Gut Liking for the Ordinary: Incorporating Design Fluency Improves Automobile Sales Forecasts

Automotive sales forecasts traditionally focus on predictors such as advertising, brand preference, life cycle position, retail price, and technological sophistication. The quality of the cars' design is, however, an often-neglected variable in such models. We show that incorporating objective measures of design prototypicality and design complexity in sales forecasting models improves their prediction by up to 19%. To this end, we professionally photographed the frontal designs of 28 popular models, morphed the images, and created objective prototypicality (car-to-morph Euclidian proximity) and complexity (size of a compressed image file) scores for each car. Results show that prototypical but complex car designs feel surprisingly fluent to process, and that this form of surprising fluency evokes positive gut reactions that become associated with the design and positively impact car sales. It is important to note that the effect holds for both economy (functionality oriented) and premium (identity oriented) cars, as well as when the above-mentioned traditional forecasting variables are considered. These findings are counter to a common intuition that consumers like unusual–complex designs that reflect their individuality or prototypical–simple designs that are functional.