Is it my Sales growth is depend on Commisions/Discounts? I prefer this model in R

We are capturing sales data by time series (Month by month). Some of items have commissions and some have Discounts and others have both commissions and discounts. Is it Commissions or Discounts or commissions + Discounts have impact on my sales growth? Or is it my sales are growing because of those commissions or discounts or discounts +commissions Can you suggest me best model to solve my use case? I am thinking multiple regression. But I want to double check with experts like you.

Thanks for your all your help

Sample Data set: (5 variables)

Year-Month -Product -Sales  -Commission -Discounts
2013-01 Milk    300 No  Yes
2013-02 Milk    400 No  Yes
2013-03 Milk    200 No  Yes
2013-04 Milk    150 No  Yes
2013-05 Milk    500 No  Yes
2013-01 Bread   800 Yes No
2013-02 Bread   879 Yes No
2013-03 Bread   790 Yes No
2013-04 Bread   459 Yes No
2013-05 Bread   600 Yes No
2013-01 Cheese  400 Yes Yes
2013-02 Cheese  350 Yes Yes
2013-03 Cheese  600 Yes Yes
2013-04 Cheese  590 Yes Yes
2013-05 Cheese  720 Yes Yes
Multiple regression sounds appropriate in this case. Real question is what variables to use. Definitely, you should include indicator variables commisions and discounts (and possibly their combination - commisions_and_discounts - as a separate variable). Date and time information may play important role as well, though treating them is a little bit harder. At the very least, it's worth to include year (because there may be a global trend), month and day_of_week (many patterns are repeated periodically). 

Product type is a little bit more complicated. Obviously, some products will always have higher sales than others, so first idea is to include a set of product_type_x dummy variables. But product type may affect sales not additively, but instead multiplicatively, i.e. not as 

sales ~ beta_0 + beta_1*product_type_x + ...


but instead as 

sales ~ beta_1 * prodcut_type_x * (beta_0 + ...)


In this case better solution would be to create separate regression models for each product type.