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

Authors

  • Arun Chandramouli USA Author

DOI:

https://doi.org/10.47363/8c38pa49

Keywords:

Optimizing, User Engagement, Enterprise Knowledge Management, 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.

Author Biography

  • Arun Chandramouli, USA

    Arun Chandramouli, USA

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Published

2023-11-23

How to Cite

Optimizing User Engagement in Enterprise Knowledge Management:Insights and Innovations from a Confluence Pages Project. (2023). Journal of Artificial Intelligence & Cloud Computing, 2(4), 1-5. https://doi.org/10.47363/8c38pa49

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