Decision maker satisfaction in a web analytics context: the impact of analysts’ skills
thesisposted on 2021-06-08, 10:33 authored by Stephen Verspan
This quantitative research targets decision makers, who rely on the analysis of web data (web analytics) in order to make strategic decisions. As identified in the literature, important factors in a web analytics context are information quality, human factors and the presence of actionable insights. Thus, the research had two objectives. The first objective was to provide a better understanding of the skill(s) that matter(s) the most when hiring, training, or working with a web analyst, with the objective of obtaining actionable insights from the reports the team of web analysts prepares. The second objective was to propose a model – based on the DeLone and McLean’s (2002) Information Systems (IS) success model – that predicts web analytics success on the basis of decision maker satisfaction, which in turn depends on information quality, and business, analytical and technical skills of a team of web analysts. The results obtained from this study reveal that web data analysis expertise, and the ability to provide agreed upon practical insights are key skills that have a significant impact on decision maker satisfaction. These findings are beneficial to several stakeholders, such as academia, researchers, and the business community, as they provide empirical evidence that may help develop curriculum, provide directions for future research, and determine what profiles to target when hiring or training web analysts. Furthermore, these results provide evidence of the reliability of the proposed research model, and the applicability of the DeLone et al.’s (2002) IS success model to the WA context.