The Nature of Learning about Customers in a Customer Service Setting - A Study of Frontline Contact Persons

The starting point of this thesis is the notion that in order for organisations to understand what customers value and how customers experience service, they need to learn about customers. The first and perhaps most important link in an organisation-wide learning process directed at customers is the frontline contact person. Service- and sales organisations can only learn about customers if the individual frontline contact persons learn about customers. Even though it is commonly recognised that learning about customers is the basis for an organisation’s success, few contributions within marketing investigate the fundamental nature of the phenomenon as it occurs in everyday customer service. Thus, what learning about customers is and how it takes place in a customer-service setting is an issue that is neglected in marketing research. In order to explore these questions, this thesis presents a socio-cultural approach to understanding learning about customers. Hence, instead of considering learning equal to cognitive processes in the mind of the frontline contact person or learning as equal to organisational information processing, the interactive, communication-based, socio-cultural aspect of learning about customers is brought to the fore. Consequently, the theoretical basis of the study can be found both in socio-cultural and practice-oriented lines of reasoning, as well as in the fields of service- and relationship marketing. As it is argued that learning about customers is an integrated part of everyday practices, it is also clear that it should be studied in a naturalistic and holistic way as it occurs in a customer-service setting. This calls for an ethnographic research approach, which involves direct, first-hand experience of the research setting during an extended period of time. Hence, the empirical study employs participant observations, informal discussions and interviews among car salespersons and service advisors at a car retailing company. Finally, as a synthesis of theoretically and empirically gained understanding, a set of concepts are developed and they are integrated into a socio-cultural model of learning about customers.

Clustering Users of Online Content Service

Online content services can greatly benefit from personalisation features that enable delivery of content that is suited to each user's specific interests. This thesis presents a system that applies text analysis and user modeling techniques in an online news service for the purpose of personalisation and user interest analysis. The system creates a detailed thematic profile for each content item and observes user's actions towards content items to learn user's preferences. A handcrafted taxonomy of concepts, or ontology, is used in profile formation to extract relevant concepts from the text. User preference learning is automatic and there is no need for explicit preference settings or ratings from the user. Learned user profiles are segmented into interest groups using clustering techniques with the objective of providing a source of information for the service provider. Some theoretical background for chosen techniques is presented while the main focus is in finding practical solutions to some of the current information needs, which are not optimally served with traditional techniques.