Forecasting market response

The basic premise of marketing is that a company can take actions that affect its own sales. These actions include offering a product to a market; pricing; distribution (or place); and promotion through advertising or sales force effort. Taken together, this set of marketing decision variables constitutes the ‘marketing mix.’ Market response models show the relationship between such controllable decision variables as well as noncontrollable variables reflecting competitive actions and environmental factors, such as interest rates, and performance measures including unit sales and market share. Thus, market response models provide a basis for forecasting. On this view, forecasting follows planning because plans for marketing actions drive sales. Correlation studies of the impact of marketing decision variables on sales were first completed in the 1960s. Since that time-and particularly since 197O-econometric and time series analysis (ETS) has been applied to a wide variety of situations so that, today, market response models are an important tool of academic research and practical application; see, for example, Gold (1992) and Parsons et al. (1994). Nevertheless, questions remain about how to

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