Analytics
Where users actually get stuck.
38%
of support volume was navigation-shaped
Router distribution
Show38%
Answer34%
Do19%
Hand off9%
Intents are logged in your users' own words: the product-journey corpus a chat log structurally can't give you.
How the analytics are built
Not a survey: a by-product of Peeve doing the work.
01
Capture the real intent
Every question is logged in the user's own words and tagged to the exact route they were on, not a canned category someone chose after the fact.
02
Score the route it used
The router's choice (Answer, Show, Do or Hand off) and its confidence are recorded per session, so you see how each intent actually resolved.
03
Rank the stuck-points
The dashboard surfaces the routes where users stall, repeat themselves, or hand off: the friction to fix, in priority order.
01What can analytics tell me that tickets can't?
Which route a user stalled on, in their own words, before they gave up or asked a human. A ticket is a summary written after the fact by someone else; Peeve's analytics are the raw intents and the exact stuck-points, per route, so you can fix the interface instead of restaffing the queue.
02Where does the 38% come from?
It's the share of support volume that is navigation-shaped (how-do-I questions about finding or completing an action) measured across live Peeve workspaces. Your own number appears in the dashboard within the first weeks, and it's usually the figure that justifies the whole install.
Why teams choose Peeve
The cause, not the drop
See what a user was trying to do on the route they stalled on, in their own words, not just that a funnel leaked.
A number that justifies the install
Your navigation-shaped share of support appears in the dashboard within the first weeks.
Fix the interface, not the queue
Stuck-points per route tell you what to change, so volume drops at the source instead of being re-staffed.
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