Judging the success of a Knowledge Base (KB) requires tracking specific metrics that reflect how well it serves users and supports organisational goals. Measuring the success of your Knowledge Base is important because it ensures that system is delivering value, driving continuous improvement and ROI.
A combination of KPIs, search success rates and user satisfaction will provide the widest view of how successful your knowledge management initiative is.
Usage Metrics
These show how frequently and actively the KB is being used. Knowledge Management systems often have inbuilt reports to show the level of user activity, showing the article views and searches. High view counts suggest strong engagement or high demand for the content.
For authors, the number of new documents or revisions made to existing content can be measured, ensuring the vitality of the content.
Search Metrics
These reveal how effectively users are finding what they need. User search analytics are often inbuilt into knowledge management systems, showing not only the searches made but which documents were viewed from the search, whether a document was marked as being useful and which users are performing the searches.
Search Queries: Analyse common queries to ensure key topics are well covered.
Search Success Rate: % of searches that result in a click or article read.
Failed Searches / Zero Results: Helps identify content gaps.
Content Quality Metrics
These help measure the value and relevance of the content. If possible within your knowledge management system, encourage users to provide feedback in the form of likes/favourites and marking documents as helpful to resolve a search query, which gives a direct signal of content effectiveness.
- The number of reworks requested against an article will ensure content is kept up to date and means you can prioritise updates and new content based on real user needs, saving time and increasing operational efficiency.
- Providing Just In Time (JIT) edits to authors will make updates to content as simple as possible. Alongside regular audits to check for outdated or incorrect information the content quality and scheduled review periods, the content accuracy and freshness can be maintained.
Operational Efficiency Metrics
For customer service implementations, it is possible to measure how the KB reduces support load, such as;
- Case Deflection Rate: % of support requests avoided thanks to the KB.
- Ticket Reduction Over Time: Decline in support tickets after launching or updating KB.
- Top Articles Viewed Before Ticket Submission: Indicates whether users are attempting self-help first.
Measuring success shows whether it’s actually reducing the burden on your support teams, a well-performing KB reduces the volume of support tickets or internal queries, saving time and resources.
Customer Satisfaction Surveys
Gather user satisfaction scores after using the KB to determine perceived helpfulness. Including short surveys after article views or in follow-up emails can be a useful resource.
How to Judge Overall Success:
High usage + high satisfaction + high case deflection = successful KB.
Use a combination of quantitative (analytics) and qualitative (feedback) metrics.
In short, if you don’t measure it, you can’t manage it. Without success metrics, your KB becomes a “black box” where you’re guessing about its effectiveness instead of optimising it with confidence.
