I have data about sale as example follows:
| Date | Product | Category | Sale | Promotion of product 1 | Promotion of product 2 | Promotion of product 3 |
|---|---|---|---|---|---|---|
| 01/01/2020 | Product1 | A | 3 | 1 | 0 | 0 |
| 01/01/2020 | Product2 | A | 4 | 0 | 1 | 0 |
| 01/01/2020 | Product3 | B | 2 | 0 | 0 | 1 |
| 02/01/2020 | Product1 | A | 7 | 1 | 0 | 0 |
| 02/01/2020 | Product2 | A | 4 | 0 | 1 | 0 |
| 03/01/2020 | Product1 | A | 2 | 0 | 0 | 0 |
| 03/01/2020 | Product2 | A | 1 | 0 | 0 | 0 |
| 03/01/2020 | Product3 | B | 9 | 0 | 0 | 1 |
Suppose I have 50 products and because of the hypothesis that the sale and promotion of one product can impact to others. So, I would like to forecast each product in parallelly. (I mean that model forecast whose the outputs are the sale of each product) What are the methods to solve this problem?
