Is it my Sales growth is depend on Commisions/Discounts?
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.