Unveiling Disparities in Beer Consumer Behavior and Key Drivers Across Regions in China

Area of Science:

• Consumer Behavior Analysis
• Machine Learning Applications
• Regional Market Segmentation

Background:

• Beer consumption in China shows significant regional differences.
• Understanding these regional variations is crucial for effective market strategies.

Purpose of the Study:

• To analyze sensory preferences and influencing factors of Chinese beer consumers across different regions.
• To reveal the core driving mechanisms behind regional beer consumption behaviors.

Main Methods:

• Integrated regional consumer data including sensory attributes (bitterness, malt flavor, hop aroma, mouthfeel, foam) and consumption variables (brand, packaging).
• Employed machine learning models such as ensemble learning (LightGBM), Support Vector Machine (SVM), and decision trees for feature mining.

Main Results:

• Consumers in mature markets prioritize drinking experience and drinkability.
• Consumers in scale-dominant markets focus on foam persistence, fineness, and color.
• Consumers in growth markets exhibit strong brand orientation.

Conclusions:

• Regional heterogeneity significantly impacts factors influencing Chinese beer consumption.
• Data-driven insights support cross-regional product customization, precision marketing, and resource optimization in the Chinese beer market.