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onboarding

skill · 267 lines · MIT · skills/onboarding/SKILL.md

The facts

Its description

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup. For ongoing email sequences, see emails.

The description the agent reads to decide when to use it.

From its settingsline 3

When it starts

This skill fires when a person asks for help with what happens after signup — onboarding flows, activation rate, first-run or first-session experience, empty states, the aha moment, or time-to-value — including the complaint that users sign up but never come back or never finish setup.

Things a person might say (the model's guesses)

  • “Our users sign up but never actually use the product — how do we fix that?”
  • “Can you audit our onboarding flow? Nobody completes setup.”
  • “How do we improve activation rate and get people to value faster?”

A model's summary of when it is used.

A model's reading

Files it mentions

references/minimum-path-to-value.md, references/activation-models.md, references/experiments.md (first 5 of 6 lines)

Files the text names, such as ones to read or write. Found by matching words, so treat them as pointers.

Found by matching wordsline 28 line 74 line 240 line 246 line 247

What it leads to

Other skills this one hands off to, calls, requires or offers instead, as a model read them.

A model's reading

What leads to it

Other skills that hand off to this one, call it, require it or offer it instead, as a model read them.

A model's reading

Licence

MIT, from LICENSE

The terms its author shares it under, which let it be shown here.

From the repositorylicence text

Other settings

metadata: version: 2.0.2

More settings at the top of the file, shown as written.

From its settingsline 4
Other files in this skill (4) Close

The text

Open on GitHub

Most marks come from matching words in the file, so treat them as pointers.

1---
2name: onboarding
3description: When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup. For ongoing email sequences, see emails.
4metadata:
5 version: 2.0.2
6---
7
8# Onboarding CRO
9
10You are an expert in user onboarding and activation. Your goal is to help users reach their "aha moment" as quickly as possible and establish habits that lead to long-term retention.

Onboarding CRO

You are an expert in user onboarding and activation. Your goal is to help users reach their "aha moment" as quickly as possible and establish habits that lead to long-term retention.

Raw lines 1 to 11
Names a skill signup :3
Names a skill emails :3
12## Initial Assessment
14**Check for product marketing context first:**
15If `.agents/product-marketing.md` exists (or `.claude/product-marketing.md`, or the legacy `product-marketing-context.md` filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
17Before providing recommendations, understand:
191. **Product Context** - What type of product? B2B or B2C? Core value proposition?
202. **Activation Definition** - What's the "aha moment"? What action indicates a user "gets it"?
213. **Current State** - What happens after signup? Where do users drop off?
23---

Initial Assessment

Check for product marketing context first: If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Before providing recommendations, understand:

  1. Product Context - What type of product? B2B or B2C? Core value proposition?
  2. Activation Definition - What's the "aha moment"? What action indicates a user "gets it"?
  3. Current State - What happens after signup? Where do users drop off?

Raw lines 12 to 24
Names a skill product-marketing :15
25## Core Principles

Core Principles

Raw lines 25 to 26
27### 1. Time-to-Value Is Everything
28Remove every step between signup and experiencing core value. Design the **Minimum Path to Value (MPTV)** — the least number of steps to experience enough value to make a confident decision (see [references/minimum-path-to-value.md](references/minimum-path-to-value.md)).

1. Time-to-Value Is Everything

Remove every step between signup and experiencing core value. Design the Minimum Path to Value (MPTV) — the least number of steps to experience enough value to make a confident decision (see references/minimum-path-to-value.md).

Raw lines 27 to 29
30### 2. One Goal Per Session
31Focus first session on one successful outcome. Save advanced features for later.

2. One Goal Per Session

Focus first session on one successful outcome. Save advanced features for later.

Raw lines 30 to 32
33### 3. Do, Don't Show
34Interactive > Tutorial. Doing the thing > Learning about the thing.

3. Do, Don't Show

Interactive > Tutorial. Doing the thing > Learning about the thing.

Raw lines 33 to 35
36### 4. Progress Creates Motivation
37Show advancement. Celebrate completions. Make the path visible. (See onboarding psychology below for the mechanisms.)
39---

4. Progress Creates Motivation

Show advancement. Celebrate completions. Make the path visible. (See onboarding psychology below for the mechanisms.)


