The data preparation technique used in market segmentation to divide consumers into different homogeneous groups is called

The data preparation technique used in market segmentation to divide consumers into different homogeneous groups is called cluster analysis. This technique involves statistical methods to identify distinct groups within a dataset based on similarities in consumer characteristics, behaviors, or preferences.

Cluster analysis categorizes individuals into subsets where members of each subset are more similar to each other than to those in other subsets. By utilizing various clustering algorithms, such as K-means or hierarchical clustering, marketers can effectively segment the market, allowing for tailored marketing strategies that meet the specific needs of each group.

This approach helps businesses identify target demographics, understand consumer behavior, and optimize their marketing efforts, ultimately leading to improved customer satisfaction and increased sales. Cluster analysis is a critical element in data preparation for effective market segmentation.