Form Analyzer

Field-by-field form analysis — which fields cause abandonment, where validation errors hit, how long each field takes, and where users get stuck.

When to Use

• "Which field on the signup form has the highest abandonment?"
• "Why are users dropping off at the password field?"
• "How long does it take users to complete the checkout form?"
• "Which form fields trigger the most validation errors?"
• "Compare form completion on mobile vs desktop"
• "Did the new inline validation reduce form abandonment?"

Mental Model

A form is a sequence of fields users must fill. Each field is a micro-funnel: enter → validate → proceed. The goal is to find which fields cause users to stall, error, or abandon.

Forms have unique failure modes:

• Confusion: Users don't know what to enter (e.g., "Username" vs "Email")
• Validation friction: Strict rules reject valid input ("Password must contain a special character")
• Technical failure: Field doesn't respond, autofill breaks, input type mismatch
• Trust barrier: Asking for too much info too early ("Why do you need my phone number?")

For visual checks, follow session-review: open with fullstory:review-open, pass its client_id to fullstory:review-snapshot at the target timestamp, and always call fullstory:review-close, including on errors. Delegate repeated captures to session-replay.

Use free fullstory:discover_groups and fullstory:get_opportunity_stats for live signals. Discovery accepts one scope at a time (page_id, domain, app_name, segment_id, or funnel_id); use a segment for device/user filters and the live schema for time ranges. Use computed metrics for exact custom windows.

Workflow

Step 1: Identify the form

Clarify which form and what success looks like:

• Form page: /signup, /checkout, /contact
• Success event: page navigation to /signup/confirmation, custom event form_submitted, or purchase completion
• Fields of interest: all fields, or specific ones the user suspects

Step 2: Build form metrics

Start with the overall funnel:

fullstory:build_metric(
  query="users who visited /signup, then completed signup",
  output_type="funnel"
)

Then build field-level metrics. For each field, build a metric for users who interacted with the field but abandoned before completing the form:

fullstory:build_metric(
  query="users who focused or typed in the password field on /signup but did not reach /signup/confirmation",
  output_type="single_number"
)

Step 3: Detect friction per field

For the highest-abandonment fields, investigate:

Rage clicks on the field:

fullstory:discover_groups → filter to the form page → look for rage clicks on form elements

Dead clicks on submit buttons:

fullstory:build_metric(
  query="dead clicks on submit button on /signup",
  output_type="single_number"
)
→ if high, the button is unresponsive or validation is blocking silently

Validation errors: Build metrics for console errors or custom validation-error events on the form page.

Step 4: Time-to-complete analysis

fullstory:build_metric(
  query="time spent on /signup page",
  output_type="single_number"
)

Break down by completion vs abandonment:

• Users who completed: 2m 30s average
• Users who abandoned: 4m 15s average (spent longer before giving up)

Long time + abandonment = user struggling, not just distracted.

Step 5: Read sessions for the worst fields

For the field with the highest abandonment:

fullstory:get_sessions(page="/signup", metric_id=field_abandonment_metric, limit=5)
→ session-context agent: "Did the user interact with the password field? What happened — did they get a validation error, leave the field blank, or type something and then delete it?"

Step 6: Report

## Form Analysis — /signup (last 30 days, 12,000 visits)
Completion rate: 64%

### Field Abandonment
| Field | Users who abandoned after this field | % of total visitors |
|-------|--------------------------------------|---------------------|
| Email | 340 | 2.8% |
| Password | 1,240 | 10.3% ← WORST |
| Name | 210 | 1.8% |
| Submit button | 420 | 3.5% |

### Password Field Deep Dive
- 1,240 users (10.3%) abandoned at or after the password field
- Average time on the field before abandoning: 22 seconds
- 73% received a validation error ("Password must contain...")
- Rage clicks: 87 users rage-clicked the password field or submit button

### Session Evidence
In 4 of 5 sessions, users received "Password must contain at least one special character" — typed a special character — still got rejected (the character wasn't recognized). Users tried 2-3 times, then left.

### Recommendation
The special character validation is too strict. Common characters like ! and @ are rejected. Relax the regex or switch to a strength meter without hard requirements.

Common Form Patterns

Guidelines

• Form analysis is hypothesis-driven. Don't just dump field stats — explain why a field is problematic, backed by session evidence.
• A field with high abandonment might be the symptom, not the cause. Users might abandon at the password field because the email field confused them and they were already frustrated.
• Time-on-field is a proxy for struggle. Short time + abandonment = likely a trust/privacy issue. Long time + abandonment = likely a usability issue.
• Mobile forms have unique issues: keyboard covering the field, autofill not working, touch targets too small. Always check device breakdown.
• If form conversion changed after a deploy, cross-reference with deploy-radar and experiment-analyzer.