Background: Visual salience computed using algorithmic procedures have been shown to predict eye-movements in a number of contexts. However, despite calls to incorporate computationally-defined visual salience metrics as a means of assessing the effectiveness of advertisements, few studies have incorporated these techniques in a marketing context. The present study sought to determine the impact of visual salience and knowledge of a brand on eye-movement patterns and buying preferences.
Methods: Participants (N=38) were presented with 54 pairs of products presented on the left and right sides of a blank white screen. For each pair, one product was a known North American product, such as Fresca?, and one was an unknown British product of the same category, such as Irn Bru?. Participants were asked to select which product they would prefer to buy while their eye movements were recorded. Salience was computed using Itti & Koch’s [2001] computational model of bottom-up salience. Products were defined as highly salient if the majority of the first five predicted fixations were in the region of the product.
Results: Results showed that participants were much more likely to prefer to buy known products, and tentative evidence suggests that participants had longer total dwell times when looking at unknown products. Salience appears to have had little or no effect on preference for a product, nor did it predict total dwell time or time to first fixation. There also appears to be no interaction between knowledge of a product and visual salience on any of the measures analyzed.
Conclusions: The results indicate that product salience may not be a useful predictor of attention under the constraints of the present experiment. Future studies could use a different operational definition of visual salience which might be more predictive of visual attention. Furthermore, a more fine-grained analysis of product familiarity based on survey data may reveal patterns obscured by the definitional constraints of the present study.
Background: Visual salience computed using algorithmic procedures have been shown to predict eye-movements in a number of contexts. However, despite calls to incorporate computationally-defined visual salience metrics as a means of assessing the effectiveness of advertisements, few studies have incorporated these techniques in a marketing context. The present study sought to determine the impact of visual salience and knowledge of a brand on eye-movement patterns and buying preferences.
Methods: Participants (N=38) were presented with 54 pairs of products presented on the left and right sides of a blank white screen. For each pair, one product was a known North American product, such as Fresca?, and one was an unknown British product of the same category, such as Irn Bru?. Participants were asked to select which product they would prefer to buy while their eye movements were recorded. Salience was computed using Itti & Koch’s [2001] computational model of bottom-up salience. Products were defined as highly salient if the majority of the first five predicted fixations were in the region of the product.
Results: Results showed that participants were much more likely to prefer to buy known products, and tentative evidence suggests that participants had longer total dwell times when looking at unknown products. Salience appears to have had little or no effect on preference for a product, nor did it predict total dwell time or time to first fixation. There also appears to be no interaction between knowledge of a product and visual salience on any of the measures analyzed.
Conclusions: The results indicate that product salience may not be a useful predictor of attention under the constraints of the present experiment. Future studies could use a different operational definition of visual salience which might be more predictive of visual attention. Furthermore, a more fine-grained analysis of product familiarity based on survey data may reveal patterns obscured by the definitional constraints of the present study.
