Optimizing User Engagement in Enterprise Knowledge Management: Insights and Innovations from a Confluence Pages Project

Abstract

In the pursuit of enhancing user engagement within Confluence-based knowledge repositories, this paper details the development of an advanced scoring system tailored to evaluate content efficacy. Central to this system is the normalization of disparate content metrics against a common scale and the strategic weighting of key performance indicators—such as engagement, timeliness of updates, frequency of edits, content length, and collaborative contributions. The confluence of these metrics culminates in a composite score per content piece, enabling a nuanced appraisal of its value. Employing Z-scores for benchmarking facilitates the delineation of content into actionable tiers, thus informing a data-driven approach to content management. This scoring framework, with its capacity to quantify and qualify user-content interaction, presents a transformative tool for knowledge management, ensuring that content not only resonates with its audience but also aligns with organizational objectives.