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  • Modelling the Advertising Effects - Part III

Modelling the Advertising Effects - Part III

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Till now, you have seen the models that capture the current effect of advertising. However, if you want to capture the carry-over effect, you would want to model the current sales or revenue figures based on the past figures of the advertising spends and other KPIs. The models that can help you model these impacts are the Koyck and the distributed lag model. Let us learn about these models in the video below.

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Clarification: At 4:25 minutes, read it as Y_t = \alpha + \mu_1 Y_{t-1} + \mu_2 Y_{t-2} + \mu_3 Y_{t-3} + ..... 

 

In the distributed lag model, not only is the dependent variable entered in its lagged version, but the independent variables are as well. This is a more generalist model and captures the carry-over effect of all the variables. Thus, the Koyck model is a special type of distributed lag model, which includes the lag value of only the dependent variable. The hierarchical model, on the other hand, uses dummy variables to capture the impact, like content or media. As the dummy variable takes a value of 1 or 0, it signifies the presence of one or the other content or media channel.