how to tackle this problem with a machine learning approach and would like to hear if anyone knows where to start with such a prediction problem.