Advertising cost interactions and the optimality of pulsing
Management Science
Dynamic optimal control models in advertising: recent developments
Management Science
Bayesian forecasting and dynamic models (2nd ed.)
Bayesian forecasting and dynamic models (2nd ed.)
Eye Tracking Methodology: Theory and Practice
Eye Tracking Methodology: Theory and Practice
Planning Media Schedules in the Presence of Dynamic Advertising Quality
Marketing Science
On Continuous-Time Optimal Advertising Under S-Shaped Response
Management Science
Bayesian Statistics and Marketing
Marketing Science
Optimal Feature Advertising Design Under Competitive Clutter
Management Science
Marketing Science
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We develop a conceptual framework about the impact that branding activity (the audiovisual representation of brands) and consumers' focused versus dispersed attention have on consumer moment-to-moment avoidance decisions during television advertising. We formalize this framework in a dynamic probit model and estimate it with Markov chain Monte Carlo methods. Data on avoidance through zapping, along with eye tracking on 31 commercials for nearly 2,000 participants, are used to calibrate the model. New, simple metrics of attention dispersion are shown to strongly predict avoidance. Independent of this, central on-screen brand positions, but not brand size, further promote commercial avoidance. Based on the model estimation, we optimize the branding activity that is under marketing control for ads in the sample to reduce commercial avoidance. This reveals that brand pulsing---while keeping total brand exposure constant---decreases commercial avoidance significantly. Both numerical simulations and a controlled experiment using regular and edited commercials, respectively, provide evidence of the benefits of brand pulsing to ward off commercial avoidance. Implications for advertising management and theory are addressed.