eThesis - Kauppakorkeakoulun sähköiset gradut

Multichannel customer management and consumer behavior have previously been studied in conventional retail environment, where products are usually homogeneous. Multichannel customer management is about using more than one channel, such as brick-and-mortar store, telephone or the Internet to manage customers in a consistent and coordinated way. This thesis takes a previously unexplored view to the topic by studying it in the context of an art and antiques auction. Not only is there a difference between auctions and fixed price trade as transaction mechanisms, but also between the commodities sold in art and antiques auctions and conventional retail stores. Items sold at this kind of auctions tend to be unique. Art above all other product categories is most prone to uncertainty concerning authenticity especially when sold online.

The purpose of this study is to identify customer groups of a private art and antiques auction house based on customers' previous purchase behavior that is related to their individual psychographic and demographic profiles. The auction house organizes auctions both live and online. Identifying customer groups is one of the primary issues in multichannel customer management. By identifying these groups and understanding their characteristics, companies can design their channels better and target marketing more efficiently. In addition to previously studied psychographics, an additional psychographic is included to measure customer trust in online shopping. Trust is a particularly significant factor in the uncertain environment of electronic commerce. Its role is even more enhanced in the art and antiques market.

An online questionnaire was used for data collection. Principal components analysis was conducted to find a smaller number of underlying psychographic variables. Customers were grouped with k-means clustering based on the number of purchases they had made live and online since both channels had been simultaneously available. Cross tabulations were conducted to study the relationship between the identified groups and demographics. Finally, a multinomial logistic regression was used to answer the main research question of how the customers' psychographic profiles relate to their purchase channel orientation. In other words, the relationship between cluster membership and the principal components derived from factor analysis was studied.

As a final result, four distinctive customer groups, which all differ in their purchase channel orientation, were identified. In addition, a few significant psychographics were found to predict channel orientation. Surprisingly, the impact of these psychographics turned out to be the opposite in most cases. Of the demographics, only gender distribution differed between the identified groups. The more involved customers were with the auction house and the more they had purchased in live auctions, the more likely they were males. The results proved once again to be very different from previous studies, where customers' individual differences were used to identify clearly defined customer groups. They show that the outcome for identified groups depends on the context and variables used in the study.