Using principal components analysis to understand consumers' moment-to-moment affect traces and their influence on ad and brand attitudes

Marketers and advertisers have long searched for new and more powerful ways to measure the effectiveness of advertising. One data source that has proven useful is consumers’ moment-to-moment affective responses to advertisements. The first essay of my dissertation examines consumers’ moment-to-moment evaluations of advertisements and presents an application of principal components analysis that allows researchers to understand divergence in consumer response and link this divergence to specific elements of the ad’s storyline. While traditional research has focused on the aggregate peak, final moment and linear trend of consumers’ affect traces in predicting overall evaluations of the advertisement, this application provides better predictions of holdout evaluations. Additionally, I find these traditional measures do not provide insight into consumers’ credibility assessments of the advertisement and illustrate that these evaluations are determined much earlier in the advertisement. The second essay of my dissertation examines how important consumer characteristics (receiver factors), such as prior brand attitude and product category involvement, impact consumers’ moment-to-moment affective responses to advertisements. I also examine how these consumer characteristics moderate the relationship between consumers’ affect traces and important downstream variables such as attitude toward the ad, attitude toward the brand and likelihood to purchase the product. I demonstrate that consumers form biased evaluations based on their prior brand attitude and category involvement and illustrate how advertisers can reduce these biases resulting in greater attitude change in consumers less positively predisposed to the product.