Intervention Analysis of a Field Experiment to Assess the Buildup Effect of Advertising

The authors study the buildup effect of increased advertising using time series intervention analysis. The data are from an ADTEL field experiment with test and control panels connected to a split-cable TV system. Use of the control series in the analysis depends on the nature of the relevant external factors. If these factors are purely unmeasured, the control series is included as a covariate, resulting in a single-input transfer function–intervention model. If there are also measured external factors, a multiple-input model results. A careful analysis of the increased advertising shows that the buildup effect is immediate with a duration of the order of the purchase cycle.

[1]  Box Ge,et al.  Time series analysis: forecasting and control rev. ed. , 1976 .

[2]  T. Cook,et al.  Quasi-experimentation: Design & analysis issues for field settings , 1979 .

[3]  Dominique M. Hanssens,et al.  Bivariate time-series analysis of the relationship between advertising and sales , 1980 .

[4]  Lon-Mu Liu,et al.  Identification of multiple-input transfer function models , 1982 .

[5]  S. P. Raj,et al.  The Effects of Advertising on High and Low Loyalty Consumer Segments , 1982 .

[6]  Richard M. Helmer,et al.  An Exposition of the Box-Jenkins Transfer Function Analysis with an Application to the Advertising-Sales Relationship , 1977 .

[7]  F. Bass.  A Simultaneous Equation Regression Study of Advertising and Sales of Cigarettes , 1969 .

[8]  D. Aaker,et al.  Modeling Advertising-Sales Relationships Involving Feedback: A Time Series Analysis of Six Cereal Brands , 1982 .

[9]  H. Gatignon.  Competition as a Moderator of the Effect of Advertising on Sales , 1984 .

[10]  Gerald J. Eskin,et al.  Effects of Price and Advertising in Test-Market Experiments , 1977 .

[11]  Larry D. Haugh,et al.  Identification of Dynamic Regression (Distributed Lag) Models Connecting Two Time Series , 1977 .

[12]  L. Winston Ring,et al.  Measuring Sales Effects of Some Marketing Mix Variables and Their Interactions , 1976 .

[13]  Michael J. Naples.  Effective frequency : the relationship between frequency and advertising effectiveness , 1979 .

[14]  Dominique M. Hanssens,et al.  Market Response, Competitive Behavior, and Time Series Analysis , 1980 .

[15]  Johannes Ledolter,et al.  Statistical methods for forecasting , 1983 .

[16]  Lakshman Krishnamurthi,et al.  The Effect of Advertising on Consumer Price Sensitivity , 1985 .

[17]  Dean W. Wichern,et al.  Assessing the Impact of Market Disturbances Using Intervention Analysis , 1977 .

[18]  D. Clarke.  Econometric Measurement of the Duration of Advertising Effect on Sales , 1976 .

[19]  John D. C. Little,et al.  Feature Article - Aggregate Advertising Models: The State of the Art , 1979, Oper. Res..

[20]  G. C. Tiao,et al.  Modeling Multiple Time Series with Applications , 1981 .

[21]  J. Farley,et al.  How Advertising Affects Sales: Meta-Analysis of Econometric Results , 1984 .

[22]  Paul Newbold,et al.  ARIMA model building and the time series analysis approach to forecasting , 1983 .

[23]  Y. Peles,et al.  Econometric Measurement of the Duration of Advertising Effect on Sales: A Comment , 1979 .

[24]  George E. P. Box,et al.  Intervention Analysis with Applications to Economic and Environmental Problems , 1975 .

[25]  P. Kotler.  Marketing Decision Making: A Model-building Approach , 1971 .

[26]  Colin McDonald,et al.  What is the short-term effect of advertising? , 1971 .

[27]  Douglas C. Montgomery,et al.  Modeling and Forecasting Time Series Using Transfer Function and Intervention Methods , 1980 .

[28]  G. Lilien,et al.  Marketing Decision Making: A Model Building Approach , 1984 .

[29]  Scott A. Neslin,et al.  Using a Natural Experiment to Estimate Price Elasticity: The 1974 Sugar Shortage and the Ready-to-Eat Cereal Market , 1983 .

[30]  Robert P. Leone.  Modeling Sales-Advertising Relationships: An Integrated Time Series–Econometric Approach , 1983 .