This chapter discusses the empirical (i.e., Lockean) aspects of information services. The empirical approach measures and analyzes data of an information service and its stakeholders and context. Such data are important for revenue collection (e.g., showing evidence for a bill) and for generating insights to improve the service. This chapter focuses on the latter, because improvement is the fi nal step in design science. The type of data needed for improvement diff ers for the diverse levels of management decision-making. The empirical analysis can be done at the strategic level by measuring siteaccess, and infl uencing the audience to increase these numbers by “search engine optimization”. At the operational level web analytics can be used to improve insights in the performance of certain parts of information services. Finally, we discuss user questionnaires as a means of fi nding improvement suggestions. Topics in this chapter are:

Supplier-oriented performance indicators• Search engine optimization (SEO) and web analytics• User evaluation questionnaires•


This chapter approaches service exploitation from a management control perspective, in which an information service manager collects data to be compared with the goals and objectives of the service (which should have been defi ned during business modeling). For this the manager can apply a black box and a white box model. In the black box model, the manager compares his or her objectives with data from the infl ow and outfl ow. These data may be about how people can fi nd the service and from where they enter the service, which is largely serviced by search engine optimization tools. The outfl ow data check the satisfaction of the users with the service, e.g., by user questionnaires. In the white box

model, the manager checks data internal to the operation of the service with the objectives of the service. This can be done by tracing the user’s path in the service by web analytics, and by a more in-depth analysis of the service’s internal organization and operations. These methods are presented in Figure 6.1.