Applying web analytics in a K‐12 resource inventory

This paper seeks to investigate how to use a web analytics tool to conduct deep analysis of users' web behaviors. This study aims to focus on examining whether the types of traffic sources and temporal fluctuation influence the web visitors' performance on the web portal of a K‐12 resource inventory.

One year's data were collected via the Advanced Segmentation function of Google Analytics. To compare visitors' behavior from different types of traffic recourses with the intervention of temporal effect, clickstream data of three visitor segments were collected.

Traffic sources and temporal effect have been found to influence web site visitors' performance interactively. Search engines seemed good at bringing a significantly large amount of traffic to the eThemes site, but most visitors are likely “information encounters”. However, visitors from direct traffic (bookmark/typed URLs) seemed to visit the eThemes site purposefully – stay for a long time on the site and view more web pages. Additionally, loyal users of the site seemed to employ the eThemes site as an everyday life information source.

This study introduces a strategic approach to study and analyzes web site visitors' behavior longitudinally. The findings of this study contribute to loyal user behavior identification. Empirical evidence has been found to support the correlational relationship between traffic sources, the temporal factor, and Key Performance Identifiers of a site.