Discovering Design Principles of Web Analytics Tools: A Text Mining Approach
Yousra Harb, Yanyan Shang, Lamar Al-Musa
2020Journal of the Association for Information Systems11 citations
Abstract
With the popularity of the Internet and web-based business model, web analytics tools have increasingly drawn attention. This study aims to discover the design principles of web analytics tools from the analysis of users’ feedback from the actual use of the tools. Specifically, we employed text mining (clustering algorithm) to extract the design principles from online user reviews of web analytics. Overall, the results highlight the necessity to incorporate the product, technical, and experience design principles into web analytics tools design. Keywords Web analytics, design features, text mining, clustering, users reviews.
Topics & Concepts
Computer scienceAnalyticsWeb analyticsData scienceWeb miningWorld Wide WebWeb intelligenceThe InternetWeb pageWeb modelingWeb Data Mining and AnalysisData Mining Algorithms and ApplicationsWeb Applications and Data Management