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The majority of the current research on measuring advertising productivity has gone toward creating techniques for determining the "theme" advertising’s long-term effects. However, measuring advertising productivity in the retail sector presents significant difficulties. For example, the main purpose of advertising in many retail companies is to draw people in by announcing "limited-time price specials." It is necessary to link advertising expenses to short-term changes in sales in order to evaluate the efficacy of advertising for these businesses in the lack of shop traffic data. In this work, we develop a decision support system to help merchants plan, monitor, and assess their advertising expenditures. 

This system’s main goal is to suggest more effective ways to spend advertising dollars based on media type and market. We provide an example of the system in action for a national retailer with an emphasis on electronics. We estimate various models to evaluate advertising performance for various days of the week using daily sales and advertising spend data. We talk about the model results, how they affect advertising choices, and what has to be done to make this system better moving forward.