Validating Gravity-Based Market Share Models Using Large-Scale Transactional Data

Area of Science:

• Marketing Science
• Spatial Analysis
• Retail Analytics

Background:

• Customer patronage behavior is crucial for market share modeling, retail sales estimation, and competitive location analysis.
• Traditional methods rely on surveys, but Big Data offers more realistic insights into consumer decision-making.
• The Huff gravity model is widely used but lacks validation with real-world transactional data.

Purpose of the Study:

• To introduce a novel approach for validating the Huff gravity market share model.
• To utilize a large-scale transactional dataset for empirical validation.
• To assess the model's applicability across different regions and merchant categories.

Main Methods:

• Validation of the Huff gravity model using a comprehensive regional transactional dataset.
• Analysis of customer patronage behavior data.
• Regression analysis to identify factors influencing model validation.

Main Results:

• The Huff model demonstrates a strong fit for modeling customer shopping behavior in categories like grocery, clothing, gas stations, and restaurants.
• The model's validation is significantly strengthened by demographic diversity features, such as gender and marital status diversity.
• Empirical evidence supports the viability of gravity-based market share models.

Conclusions:

• The Huff gravity model is a viable tool for retail sales estimation and competitive facility location when validated with real transactional data.
• Demographic diversity is a key factor influencing the accuracy of gravity-based market share models.
• This data-driven approach facilitates the application of the Huff model in diverse retail contexts.