Market segmentation strategies for complex automotive products

With the advent of 'big data', the purpose of this empirical study was to take the opportunity to rethink conventional market segmentation strategies. This is particularly relevant for the automotive industry which is going through a period of rapid change with advanced technologies such as electric powered and autonomous vehicles, creating increased concerns as to how this complexity is communicated effectively. A mixed methods approach was utilised to collect data from multiple sources, incorporating in-depth discussion groups, semi-structured interviews, an online survey, and data collection of communication processes through the attendance of new car product launches. The results suggest that marketing departments should rethink their data capture methods to collect more relevant consumer information, not the contemporary trend of needs, attitude, and motivation variables that are difficult to identify and collect, but basic information on their level of familiarity with products through previous experience and exposure. The basic dimensions identified are characterised by a consumer's expertise, involvement, and familiarity with a product. The findings are synthesised into a theoretical framework to define differing levels of product complexity, which would enable manufacturers to provide more closely defined market segmentation strategies when communicating new product information.