Buyer behavior in online retail operations in apparel stores

Abstract

Online retailing started in a big way in the late nineties and grew into a major business in the past decade to become a major strategy for many retail companies. A large number of retail companies maintain brick and mortar outlets as well as online presence. It is also common for different stores to operate in the same product group (such as apparels) to have different stores targeting different customer segments. Under such circumstances, it is necessary to target the online customers differently, even though it is likely that the same customers are purchasing from both the stores. In order to achieve such differentiation, the companies need to understand the differences in customer profiles as well as their purchasing patterns. This study used K-means clustering for understanding the customer segments and web diagrams to identify the purchasing patterns. Based on the cluster analysis, the differences in customer segments are highlighted. The differences in purchase patterns are identified using the link analysis based on the web diagrams created individually for the two different types of stores.