Find the page that's losing you users
Web vitals for every page, the JavaScript errors behind them, and the funnel step where people drop out. When a number looks wrong, open a session and watch what happened.
A p75 tells you the page got slower. It doesn't tell you who, or what they were doing.
KloudMate RUM measures web vitals and errors for each page and each release, and maps the route people take through your app. Open any single session and every page view, request, error, console line, and rage click sits on one timeline next to the replay.
What teams can do with Real User Monitoring
Measure what real users get, find the page or release that broke it, and see the individual visits behind both.
Core Web Vitals by page and release
LCP, INP, and CLS p75 for every page, split by device, plus TTFB and FCP for the application. Compare one release against the last to see which build moved them.
Errors grouped by cause
Recurring JavaScript errors collapse into one group, tagged with the pages they hit and the version they started in.
Funnels and pathways
Build a funnel over the steps that matter and see which one loses people. Pathways map where users go next from any page.
Rage, dead, and error clicks, on by default
The browser SDK flags repeated clicks in the same spot, clicks that got no response, and clicks followed by a JavaScript error. Counts sit on the session row.
One timeline per session
Every event in the session lands on one timeline beside the replay, in the order it happened. Click one and the replay jumps to that moment.
Tied to your backend traces
The SDK propagates W3C trace context on fetch and XHR, so a request that failed in someone's browser opens as the backend trace that produced it.
From a number that moved to the session behind it
Start with the numbers across every page and release. Narrow to the one that changed. Go to a single visit only when you have to.
Add the browser SDK
Drop in the RUM script. Page timing, Web Vitals, fetch and XHR spans, JavaScript errors, and the three frustration clicks start reporting on the first page load. Turn on session replay when you want the recording too.
Find what changed
Compare vitals and error rate across pages, devices, and releases until one of them stands out.
Run the funnel
Pick a flow like signup or checkout. Open the step with the biggest drop to see why people left it.
Watch the session
Watch the replay with the whole timeline beside it. The backend trace is one click from any failed request.
Find the slow page, and the build that caused it
Each page gets its own p75 for LCP, INP, and CLS, split by device. Compare a release against the one before it and you can tell a slow page from a slow build.
- Group URLs like /product/1234 into one page, or split a group back open
- Open a page for its own vitals, errors, and the sessions that visited it
- See how many sessions are behind each number
See the step where people give up
Open the step with the biggest drop and you get three answers about the people who stalled there: the errors and vitals they hit, the pages they went to instead, and the list of sessions to watch.
- Funnels of up to five steps, with a completion window you set
- Save a funnel and compare this period against the last one
- Pathways show where people go next from any page, several steps out
Group the errors before you triage them
Recurring errors collapse into one group with an occurrence trend, so ten thousand hits of the same TypeError read as the one problem they are.
- Error rate by version, so a bad release shows up without diffing anything
- Filter to the errors that only happen on one page, browser, or device
- Jump from an error group to the pages and sessions that hit it
Open one session and see the whole visit
Every page view, network request, error, console line, and frustration click from the visit sits in one order, beside the replay. Click any event and the replay jumps to that moment.
- A network waterfall of every request, with method, status, timing, and where it sat in the visit
- Console errors and warnings from the user's own browser, plus TTFB, FCP, LCP, INP, and CLS for that one visit
- Large recordings stream the part you are watching, so a seek into a long session lands in about a second
Use KloudMate Assistant to explain what changed for your users
Ask Assistant where the drop is coming from. It answers with the errors and requests underneath, and the view worth opening next.
- Describe Name the page or release losing the most users
- Correlate Tie a slow page to the errors and requests behind it
- Prioritize Say how many real sessions hit it, before anyone digs in
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