Voting and analytics
Visitors rate articles helpful / not helpful. View counts tell you what gets read.
Two cheap signals tell you which articles are doing their job and which are wasting visitors' time.
Voting
Every public article has a "Was this article helpful? 👍 / 👎" widget at the bottom. One vote per visitor per article (we key on IP for the cap — imperfect but good enough). Voting is anonymous; we don't ask for an email.
The counts surface in the admin article list:
- Helpful count — clicked 👍
- Not helpful count — clicked 👎
There's no comment field today. If you want qualitative feedback, link to your contact form or open a ticket. We may add an optional comment field in a future release.
View count
Every page load on a public article increments view_count. It's a naive counter — no bot filtering yet — but it's directionally useful:
- High views + high helpful ratio — keep, maybe feature it.
- High views + low helpful ratio — rewrite urgently. People are finding it but it's not solving their problem.
- Low views + high helpful ratio — the topic is niche but the article is good. Consider SEO-improving the title.
- Low views + low ratio — archive or rewrite, doesn't matter which.
Where to see the data
The admin article list (<tenant>.nura24.com/admin/kb/articles) shows views, helpful, not-helpful columns. Sort by any of them.
We don't have a charts dashboard yet — the per-article counters are the whole story. A dedicated analytics page is on the roadmap.
Using the data for AI gap analysis
The KB gap analysis feature looks at customer questions you DIDN'T have an article for. Voting / view counts are about articles that DO exist. Both signals matter:
- Vote / view counts tell you what to improve.
- Gap analysis tells you what to write next.
Resetting counters
You can't reset counters from the UI (deliberate — preserving history is the point). If you republish an old article with a major rewrite, the counts carry over; consider it an honest signal that the article has been around a while.