Analysis Approaches to Moment By Moment Reactions to Commercials: Discussion For Special Session on Moment By Moment Analyses of Tv Commercials


Linda F. Alwitt (1991) ,"Analysis Approaches to Moment By Moment Reactions to Commercials: Discussion For Special Session on Moment By Moment Analyses of Tv Commercials", in NA - Advances in Consumer Research Volume 18, eds. Rebecca H. Holman and Michael R. Solomon, Provo, UT : Association for Consumer Research, Pages: 550-551.

Advances in Consumer Research Volume 18, 1991      Pages 550-551


Linda F. Alwitt, DePaul University

Most evaluations of advertising are overall reactions collected after exposure of the advertisement. These evaluations are either short-term, like recall or persuasion, or long-term like ad or sales tracking. Post-exposure copytesting assumes that reactions to advertising depend on the effect of the total commercial, and that they transcend the sum of reactions to each part of an ad. The latter assumption makes sense because parts of an ad interact with each other to produce an overall effect, and because the past experiences and current mood states of individuals interact with the content of a commercial to produce an overall reaction. However, when post-exposure reactions to advertising are analyzed, one must infer what caused consumers to reach their evaluations. That is, one must infer what a marketer must do to persuade a consumer to take action such as buying the advertised brand.

Moment by moment approaches to evaluating reactions to television commercials offer an opportunity to learn how consumers form their evaluations. These approaches allow us to dissect overall reactions and extract the aspects of a commercial that can be controlled by marketers. This is potentially the most valuable contribution of moment to moment analyses of television commercials.

Four types of variables can be used to dissect overall reactions to advertising using moment by moment approaches: person; product; medium; content.

Person variables include traits such as the speed of reaction to events within a commercial, the time delay between comprehending the content of a commercial and crystallizing an evaluation, the influence of mood due to the program context, and persistence. Persistence refers to the tendency of a viewer to respond at time t in the same way he responded at time t - 1. Examples of product variables are levels of involvement with the category and the brand, awareness Of the brand's current and past positioning, and the brand's advertising history. Variables related to the medium of television involve how people react to on-going events. One example is the phenomenon of attentional inertia (Anderson 1985). Another is how people chunk on-going events into meaningful units (e.g., Newtson 1973). Content variables include the relevance of the message, the creative approach such as the distinction between lecture and drama commercials (Wells 1989) and the structure of the ad. An example of ad structure is a 'poignant' emotional problem-solving ad (Thorsen 1989). Research on moment by moment reactions to advertising has just started to examine these types of variables.

Moment by moment researchers have developed rather sophisticated ways of gathering and describing their results (e.g., Polsfuss and Hess this volume; Young & Robinson this volume), but have just started to explore ways to analyze the data in order to address some of the issues involved in dissecting overall evaluations of a brand based on its advertising. Two methodological questions are important:(1) what should be the units of analysis? (2) what analytic techniques should be used?

The unit of analysis depends on the issue being addressed. The total pattern of response for an entire commercial, for example, might be an appropriate unit of analysis for evaluating persistence, positioning, chunking of events into meaningful units, or creative strategy. Reactions to specific events within a commercial might be the appropriate unit for studying the speed of reaction to events, positioning, context effects within a commercial or ad structure. Individual viewers might be the appropriate unit of analysis for evaluating response styles, involvement, familiarity with the brand's advertising history, or message relevance.

A great strength of the moment by moment approach is that it tells us how a viewer changes over the course of a commercial. This calls for analytic techniques that take into account that:

a. events in a commercial are ordered in a sequence;

b. an event at time t is related to events at time t-n and t+n;

c. the response at time t is likely to be related to the response at time t - n as well as events at time t - n.

That is, analysis of moment by moment data calls for time-series analysis. Since time-series analysis has not been commonly used for evaluating reactions to advertising, we must learn how to apply and interpret these methods. Different time-series approaches suit different issues. For example, to analyze the pattern of reactions to an entire commercial, one might use Fourier analysis (Kaplan 1983), ARIMA and econometric regression approaches (Makridakis, Wheelwright & McGee 1983), or profile analysis (Greenhouse & Geisser 1959; Cole & Grizzle 1966). To analyze the effects of specific events within a commercial, Markov analysis or lag sequential analysis (e.g., Gottman & Roy 1990) should be useful.

Analysis of moment by moment reactions to television commercials is in its infancy. It offers opportunities to address issues which can only be inferred from post-viewing reactions to commercials, issues about how persuasion works. To take advantage of these opportunities, we will have to apply new techniques such as the various time-series analytic approaches.


Anderson, Daniel R. (1985) Online cognitive processing of television. In L.F. Alwitt & A.A. Mitchell (Eds), Psychological Processes and Advertising Effects, Hillsdale,N.J.: Erlbaum.

Cole, J.W.L. & James E. Grizzle (1966) Applications of multivariate analysis of variance to repeated measures experiments. Biometrics, 22, 810-828.

Gottman, John M. & Anup K. Roy (1990) Sequential Analysis. Cambridge: Cambridge University Press.

Greenhouse, Samuel W. & Seymour Geisser (1959) On methods in the analysis of profile data Psychometrika, 24(2), 95-112.

Kaplan, Howard L. (1983) Correlations, contrasts, and components: Fourier analysis in a more familiar terminology. Behavioral Research Methods and Instrumentation, 15(2), 228-241.

Newtson, Darren. (1976) Attribution and the unit of perception of ongoing behavior. Journal of Personality and Social Psychology, 28, 28-38.

Makridakis, Spyros, Steven C. Wheelwright & Victor E. McGee (1983), forecasting:Methods and Applications, 2nd ed., New York: Wiley.

Polsfuss, Mark & Mike Hess (1990), 'Liking' through moment-to-moment evaluation: identifying key selling segments in advertising, Advances in Consumer Research, this volume.

Thorsen, Esther & Marion Friestad (1989) The effects of emotion on episodic memory for television commercials. In P. Cafferata & A. Tybout (Eds.) Cognitive and Affective Responses to Advertising. Lexington, MA: Lexington Books.

Wells, William D.(1989) Lectures and Dramas, In P. Cafferata & A. Tybout (Eds.) Cognitive and Affective Responses to Advertising. Lexington, MA: Lexington Books.

Young, Charles & Michael Robinson (1990) The visual experience of new and established product commercials, Advances in Consumer Research, this volume.



Linda F. Alwitt, DePaul University


NA - Advances in Consumer Research Volume 18 | 1991

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