What Are Knowledge Base Analytics?
What Are Knowledge Base Analytics?
Knowledge base analytics help determine the content being searched for and viewed, as well as the general health of the content being served.
This is especially important when your knowledge base is public or client facing. Without analytics you won’t be able to tell what kind of content resonates with your audience and what they are looking for in terms of information.
Analytics for analyzing knowledge base performance can be broken into three categories.
- Content analytics – what content is being viewed?
- Contribution analytics – who is providing content?
- Search analytics – what is being searched for?
Each of these categories provides insights to help you gauge the health of your content and the level of customer engagment.
Understanding who is viewing what content and when can help to determine:
- The best performing knowledge base content
- Content that is never being viewed
- Most used Spaces and Categories
- Content tags that are surfacing content views
A typical dashboard view for content analytics will provide drill-down data using a combination of reporting types and date filters.
View counts identify hot and cold content, whilst space view counts indicate where people spend their time looking at content.
Category and tag view counts tell us how people are navigating the knowledge base in the hope of finding relevant content.
Look for and remove under-performing or non-used tags. In doing so, we reduce and simplify the layout and navigation of our knowledge base.
TIP: Content within spaces should be categorised to help people find related content.
TIP: To keep things simple, no more than three tags should be used per content.
Understanding the impact of content contributors can help to:
- Surface the best authors so uou can recognize and reward their efforts
- Highlighting areas of training to help people write better
Content additions and changes should be tracked separately to identiy patterns:
- Is there a group of people who seem to mostly provide new content?
- Is there a group of people who take the time to improve current content?
Depending upon internal procedures, content contributions may need to be reviewed before publication. In such cases understanding who is reviewing what content helps to identify approval rates and identify bottlenecks.
Metrics related to content lifecycle events are key to ensuring a current and relevant knowledge base.
The reputation of a knowledge base can be tarnished by irrelevant or obsolete content. Tracking two metrics can help to keep content relevant and fresh:
- What is being archived?
- What is being versioned?
Archiving of obsolete content should be routine and considered as important as the creation of new content.
Content Versioning is the process of providing different variants of the same content so that end users can choose to view v1, v2 or v3. Typically, versions are linked to product releases or versions.
If you are shipping product variants and have customers adopting different products, versioning metrics will tell you if content is being generated for all audiences.
TIP: Put in place periodic content reviews to help trim outdated knowledge.
TIP: Get into the habit of versioning content so end users have access to the right content.
Search analytics are the levers used to tune the relevance of your knowledge base.
By far the biggest win for any knowledge base administrator is knowing what content people are searching for and how often. Such metrics needs to provide answers to these kinds of questions:
- What keywords are being used when finding content?
- What content is being displayed in search results?
- Which keywords have no search results?
- What content is being accessed and viewed directly from search results?
- What content within search results is not being clicked/opened/viewed?
Keyword search metrics should be viewed like SEO – use the information to help write content that will be found. If keywords don’t appear in your content then how do we expect anyone to find it?
Nobody likes empty search results. so review the keywords that have no search results. Are these “bad” searches that we need to ignore? Or do we need to write new content for the keywords that have no results? Emptiness should be considered bad UX.
TIP: Content that is consistenty ignored in search results should be enhanced, merged or archived.
TIP: Periodically review top searched and viewed content for freshness.
Use the tips to manage your knowledge base for more happier end users and authors!