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Advertising effectiveness and Return On Investment (ROI) are typically measured through econometric models that measure the impact of varying levels of advertising Gross Ratings Points (GRPs) on sales or on purchase decision and choice. TV advertising has both dynamic and diminishing returns effects on sales, different models capture these dynamic and nonlinear effects differently. This paper focuses on reviewing the econometric rationale behind the popularized Adstock transformation model that allows the inclusion of lagged and non-linear effects in linear models based on aggregate data.
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