Reporting and analytics

We encourage you, early on, to think about what kind of reporting and analytics you might need in your knowledge base. KnowledgeOwl provides some high-level reporting, but if you want detailed analytics, taking the time to set an analytics tool up before you officially launch your knowledge base is time well-spent.

There are two main reasons you might want to use reporting, feedback, and analytics tools:

  1. To provide feedback/tracking that influences your content decisions (content management)
  2. To measure the success of your knowledge base (measuring success)

We discuss each in a bit more detail below.

Reporting for content management

For feedback directly from end-users, consider these KnowledgeOwl features:

The high-level Reporting available in KnowledgeOwl might meet a lot of your explicit reporting needs, too.

Our built-in reporting includes:

Our built-in reporting won't provide more detailed analytics-type reporting, though. So if you want things like:

  • Views split out by geography, reader group, or reader
  • Click-through
  • Event-based analytics
  • Browser info

Consider adding a third-party analytics tool (see final section below).

For content management reporting, you might also want to check with your support team or help ticketing system to see if there are ways to get reports on what features, policies, services, or whatever your customers are asking about. These can be a great source of new content ideas, but you'd rarely see them surfaced within the knowledge base!

Reporting for measuring success

If you worked through Purpose & audience, you should have a sense of the ultimate goal for your knowledge base: how will you know if your knowledge base is successful?

Reporting or analytics tools might be a piece of how you measure success. This can include things like:

  • Monthly number of distinct users or views
  • Reduction of support tickets submitted on xx after launch of knowledge base
  • Demonstrated ticket deflection using the Contact form reporting
  • Reduction in average amount of time a support person spends answering a ticket
  • And so on

These reporting requirements can be a bit trickier. Why? Two reasons: first, defining success can be hard. Second: just because you can generate a number on something doesn't mean that number is a good measure for what you're trying to measure.

For some of these sample metrics, adding a third-party analytics or tracking tool to your knowledge base might be the best way to go. For others, you may need to coordinate with people handling support, customer experience, quality assurance, or more to be able to capture some baseline numbers from before your knowledge base is launched and then to capture updated numbers to compare against at set intervals (monthly, quarterly, etc.).

Third-party tools

If it seems like third-party tools are the best place to get information, we have instructions on setting up Google Analytics. But you're definitely not limited to only Google Analytics!

Most analytics tools are added by accessing the Custom Head. KnowledgeOwl allows you to add scripts and code to your Custom Head, so you should be able to set up most third-party tools.

We have also tried tools like:

  • Plausible - a more privacy-friendly alternative to Google Analytics, though it does cost money. No cookies and fully compliant with GDPR, CCPA and PECR. Made and hosted in the EU.
  • FullStory - good for tracking individual viewing history/actions; can record end-user sessions
  • Hotjar - good for heatmaps and behavior analytics (useful if you are considering a redesign/layout changes)