# User Flow Friction Finder

Walks through a described user flow step by step to identify friction points, unnecessary steps, and confusing moments that could cause drop-off.

## Prompt

You are a UX researcher who specializes in identifying friction in multi-step user flows before they cause real drop-off.

Flow being reviewed (describe each step in order, e.g., landing -> signup -> onboarding -> first action): {{flow_steps_description}}
What the user is trying to accomplish: {{user_goal}}
Any known drop-off points (if you have data): {{known_drop_off_points}}

Do the following:
1. Walk through the flow step by step, and for each step, note what the user is thinking/feeling and what could cause hesitation, confusion, or abandonment at that exact point.
2. Identify unnecessary steps: anything that could be removed, combined with another step, or deferred to later without hurting the core goal.
3. Flag the single step most likely to be the primary drop-off point, with reasoning, especially if it matches or is near any known drop-off data provided.
4. Propose a revised, leaner version of the flow, listing the new step sequence and explaining what changed and why.

## Best for

Product managers, founders, and UX designers reviewing signup flows, onboarding sequences, checkout processes, or any multi-step user journey that needs to minimize drop-off.

## Compatible tools

- Claude
- ChatGPT

## How to use

- List out each step of your current user flow in order, as specifically as you can.
- State clearly what the user is ultimately trying to accomplish through this flow.
- Share any known drop-off data if you have it, since it helps validate or challenge the friction analysis.
- Use the revised leaner flow as a starting redesign, then test it against your actual metrics after implementing.

## Customization tips

- If you have screenshots of each step, describe the visual layout too, since friction can come from visual clutter, not just the flow logic itself.
- For flows involving payment or sensitive data, ask for extra attention to trust-building moments at those specific steps.
- Request a version comparing mobile versus desktop friction separately if your flow behaves differently across devices.

## Example input

Flow: Landing page -> Sign up with email -> Verify email -> Fill out a 6-field profile -> Connect a payment method -> See the dashboard. User goal: Start using an AI writing tool. Known drop-off: Analytics show a big drop after the profile step.

## Example output

A step-by-step walkthrough noting the 6-field profile step likely feels like a wall of forms before the user has experienced any value yet, an identification that email verification and profile completion could be deferred until after the user sees the dashboard, a flagged primary drop-off point at the profile step matching the provided data, and a revised leaner flow moving profile completion to an optional post-signup step, letting users reach the dashboard faster.