I often get asked by support leaders: “How do I know if our knowledge base is actually helping customers — and how quickly can I spot the biggest wins?” If you’ve got 20 minutes and a cup of coffee, you can run a pragmatic, evidence-based audit that surfaces the highest-impact fixes for deflection. Below I walk you through a repeatable 20-minute process I use with teams to evaluate knowledge base (KB) quality and prioritise improvements that move the needle on CSAT and contact volumes.
What I’m trying to prove in 20 minutes
In a short audit I focus on two things: usefulness and discoverability. Usefulness answers whether articles actually solve customers’ problems; discoverability checks if customers can find those articles when they need them. If an article is useful but invisible, or visible but useless, it won’t deflect contacts.
What you need before you start (quick setup)
Collect these three items — you’ll likely already have them:
If you use Zendesk Guide, Freshdesk, Intercom Help Center, or Help Scout, you’ll be able to export these metrics easily. If your KB is on a CMS (Confluence, WordPress), grab site search logs or GA event data.
The 20-minute audit: step-by-step
Set a 20-minute timer and follow these focused checks.
Minute 0–5: Traffic & search signal quick scan
Open your top-20 articles by pageviews. For each article, note three signals:
Why this matters: If high-traffic articles have very short time-on-page or users immediately return to search, that’s a strong sign content isn’t solving intent. Likewise, frequent “no results” searches highlight gaps in coverage or poor keyword mapping.
Minute 5–10: Relevance sampling from recent tickets
Scan the top 50 recent tickets or chat logs. For each, ask: was there an existing KB article that could have solved this? Tag each ticket as:
Count the proportions. If >40% are “direct match” but customers still raise tickets, you’ve got a discoverability problem. If many are “partial” or “missing,” you have content-quality or coverage problems.
Minute 10–15: Article quality checklist (sample 10 articles)
Pick 10 articles: the top five by traffic and five randomly from the top 50. For each, run this checklist (takes ~30–60s per article):
Mark each check as pass/fail. Articles with multiple fails are high-priority for fixes.
Minute 15–18: Discoverability quick wins
Use this short checklist to identify immediate SEO/search improvements:
These changes often increase click-through and deflection within days, especially when combined with chatbot integrations like Ada, Intercom, or Zendesk Answer Bot.
Minute 18–20: Prioritise fixes that boost deflection
Now translate what you found into a short prioritised list. I use a quick impact/effort matrix — but simplified to three buckets:
Example prioritisation table:
| Article/Topic | Signal | Action |
|---|---|---|
| Reset password | High traffic, short time-on-page | Rewrite title, add 3-step numbered guide + screenshot (Fix now) |
| Billing disputes | Many tickets, no KB | Create article + FAQ + chatbot flow (Plan) |
| Developer API edge case | Low traffic, deep technical | Backlog |
Tips I use to increase confidence in recommendations
These little checks prevent false positives:
Tools and integrations that speed this up
If you want to scale beyond a 20-minute audit, these tools help:
Integrating your KB with chatbot automation (Intercom, Ada, Zendesk Answer Bot) lets you measure deflected conversations and tune article matching iteratively.
Do this quick audit once a month and you’ll surface a manageable backlog of high-impact fixes. The magic isn’t in writing more content — it’s in reshaping the right content so customers find and trust it. If you’d like, I can format a one-page checklist you can paste into your team’s triage board to run this in under 20 minutes every week.
