Real Screens, Real Answers
Every card below is a live screenshot from the v2 Form Intelligence view — no mockups. The product UI ships in English and Italian, and all ten diagnostics are live today.
Where the journey actually breaks
Four honest stages — human visits → visits that reach the form → attempts to submit → converted visits — with the formula printed on the card so the whole team reads the numbers the same way. No mixing page views with form fills: you see exactly which step leaks, and by how much.
- Bot traffic is excluded from the denominator — humans only
- Reach, attempt, convert: three separate leak points, not one blur
- The formula sits on the card itself — zero definition debates in meetings
The exact field where people stop
You already know the form leaks. This card tells you where. Abandonment is attributed field by field, ranked, with each field's share of total drop-off — so the fix becomes a design decision instead of a guessing game.
- Field-level abandonment counts and percentage share of the total
- Worst offender ranked first — your fix list writes itself
- Pairs with field error analysis: stopping and failing are different diseases
Validation errors, field by field
Which fields generate validation errors, with the error message and its origin for each. A field with a high error rate means one of two things: unclear input requirements, or validation rules that are too strict. Both are fixable — once you can see them.
- Errors per field, with message and origin
- Failed submissions with no attributable field are tracked separately, so they never distort per-field rates
How smooth is the submit?
Conversion rate tells you who finished. This measures what finishing felt like: submissions completed on the first attempt with zero errors, versus everything that needed a retry. It's a UX metric, not a marketing metric — and the early-warning light for form friction.
- Immediate successes and first-attempt rate at a glance
- Clean submissions separated from retries and failures
Who fixes the error — and who gives up
When a visitor hits a validation error, two things can happen: they correct it and convert, or they leave. The recovery rate tells you which. A zero recovery rate after errors is a red flag no standard analytics report will ever surface.
- Recovered vs. not-recovered submissions after an error
- Recovery rate = completed-after-error ÷ submissions with at least one error
Desktop, tablet, mobile — honestly split
Visits and conversions broken down by device, on one clean denominator: human visits of the segment. If your form converts on desktop and dies on mobile, this is the card that says so out loud.
- A/B variant visits shown side by side where an experiment is running
- Same formula as every other card — converted visits over human visits
How deep they scroll before they commit
Conversions bucketed by scroll depth — 0, 25, 50, 75, 100%. If most conversions happen at 50% scroll, your form is buried. If people convert without scrolling, the placement is already right. Either way you learn where the page earns the submit.
- Five depth buckets, from zero to fully read
- Exposes buried forms — and confirms well-placed CTAs
Who actually converts
New, returning and unknown visitors with visits and conversions for each. If returning visitors convert at multiples of new ones, your retargeting math changes. If it's the opposite, your nurture math does. One table, real budget decisions.
- Visitor type split with visits and conversions
- Feeds retargeting vs. nurture spend decisions with facts
How much of your traffic isn't human
Suspicious traffic share with a severity rating, form bots producing fake leads, zero-engagement visits and broken tracking sessions — all against the total of tracked sessions. Because every other number on this page is only as honest as the traffic behind it.
- Suspicious-traffic percentage with severity badge
- Fake form leads counted separately — bots never reach your CRM
- Zero-engagement and broken sessions visible, not hidden in averages
Where users click in frustration
Repeated clicks on the same element are a frustration signal: something looks clickable and isn't — or looks broken and is. Digenio surfaces the element, the sessions and the clicks-per-session. It's the shortest path from analytics to a UX fix.
- Element, clicks, sessions and clicks-per-session in one table
- Flags broken or misleading interactive elements automatically