To inform the design space of electronic commerce stores, increase the sales opportunities and convert browsers to buyers, it is imperative to understand consumers’ online shopping tasks. This study postulates that consumers’ shopping tasks, particularly those involving information seeking and decision making, can be classified and aggregated into a few interaction archetypes, which would require specific technology support from EC stores. With better support from the EC stores, consumers would be more satisfied with their shopping experience, more likely to make a purchase and to return loyally. After reviewing the literature, this study proposes the context-aware shopping interaction archetypes (CASIA) conceptual framework, which helps classifying shopping tasks with the characteristics of the context: customers, tasks, and products. A CASIA would share similar contexts and differ from other CASIAs in terms of cognitive efforts, behaviors, and problems encountered in carrying out the tasks. The study proposes a naturalistic case-study methodology to validate the CASIA framework.