The Advantages of Performance-Based Segmentation: An Investigation of Online Grocery Retailing

Most companies aim to identify different groups of attractive customers in order to offer them appropriate products and/or services. To do this, companies need market segmentation. There is, however, a problem with the standard methods employed in market segmentation. The static inductive approach to market segmentation commonly employed by companies does little to identify buying intentions across demographic variables. A more dynamic and deductive approach to developing market segmentation is through analysis of consumer preference structures — an approach which is glaringly absent from most marketing texts, not least because of the difficulty of developing practical approaches which can generate effective marketing strategies. The purpose of this paper is to highlight and demonstrate a preference-based approach to market segmentation, using shoppers’ experience of online grocery retail brands in the UK. The paper first demonstrates how using choice-based conjoint analysis could help achieve this objective more effectively than other more traditional conjoint methods. While conjoint analysis is not new, the ability to segment based on markedly different preference structures is a recent development and comprises a powerful, but underutilised segmentation approach. A web-based methodology is then applied to build up a picture of consumers’ conscious and unconscious prioritisation of a large number of choice criteria. The paper calculates consumer utility values for both offline and online shoppers in the UK and develops a preference-based segmentation approach, which is compared with a traditional demographic segmentation approach using the same data. From this analysis, the advantages of a preference-based approach to segmentation are extracted. The paper closes with recommendations for market research practitioners.