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Abstract
Eye tracking technology allows for a relatively direct and continuous measurement of unconcealed visual attention. In the consumer goods market today, it is important for companies to make their brand or product stand out within a vast competitive array. Even though it is highly unlikely that a product would be purchased without having been noticed (unseen is unsold), it is important to investigate if products that garner high attention are in fact purchased in the marketplace, and if a correlation between the two metrics exists. Through the utilization of real consumers in an immersive consumer retail experience laboratory, an eye tracking study on seasoned breading mix was conducted to test the correlation between attention and sales data. Data captured from 37 study participants were used to create a regression model by utilizing the Fit Y by X function in the statistical program JMP Pro 12. Statistical analysis indicated that including attention metrics in the prediction model significantly improves the ability to predict average sales. Demographics such as gender, age, relationship status, education, employment, shopping habits were also investigated in order to understand the trends of individual participants to find ideal consumers. Overall, eye tracking is a viable option to foreshadow sales and attention performance within this category.
Recommended Citation
Rice, Julie C.; Hurley, Andrew; Griffin, Sarah; Whiteside, William S.; and Dawson, Paul
(2019)
"Influence of Visual Attention on the Likelihood of Choice Through Regression Analysis,"
Journal of Applied Packaging Research: Vol. 11:
No.
1, Article 2.
Available at:
https://repository.rit.edu/japr/vol11/iss1/2