EXPRESS: The Value of Genetic Data in Predicting Preferences: a Study of Food Taste

Abstract

The exponential expansion of consumer genetic testing has led to an accumulation of massive genomic datasets owned by governments and firms. The prospect of leveraging genetic data for enhancing consumer’s health, well-being and satisfaction, through improved personalization, segmentation, and targeting is promising. Nonetheless, this potential has not been studied empirically to date and it is unknown whether and when resources should be invested into incorporating genetic data into strategies and processes. We address this gap in a study of taste preferences, important drivers of food and beverages consumption. Using a large UK-based sample, we find that with sample sizes currently available, genetic data is expected to significantly improve prediction of taste preferences above traditionally used metrics such as demographics, behavioral variables, and even past consumption, especially for tastes that are uncommon in the local diet (e.g., spicy and sour) as they are less expressed behaviorally. We conclude that genetic data shows immense promise for prediction-based applications when other data sources are limited or uninformative. These findings could have significant implications for public health initiatives, potentially aiding development of personalized nutrition plans and dietary interventions.