From Personality to Pour: How Consumer Traits Shape Wine Preferences and Alcohol Choices

This study aims to examine how personality traits influence consumer preferences for wine alcohol content (ABV), an area that remains underexplored in wine marketing research.

Drawing on the Big Five Personality Traits framework, this study employed natural language processing (NLP) and BERT (Bidirectional Encoder Representations from Transformers) to infer personality traits from 9917 consumer reviews collected from an e-commerce wine platform. A beta regression model was then used to analyze the relationship between inferred personality traits and wine ABV preferences.

The results reveal that openness and agreeableness are positively associated with higher ABV preferences, while extraversion and neuroticism show negative associations. Conscientiousness did not exhibit a significant relationship with ABV preferences.

The findings indicate that personality traits significantly shape consumer evaluations of wine intensity and validate the predictive power of AI-based personality inference. This research contributes to consumer behavior theory and offers practical implications for developing personalized wine recommendations and targeted marketing strategies in digital retail environments.