A well-built Zendesk Help Center can cut ticket volume, speed up resolutions, and improve customer satisfaction. But creating content is just the start — you must measure how it performs. This guide walks through the top metrics to track, why they matter, and how to act on them to make your Help Center genuinely useful.
Why metrics matter for your Help Center
Metrics turn assumptions into facts. They show what customers actually look for, what they read, and when they still need an agent. The right metrics help you:
- Prioritize content updates.
- Reduce repetitive tickets.
- Improve search relevance.
- Make data-driven content decisions.
1. Article Views & Engagement
What it is: Number of views for each article plus engagement indicators (time on page, clicks, scroll depth).
Why it matters: High views show useful topics. Low engagement suggests the article isn't meeting user needs.
How to act:
- Promote top-view articles on the Help Center homepage.
- Improve SEO and titles for low-traffic but important articles.
- Add images, steps, and examples to increase time on page.
2. Search Queries & Zero-Result Searches
What it is: The terms users type in your Help Center search and the queries that return no results.
Why it matters: Zero-result searches reveal missing content or poor keyword coverage.
How to act:
- Review top search terms weekly.
- Add or rewrite articles for frequent zero-result queries.
- Include synonyms and plain-language terms (e.g., “reset password” vs “credential recovery”).
3. Article Rating (Help Center CSAT)
What it is: Helpful/not helpful votes and optional comments on articles.
Why it matters: Direct user feedback on whether an article solved the problem.
How to act:
- Prioritize articles with many “Not Helpful” votes.
- Read comments for qualitative clues and fix clarity or accuracy issues.
- Track rating trends after updates.
4. Ticket Deflection Rate
What it is: How many potential tickets are avoided because users found answers in the Help Center.
Why it matters: Shows the Help Center’s direct impact on reducing agent workload and support cost.
How to act:
- Use Answer Bot suggestions and contextually link articles in ticket flows.
- Monitor which articles are most correlated with deflection.
- Improve or expand content in topics with low deflection.
Simple formula:
Ticket Deflection Rate = (Self-Service Views ÷ Total Ticket Submissions) × 100
5. Bounce Rate & Exit Rate
What it is: Bounce rate = users who leave after viewing one page. Exit rate = where users typically drop off.
Why it matters: High bounce or exit rates can indicate irrelevant content or poor navigation.
How to act:
- Add “Related articles” and clear “Next steps.”
- Improve article structure: short steps, headings, and visuals.
- Ensure mobile layout is optimized.
6. Time on Page
What it is: Average time spent on an article.
Why it matters: Signals whether users are reading (or abandoning) content.
How to act:
- Pair time-on-page with helpfulness scores: long time + low helpfulness = confusing content.
- Shorten or reorganize long articles; add TL;DR sections and step-by-step bullets.
7. Search-to-Ticket Ratio
What it is: Ratio of users who searched the Help Center vs. those who created a ticket afterward.
Why it matters: Higher ratio suggests better self-service success.
How to act:
- Identify search terms that often lead to tickets and enrich those articles.
- Improve article intros to clearly state what the article covers.
8. Top Performing Articles
What it is: Articles with the highest views, highest helpfulness scores, and most deflections.
Why it matters: Shows what works — useful for replicating structure and tone.
How to act:
- Feature top articles on category pages.
- Use their format (headings, images, step lists) as a template for new content.
9. Device & Region Metrics (GEO Insights)
What it is: Data showing users’ devices (mobile/desktop) and geographic origin.
Why it matters: Helps with localization, responsive design, and scheduling updates.
How to act:
- Localize high-traffic regional articles.
- Prioritize mobile-friendly layouts if most users are on mobile.
- Adjust publishing or update times to match peak activity in major regions.
10. Internal vs External Traffic
What it is: Percentage of visits from agents/admins vs. external customers.
Why it matters: Too much internal traffic might mean agents are over-reliant on internal docs or that customers can’t find public content.
How to act:
- Segment analytics and filter internal traffic.
- Keep internal agent resources separate from customer-facing content.
Bonus: Feedback Comments & Content Updates
Numbers are useful — but free-text comments often point to the exact problem. Review comments for recurring themes and use them to prioritize edits.
How to act:
- Monitor feedback monthly.
- Tag common issues (outdated info, missing screenshots, poor flow).
- Schedule content refreshes for mission-critical articles.
Quick Checklist: Start Tracking Today
- [ ] Set up Google Analytics + Zendesk Guide tracking.
- [ ] Export Help Center search logs weekly.
- [ ] Schedule a monthly content audit for low-rated articles.
- [ ] Track ticket deflection monthly and report trends.
- [ ] Localize top 10 articles by region and device.
DevOps & Product Tips
- Use versioning for complex how-tos so users see recent updates.
- Add small walkthrough GIFs for processes that involve UI steps.
- Store article metadata (last updated, author, version) visible on each page.
- Consider A/B testing article titles and intros to improve search clicks.
FAQs
Q: Which metric should I track first?
Start with Article Views + Article Rating. They’re easy to access and tell you whether content is seen and if it helps.
Q: How often should I review metrics?
Monthly reviews are a minimum. For high-traffic centers, weekly checks make sense.
Q: Can I combine Zendesk data with other analytics?
Yes — integrate Zendesk with Google Analytics, Power BI, or Tableau for deeper insights.
Conclusion
A thriving Zendesk Help Center is measurable. Track the right metrics, act on what you learn, and iterate. Start with views, search logs, and helpfulness scores — then expand into deflection, region, and device metrics. Over time, small improvements compound into a Help Center that genuinely reduces tickets and improves customer experience.
Call to action: Review your top 10 Help Center articles today. Pick one low-rated article and update it — then measure the change over the next 30 days. Share your results or questions below — I’ll help you interpret the data.
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