Raw lines 36 to 40
41## Onboarding Psychology
43The principles that make progress mechanics, checklists, and prompts actually work:
45- **Endowed Progress Effect** — people finish faster when progress is already started for them. A checklist that opens at "20% done" (a step pre-completed on their behalf) drives roughly **+40% completion** vs. starting at 0%. Give users a head start, don't make them start from nothing.
46- **Peak-End Rule** — users remember an experience by its most intense moment (the *peak*) and its *end*, not the average. Engineer a clear high point (a win, a wow, a celebration) and end each session on a positive note.
47- **Goldilocks Rule** — motivation peaks when a task is neither too easy nor too hard, but *just right* on the edge of ability. Tune early steps so they're achievable but not trivial.
48- **BJ Fogg Behavior Model** — a behavior happens only when **Motivation × Ability × Prompt** converge at the same moment. If a step isn't happening, one of the three is missing: raise motivation, make it easier (Ability), or add a better-timed Prompt.
49- **Mario Kart boosters & blockers** (Ramli John) — treat onboarding like a race track. Add **boosters** (accelerants: pre-filled data, templates, quick wins, celebrations) and remove **blockers** (friction: required fields, dead ends, confusing empty states). Speed users toward value and clear obstacles from the lane.

Onboarding Psychology

The principles that make progress mechanics, checklists, and prompts actually work:

  • Endowed Progress Effect — people finish faster when progress is already started for them. A checklist that opens at "20% done" (a step pre-completed on their behalf) drives roughly +40% completion vs. starting at 0%. Give users a head start, don't make them start from nothing.
  • Peak-End Rule — users remember an experience by its most intense moment (the peak) and its end, not the average. Engineer a clear high point (a win, a wow, a celebration) and end each session on a positive note.
  • Goldilocks Rule — motivation peaks when a task is neither too easy nor too hard, but just right on the edge of ability. Tune early steps so they're achievable but not trivial.
  • BJ Fogg Behavior Model — a behavior happens only when Motivation × Ability × Prompt converge at the same moment. If a step isn't happening, one of the three is missing: raise motivation, make it easier (Ability), or add a better-timed Prompt.
  • Mario Kart boosters & blockers (Ramli John) — treat onboarding like a race track. Add boosters (accelerants: pre-filled data, templates, quick wins, celebrations) and remove blockers (friction: required fields, dead ends, confusing empty states). Speed users toward value and clear obstacles from the lane.
Raw lines 41 to 50
51## Onboarding Toolkit (10 Components)
53The components you assemble an onboarding experience from. Use the fewest that reach value:
55| Component | Purpose |
56|-----------|---------|
57| Welcome forms | Capture role/goal to personalize the path (keep short — Hick's Law) |
58| Initial screens | First-run screens that orient and point to one clear action |
59| Drip emails | Multi-touch nurture — **one concept per email**, don't overload |
60| Skippable tutorials | Optional guidance users can bypass — never trap them |
61| Videos | Show complex workflows visually |
62| Docs / help center | Self-serve reference for when users get stuck |
63| Onboarding calls | Human touch for complex or high-value accounts |
64| Data inputs | Getting the user's real data in so value feels "real" |
65| Checklists | Ordered, value-first steps with visible progress (see below) |
66| Empty states | Guided first-action opportunities, not dead ends (see below) |
68---

Onboarding Toolkit (10 Components)

The components you assemble an onboarding experience from. Use the fewest that reach value:

ComponentPurpose
Welcome formsCapture role/goal to personalize the path (keep short — Hick's Law)
Initial screensFirst-run screens that orient and point to one clear action
Drip emailsMulti-touch nurture — one concept per email, don't overload
Skippable tutorialsOptional guidance users can bypass — never trap them
VideosShow complex workflows visually
Docs / help centerSelf-serve reference for when users get stuck
Onboarding callsHuman touch for complex or high-value accounts
Data inputsGetting the user's real data in so value feels "real"
ChecklistsOrdered, value-first steps with visible progress (see below)
Empty statesGuided first-action opportunities, not dead ends (see below)

Raw lines 51 to 69
70## Defining Activation
72**Judge activation by lead→customer conversion + 90-day retention, not lead volume.** More signups mean nothing if they don't convert and stick.
74Choose an **activation model** (freemium, free trial, paid trial, money-back, consultation) before designing the flow — the model shapes the whole onboarding path. See [references/activation-models.md](references/activation-models.md) for the 5 models, the credit-card tradeoff, Model-Market Fit, and the Evernote-vs-Notion parable.

Defining Activation

Judge activation by lead→customer conversion + 90-day retention, not lead volume. More signups mean nothing if they don't convert and stick.

Choose an activation model (freemium, free trial, paid trial, money-back, consultation) before designing the flow — the model shapes the whole onboarding path. See references/activation-models.md for the 5 models, the credit-card tradeoff, Model-Market Fit, and the Evernote-vs-Notion parable.

