Fini Product Features

Feb 17, 2025

Analytics Feature Overview

Analytics Feature Overview

🚀 We're thrilled to unveil our latest enhancement designed to elevate your customer support experience: comprehensive analytics for your knowledge base

🚀 We're thrilled to unveil our latest enhancement designed to elevate your customer support experience: comprehensive analytics for your knowledge base

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Zuzanna Ostrowska

IN this article

Introducing our latest enhancement: comprehensive analytics for your knowledge base. This feature provides deep insights into usage, effectiveness, and areas for improvement, ensuring a more efficient and effective customer support experience.

🚀 Introducing Analytics  🚀

We're thrilled to unveil our latest enhancement designed to elevate your customer support experience: comprehensive analytics for your knowledge base. This powerful feature provides deep insights into how your knowledge base is utilized, its effectiveness, and areas for improvement. By leveraging these analytics, you can ensure that your support system is not only efficient but also highly effective in meeting customer needs. 

Here's a closer look at what this new feature offers:

  1. Usage Tracking:

    • Purpose: Monitor how often customers interact with the knowledge base, which articles are most viewed, and the search terms they use.

    • Benefit: Helps customers understand which topics are most relevant and identify trends in user behavior. This can guide content creation and improve overall customer experience by ensuring that the most sought-after information is easily accessible.

  2. Resolution Rate:

    • Purpose: Measure the percentage of issues or queries that are resolved using the knowledge base without needing further assistance.

    • Benefit: Indicates the effectiveness of the knowledge base in providing solutions. High resolution rates suggest that the content is helpful and well-structured, reducing the need for additional support and improving customer satisfaction.

  3. Agent Transfer Rate:

    • Purpose: Track how often interactions in the knowledge base result in a transfer to a live agent.

    • Benefit: Identifies gaps in the knowledge base content where users are unable to find answers and require further assistance. By analyzing this data, customers can enhance the knowledge base to reduce the dependency on live support, streamlining the support process and lowering operational costs.

  4. Percentage of Content Coverage in Knowledge Base by Category:

    • Purpose: Assess the completeness and comprehensiveness of the knowledge base across different categories.

    • Benefit: Ensures balanced content distribution and highlights areas needing more information. This metric helps in maintaining a well-rounded knowledge base that covers all relevant topics, improving its usefulness for users.

How These Analytics Help Customers

  • Informed Decision-Making: Customers can make data-driven decisions to improve their knowledge base, ensuring it meets user needs effectively.

  • Enhanced User Experience: By understanding which areas are most and least effective, customers can tailor their content to be more user-friendly and accessible, resulting in a better user experience.

  • Increased Efficiency: Reducing agent transfer rates and improving resolution rates streamline the support process, making it more efficient and reducing the workload on support staff.

  • Targeted Content Improvement: Identifying gaps in content coverage allows customers to focus their efforts on underrepresented areas, ensuring comprehensive support resources.

  • Cost Reduction: Effective use of the knowledge base can reduce the need for live support, cutting down on operational costs associated with handling customer queries.

By leveraging these analytics features, customers can continuously improve their knowledge base, ensuring it is a robust, efficient, and user-friendly resource. This not only enhances customer satisfaction but also optimizes the overall support process, providing a significant competitive advantage.

FAQs

FAQs

FAQs

Understanding Knowledge Base Usage

1. What does the knowledge base usage tracking feature do?
It tracks how often users interact with each article, including views, searches, and click behavior. This helps teams identify popular topics, spot content gaps, and improve discoverability.

2. Why should I monitor article-level engagement?
Monitoring engagement shows which articles are helpful and which are ignored. This data helps prioritize updates to keep your knowledge base relevant and useful.

3. How do I interpret trending search terms in my knowledge base?
Trending terms show what users are actively looking for. If terms match helpful content, your KB is working. If not, it’s a sign new content is needed.

4. What insights can I gain from low-viewed articles?
Low-viewed articles may be hard to find, poorly titled, or not needed. Use this signal to improve discoverability or prune outdated content.

5. How do I know if my content is aligned with customer needs?
Look at the most searched terms, most viewed articles, and common phrases in unsuccessful queries. They reveal what users expect and where content falls short.

Improving Self-Service Effectiveness

6. Why is it important to monitor the resolution rate?
The resolution rate indicates how many issues are solved through self-service. A high rate means fewer escalations, which improves efficiency and customer experience.

7. How can I increase resolution rates in my knowledge base?
Optimize article content based on failed search queries and agent transfer data. Use clearer explanations, add FAQs, and link related articles.

8. What is considered a good resolution rate for a knowledge base?
Benchmarks vary, but rates above 70% generally indicate effective self-service. Regular monitoring helps you push this number higher.

9. Can resolution rates vary by product or category?
Yes, some product lines may require more complex support. Use analytics by category to compare and optimize accordingly.

10. How do improvements in resolution rate affect CSAT?
Faster resolutions via self-service reduce customer effort, often leading to higher satisfaction scores and repeat usage.

Reducing Agent Transfers

11. What does agent transfer rate measure?
It tracks how often users leave the knowledge base and escalate to live chat or ticket submission. A high rate suggests content gaps or navigation issues.

