Segmenting the Retail Customers

Abstract

The goal of “serving all” is similar to “serving none.” Marketers are constantly looking for ways to refine the way they segment markets. Segmentation involves diving markets into smaller portions (segments) of consumers with similar needs for a given good or service. This chapter explores the application of various algorithms and analytical techniques that are used to segment markets. These techniques include regression, cross-tabulation, hierarchical clustering, and k-means clustering performed through analytical tools such as R-Studio and MS Excel. The analyses drew upon the “customer data” dataset, which contained eight variables: age, income, marital status, ownership status, household size, family total sales, and family total visit. The findings demonstrate how such statistics could help the businesses understand the customers and target the specific customer with unique campaigns and offerings.

The Metaverse and Web 3.0

“…The rising disruptive power of artificial intelligence technology has changed the phase of marketing (Anifa et al, 2022). Methods in artificial intelligence that facilitate the processing and understanding of human language, with applications in the development of intelligent and conversational user interfaces.…”