Factors influencing insurance customers' channel preferences in a multichannel environment - An empirical study in a Finnish insurance company

Abstract

PURPOSE OF THE STUDY This study looks into the formation of customer interaction channel preferences in a multichannel environment in the context of Finnish consumer insurance business. The primary goal of the research is to discover and examine the factors that guide consumer channel preferences based on customer characteristics. The study also strives to explore the relative effects these factors have on channels preferences and based on the found factors identify differences among customer groups. This is done by reviewing past research, viewing the underlying constructs within customer needs from a multidimensional perspective and employing multivariate analysis methods to explore the empirical data.

METHODOLY The empirical part of this thesis consists of a survey sent to a sample of customers representing a Finnish insurance company. The questions in the survey were compiled from previous studies or developed specifically to support the study at hand.

Factor analysis is performed on the variables obtained from the questionnaire in order to discover underlying value patterns in customers that influence their channel preference, in other words, to find out which factors play an important role in insurance customer channel preferences. These factors are further examined through regression analysis, which is used to explain each factor's effect on channel preferences, or the relative effect the factor has on a channel preference variable.

Cluster analysis is later performed to group customers together based on their channel preference characteristics. The cluster analysis plays an important role in transforming the results into managerial implications.

FINDINGS The principal component analysis revealed six dimensions that affect channel preference; 1) Locality & personal relations, 2) Trust in Internet, 3) Experience of branch office, 4) Experience of call center, 5) Convenience and 6) Self-reliance & privacy. From the dimensions discovered in factor analysis a regression analysis was conducted in order to compare the relative effects among these factors. The results enabled the compilation of a revised framework for channel preference formation in the context of consumer insurance services. The cluster analysis produced and described four distinctive and statistically significant customer groups, which can be used in segmentation of customers based on their channel preference. This can be useful when deciding on different channel strategies within the company.