Textual feature engineering for purchase intent and customer satisfaction: Insights from marketing 4.0 and sentiment

This study examines how textual features in customer reviews influence consumer behavior metrics like Purchase Intention and Customer Satisfaction. By analyzing 329,658 Yelp reviews in the ''Hotels & Travel'' category, sentiment analysis categorized reviews as positive, neutral, or negative. Keywords related to Customer Satisfaction, Purchase Intention, and brand attributes were generated using ChatGPT and used to create binary features in the analysis. The results showed a strong positive correlation between sentiment and both Purchase Intention and Customer Satisfaction. Additionally, Brand Identity, Brand Image, and Customer Interaction positively impacted Purchase Intention, while Brand Integrity showed mixed effects on consumer behavior.