12. How can I reduce my agent transfer rate?
Improve the clarity of articles, ensure top questions are covered, and add multimedia elements like images or videos to aid understanding.

13. What are common causes of high transfer rates?
Unclear article structure, missing steps, poor keyword matching, or outdated information often cause escalations.

14. When is agent transfer actually a good thing?
If an issue is too complex or sensitive, escalating to a human agent is appropriate. Use analytics to distinguish necessary transfers from avoidable ones.

15. How do I track agent transfers from specific KB articles?
Fini's analytics can show which articles lead to handoffs. Prioritize improving those articles to reduce dependency on live agents.

Analyzing Content Coverage

16. What is “percentage of content coverage by category”?
It measures how thoroughly your knowledge base addresses each category of support queries. A balanced coverage ensures better customer support across the board.

17. Why does content coverage matter in a knowledge base?
If major product lines or customer pain points are underrepresented, customers won’t find the help they need—leading to frustration or support tickets.

18. How can I assess underperforming content categories?
Cross-reference low-traffic or high-transfer categories with search queries. If people search for content you don’t have, coverage is likely weak.

19. Should content coverage be uniform across all topics?
Not necessarily. Focus on categories with high query volume or high-value customers. But avoid leaving critical areas under-documented.

20. How often should I review category-level coverage?
A monthly or quarterly review ensures your knowledge base evolves with product changes and customer needs.

Strategic Decision Making with Analytics

21. How do analytics help identify content gaps?
Failed searches, agent transfers, and low-resolution articles signal missing or unclear information that needs to be addressed.

22. What are “zero-result queries” and why do they matter?
These are searches that return no articles. They often indicate valuable content that should be added to the KB.

23. How can I decide which articles to update first?
Focus on articles with high views and low resolution, or high transfer rates. These have the most impact when improved.

24. Can KB analytics inform product development?
Yes, patterns in support queries often reveal product friction points. This data can be shared with product teams to influence roadmap decisions.

25. How can analytics improve onboarding guides?
By tracking where new users struggle—based on what they search or where they escalate—you can improve onboarding documentation proactively.

Enhancing User Experience

26. How does better content organization affect support outcomes?
Clear categories and intuitive navigation make it easier for users to find answers, leading to higher resolution rates and fewer escalations.

27. What’s the value of tracking bounce rates on KB articles?
A high bounce rate may mean users aren’t finding content helpful or engaging. Consider adding visuals or simplifying the language.

28. How can personalization improve KB engagement?
AI-driven KBs like Fini can tailor article suggestions based on user profiles, increasing relevance and reducing search friction.

29. What role does feedback collection play in analytics?
User ratings and comments provide direct qualitative data to validate your quantitative insights. Use both to improve article quality.

30. How can I use analytics to test KB improvements?
After making content changes, track resolution, engagement, and transfer rates to measure impact and iterate further.

Operational & Cost Impact

31. How do KB improvements reduce operational costs?
Fewer tickets and shorter agent conversations reduce the need for additional headcount, saving time and money.

32. Can analytics help plan support staffing?
Yes, by identifying patterns of when and where issues arise, you can align support staffing more closely with demand.

33. How do knowledge base insights affect agent training?
Analytics can highlight topics that frequently confuse users. Train agents on these weak points to ensure consistent support across all channels.

34. How does content freshness influence performance?
Outdated articles often result in user drop-offs or escalations. Analytics help track usage and signal when updates are needed.

35. What’s the ROI of using KB analytics?
Better resolution rates, lower support costs, and higher CSAT scores compound over time, delivering a measurable return on investment.

Best Practices for Implementation

36. How often should I audit my knowledge base using analytics?
A monthly audit is ideal for fast-moving businesses. For slower industries, quarterly reviews can suffice—just ensure it’s consistent.

37. What metrics should I monitor first?
Start with resolution rate, agent transfer rate, and search query success. These are strong indicators of content effectiveness.

38. Should analytics be used only by support teams?
No. Product, marketing, and operations teams can also benefit from insights—especially when trying to understand customer pain points.

39. How does Fini help automate KB analytics?
Fini automatically tracks key engagement and performance metrics, flags content gaps, and recommends improvements—making it easy to act on data.

40. What’s the fastest way to improve my knowledge base using analytics?
Focus on the top 10 most-viewed articles with high agent transfer or low resolution. Quick wins here can dramatically improve performance.

Zuzanna Ostrowska

Zuzanna Ostrowska

AI Customer Success Manager
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Zuza joined Fini in May 2024 as a Customer Success Manager. Originally from Poland, Zuza comes with over 7 years of experience gained at 4 four different companies that specialize in disruptive technologies. At Fini, Zuza ensures that customers are onboarded smoothly and that their needs are consistently met.

Zuza joined Fini in May 2024 as a Customer Success Manager. Originally from Poland, Zuza comes with over 7 years of experience gained at 4 four different companies that specialize in disruptive technologies. At Fini, Zuza ensures that customers are onboarded smoothly and that their needs are consistently met.

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