This article explains what Help Center Audits are, why they are crucial for maintaining an effective knowledge base, and how to interpret the key metrics.
Help Center Audits, powered by Fern, analyze your latest support conversations to identify missing content and suggest improvements for your help center. They help you proactively address user needs, reduce support volume, and ensure your documentation is always relevant and effective.
Why You Need Help Center Audits
Help Center Audits are essential for:
Identifying Knowledge Gaps: Discover which topics frequently lead to support tickets because they aren't adequately covered in your help center.
Reducing Support Volume: By creating targeted help articles for common questions, you can empower users to self-serve and reduce the number of incoming support requests.
Measuring Content Effectiveness: Understand whether your recent knowledge base updates are successfully reducing support ticket volume related to those topics.
Understanding User Behavior: Gain insights into seasonal patterns in customer questions and the impact of product changes on support volume.
Key Metrics Explained
When you review a Help Center Audit, you'll see several key metrics that provide a comprehensive overview of your help center's performance and areas for improvement:
Conversations Analyzed: This metric shows the total number of support conversations analyzed by Fern during the audit period. It indicates the volume of data processed to generate insights.
Recommendations: This metric represents the number of actionable suggestions provided by Fern to improve your help center content. These are opportunities to create new articles or update existing ones.
Coverage: Displayed as a percentage, Coverage indicates how many of your customer's questions are already addressed by existing articles in your help center. A higher percentage means your help center is more comprehensive.
Estimated Impact: For each recommendation, Fern provides an estimated impact, such as "Get up to {N} fewer tickets every week by implementing these." This metric helps you prioritize recommendations by showing the potential reduction in support tickets if you implement the suggested changes.
Types of Recommendations
Fern groups recommendations by impact level to help you prioritize your work:
High Impact: Recommendations that could significantly reduce your support volume if implemented.
Medium Impact: Recommendations that offer moderate reduction in support tickets.
Low Impact: Other suggestions to review, typically addressing less frequent questions.
Pro Tip: Regularly review your audit results and prioritize recommendations with high estimated impact to achieve the most significant reduction in support volume.
What's Next
Now that you understand what Help Center Audits are and their key metrics, learn how to create a Help Center Audit.