MethodDesign & CreativeWeb & UI designIntermediate

Design an app onboarding flow

An onboarding flow that gets new users to value fast, with screens, copy and metrics.

This is a practical, copy-paste process for many signups never become active users.. Use it when you want a clear structure, then add your own details and the linked evidence.

Published by Deepstory Research. Reviewed Sep 2026.

How to use this method

1. Copy or downloadCopy the prompt below, or download the method file and attach it to your chat.
2. Paste into any AIChatGPT, Claude, Gemini or Copilot. Replace each [PLACEHOLDER] with your details, or let the AI ask you.
3. Add evidenceAttach the evidence files listed on this page so the AI works from sourced numbers, not guesses.

The prompt

Paste it as-is. The AI will ask for anything still in [BRACKETS].

Download .md

# Design an app onboarding flow
Method by Deepstory Research: deepstoryresearch.com/method/app-onboarding-flow

You are a growth designer. Follow the method below step by step. Goal: An onboarding flow that gets new users to value fast, with screens, copy and metrics.

## My inputs
- Product and aha moment: [PRODUCT_AND_AHA_MOMENT]  (example: budgeting app, first budget created)
- User types: [USER_TYPES]  (example: students, families)
- Current drop-off: [CURRENT_DROP_OFF]  (example: 60% before step 3)

Before you start: if any input above is still in [BRACKETS] or missing, ask me for it in one short numbered list and wait. Do not guess. If I attached files (data, briefs, Deepstory evidence files), treat them as the primary source.

## Steps to follow
1. Define activation event.
2. Remove non-essential steps.
3. Design screen sequence with copy.
4. Add personalisation and empty states.
5. Define funnel metrics and tests.

## Deliver the output in this structure
- Activation definition
- Flow
- Screen copy
- Empty states
- Metrics & tests

## Quality rules
- Ask for permissions (notifications, location) only when needed, with reason.
- Label every number as FACT (with source and date), ESTIMATE (show the calculation) or ASSUMPTION.
- If a Deepstory evidence file is attached, use its figures as the reference values and cite its source references; tag claims that are not from it as [UNVERIFIED].
- End with: the 3 assumptions that matter most, what would change the answer, and the single best next step.

What you need to give the AI

Input	Placeholder	Example
Product and aha moment	[PRODUCT_AND_AHA_MOMENT]	budgeting app, first budget created
User types	[USER_TYPES]	students, families
Current drop-off	[CURRENT_DROP_OFF]	60% before step 3

Use it when

Many signups never become active users.

What you get

Activation definition
Flow
Screen copy
Empty states
Metrics & tests

The procedure, step by step

Read this before you run it, so you can check the AI actually followed the method.

1
Define activation event.
2
Remove non-essential steps.
3
Design screen sequence with copy.
4
Add personalisation and empty states.
5
Define funnel metrics and tests.

Quality checks built into the prompt

• Ask for permissions (notifications, location) only when needed, with reason.
• Every number labelled FACT, ESTIMATE or ASSUMPTION; claims outside attached evidence tagged [UNVERIFIED].

Evidence for this method

This method runs on your own material: your files, brief or code. If your task needs market or economic numbers, attach a sourced context file from the evidence library alongside the prompt.

Browse evidence

Run next

Methods that chain well after this one.

Design & CreativeDesign a web page (wireframe to UI)A section-by-section web design: wireframe, visual system, components and responsive behaviour.Design & CreativeRun a UX auditA heuristic UX review with severity-ranked issues and redesign recommendations.

Deepstory methods are process guidance for AI tools. Review AI output before relying on it; legal, tax, medical and investment decisions need a qualified professional.