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Knowledge Base
Project Manager Guide
Analytics, maintenance schedules, project metrics, and the decision framework for knowledge base managers — what to measure, when to act, and how to keep the content system healthy.
What to measure
Track these metrics after launch to drive improvement decisions. Set up monthly reviews.
Most viewed articles
Identify the articles users rely on most. These are your highest-value content and should be prioritized for accuracy and freshness.
Searches with no results
These represent content gaps. Every failed search is a topic that needs an article. Review monthly and assign writing tasks.
Ticket deflection rate
How often users self-serve instead of opening a support ticket. Tracks the business value of the knowledge base.
Chatbot fallback rate
How often the AI chatbot cannot answer a question. High rates signal missing or unclear source content.
Article feedback scores
Low-scoring articles need rewriting. High scores indicate what good looks like — use those as templates.
Human handoff rate
How often the chatbot escalates to a human. Tracks chatbot effectiveness and identifies training gaps.
Maintenance schedule
A knowledge base that is not maintained becomes a liability. Use this schedule to stay current.
Project success indicators
Articles delivered on schedule100%
Articles passing quality review on first submission>80%
Searches returning relevant results>90%
Chatbot fallback rate post-launch<15%
Support ticket volume change (3 months post-launch)Measurable reduction