Analyzing Demographic Grocery Purchase Patterns in Kenyan Supermarkets Through Unsupervised Learning Techniques

Abstract

This study applies unsupervised machine learning techniques to analyze grocery purchase patterns in Kenyan supermarkets. By identifying latent demographic and consumption clusters, the research provides insights into consumer behavior and nutrition transitions. The findings demonstrate the value of data-driven approaches for informing public health nutrition and market interventions.