Decision support and online advertising: Development and empirical testing of a data landscape

Abstract

The number of data sources available inside and outside companies and total data points increase, which makes the coordinated data selection in the forefront of decision making with respect to a specific economic goal becomes more and more relevant. To assess the available data and enhance decision support, we develop a framework including a process model that supports the identification of goal-oriented research questions and a data landscape that provides a structured overview of the available data inside and outside the company. We empirically tested the framework in the field of online advertising to enhance decision support in managing display advertising campaigns. The test reveals that the developed data landscape supports the identification and selection of decision-relevant data and that the subsequent analysis leads to economic valuable results.