A 'hidden' side of consumer grocery shopping choice

摘要

This study identifies hidden classes of grocery shoppers and their choice of different items on different days of the week. Following the literature on consumer grocery shopping, three major groups of products are considered: food/drink, cleaning, and personal care. Applying Finite Mixture Modeling to a rich scanner dataset, latent classes of customers and their choice of grocery items on different days of the week are discovered and empirically validated. The model controls for consumer unobserved heterogeneity and demographic characteristics through mixing probabilities. Results uncover latent classes of grocery shoppers and their day of the week shopping day, their sizes, their product choices, mixing probabilities, and demographics. Findings offer retail promotion targeting guidelines for the identified latent classes in the food/drink, cleaning, and personal care groups. Analysis outcome provides marketing and managerial implications in identifying grocery store segments, handling store traffic, managing store promotion and pricing, and improving store layout.