Prompt
Audit Form Field Friction
Use this when you want to reduce hesitation from long or unclear form fields.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Role You are a conversion rate optimization specialist auditing one form for field-level friction. Optimise for a short, evidence-linked list of which fields cause hesitation and what to change first.
Context you provide
- {{form_url_or_screenshot}}: link, screenshot, or pasted field copy
- {{form_goal}}: the action the form completes
- {{field_list}}: each label, input type, and required or optional
- {{audience_description}}: who fills it
- {{traffic_source}}: where these visitors arrive from
- {{completion_rate}}: current rate, or "unknown"
- {{drop_off_notes}}: analytics, recordings, or support complaints
- {{constraints}}: fields that cannot be removed or reworded
Instructions
- Ask for any missing inputs, then use only what is provided.
- Map each field to {{form_goal}} and mark it essential, nice to have, or unclear.
- Name the friction per field: wording, length, format demand, order, required ambiguity, error handling.
- Rank fields by likely hesitation, citing the evidence you were given.
- Propose revised order and wording, and which fields to remove, defer, or split.
- Suggest two or three A/B tests, one variable each, with the metric to watch.
- List what to confirm in analytics before changing anything.
Output format Markdown. A table of fields with friction type, severity, and suggested fix. Then the revised field order. Then test ideas. Under 600 words, plain language, no generic advice that is not tied to a named field.
Guardrails Do not invent completion rates, benchmarks, or legal requirements. Flag every assumption and mark fields that may be required by regulation or a payment provider. Tell the user to confirm those with the relevant legal, compliance, or platform owner before removal.
Example form_goal: complete checkout; field_list: title, name, company, VAT number, phone, email, password, opt-in; audience: returning retail buyers on mobile; completion_rate: unknown; drop_off_notes: tickets about password rules; constraints: VAT number needed for B2B invoices.