Sales promotion is a primary tool included in the marketing mix that can arbitrate the sales trend. Retailers need to deploy business analytics to measure and define key performance indicators to determine an accurate measurement of return in investment for individual promotions. In this context, the need for an advanced Decision Support System (DSS) to orchestrate promotion strategy is critical for the companies. A brand-level model, which will assess promotional performances of brands within the category, could provide a helpful tool to retailers both for category management and price promotions activity allocation. This research estimates promotion/sales elasticity models for 11 brand-category groups to assess promotion efficiency using the ARDL bounds test method. Brand-level model, we estimated points that own price and promotion depth effect have the most significant impact magnitude on sales. Auto-regressive Distributed Lag type models we employed for this analysis enable us to differentiate long- and short-term analysis.
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