The Unpredictable Audience: An Exploratory Analysis of Forecasting Error for New Prime-Time Network Television Programs

Abstract

This article investigates possible determinants of forecasting error for new prime-time network television programs. Each season, advertising industry forecasters attempt to predict the audience shares for new fall programs. Advertising expenditures are made on the basis of these projections, though historically these forecasts have been very inaccurate. Through an integration of audience behavior theory and decision—making theory, this paper attempts to identify factors that explain the magnitude of uncertainty, and hence the magnitude of forecasting error, surrounding the predictions for new programs. The results indicate that the presence of a returning network lead-in or lead-out significantly reduces the amount of forecasting error. In addition, the results indicate that forecasting error has increased significantly over time. The overall explanatory power of the model suggests that content and audience characteristics must be incorporated into the analytical framework as well.