Raw lines 70 to 75
76### Find Your Aha Moment
78Find early value actions associated with later retention, using a defined cohort and timeline:
801. Define signup as time zero, an early activation window, and a separate retention outcome after the activation window. For example, first-seven-day actions and return activity in week four; choose windows that fit the product cadence.
812. Include all eligible signups with full follow-up through the retention window. Show recent, immature cohorts separately; do not count them as churned or restrict the denominator to users who already activated.
823. Compare actions recorded within the early window. Exclude behavior during the retention outcome window: a week-four return cannot also be the early activation predictor of week-four retention.
834. Treat high-correlation events and frequency thresholds as candidate hypotheses. Report counts, uncertainty, and acquisition/product segments; confirm the definition on a later mature cohort before adopting it.
845. Test whether an onboarding intervention improves later retention or customer conversion. Correlation alone does not prove that forcing the action causes retention.
86[Amplitude's Compass setup](https://amplitude.com/docs/analytics/charts/compass/compass-aha-moment) separates early actions from later retention and requires time for every cohort member to retain; its [interpretation guide](https://amplitude.com/docs/analytics/charts/compass/compass-interpret-1) distinguishes correlation from causation.
88**Examples by product type:**
89- Project management: Create first project + add team member
90- Analytics: Install tracking + see first report
91- Design tool: Create first design + export/share
92- Marketplace: Complete first transaction

Find Your Aha Moment

Find early value actions associated with later retention, using a defined cohort and timeline:

  1. Define signup as time zero, an early activation window, and a separate retention outcome after the activation window. For example, first-seven-day actions and return activity in week four; choose windows that fit the product cadence.
  2. Include all eligible signups with full follow-up through the retention window. Show recent, immature cohorts separately; do not count them as churned or restrict the denominator to users who already activated.
  3. Compare actions recorded within the early window. Exclude behavior during the retention outcome window: a week-four return cannot also be the early activation predictor of week-four retention.
  4. Treat high-correlation events and frequency thresholds as candidate hypotheses. Report counts, uncertainty, and acquisition/product segments; confirm the definition on a later mature cohort before adopting it.
  5. Test whether an onboarding intervention improves later retention or customer conversion. Correlation alone does not prove that forcing the action causes retention.

Amplitude's Compass setup separates early actions from later retention and requires time for every cohort member to retain; its interpretation guide distinguishes correlation from causation.

Examples by product type:

  • Project management: Create first project + add team member
  • Analytics: Install tracking + see first report
  • Design tool: Create first design + export/share
  • Marketplace: Complete first transaction
Raw lines 76 to 93
94### Activation Metrics
95- % of signups who reach activation
96- Time to activation
97- Steps to activation
98- Activation by cohort/source
100---

Activation Metrics

  • % of signups who reach activation
  • Time to activation
  • Steps to activation
  • Activation by cohort/source

Raw lines 94 to 101
102## Onboarding Flow Design

Onboarding Flow Design

Raw lines 102 to 103
104### Immediate Post-Signup (First 30 Seconds)
106| Approach | Best For | Risk |
107|----------|----------|------|
108| Product-first | Simple products, B2C, mobile | Blank slate overwhelm |
109| Guided setup | Products needing personalization | Adds friction before value |
110| Value-first | Products with demo data | May not feel "real" |
112**Whatever you choose:**
113- Clear single next action
114- No dead ends
115- Progress indication if multi-step

Immediate Post-Signup (First 30 Seconds)

ApproachBest ForRisk
Product-firstSimple products, B2C, mobileBlank slate overwhelm
Guided setupProducts needing personalizationAdds friction before value
Value-firstProducts with demo dataMay not feel "real"

Whatever you choose:

  • Clear single next action
  • No dead ends
  • Progress indication if multi-step
Raw lines 104 to 116
117### Onboarding Checklist Pattern
119**When to use:**
120- Multiple setup steps required
121- Product has several features to discover
122- Self-serve B2B products
124**Best practices:**
125- 3-7 items (not overwhelming)
126- Order by value (most impactful first)
127- Start with quick wins
128- Progress bar/completion %
129- Celebration on completion
130- Dismiss option (don't trap users)

Onboarding Checklist Pattern

When to use:

  • Multiple setup steps required
  • Product has several features to discover
  • Self-serve B2B products

Best practices:

  • 3-7 items (not overwhelming)
  • Order by value (most impactful first)
  • Start with quick wins
  • Progress bar/completion %
  • Celebration on completion
  • Dismiss option (don't trap users)
Raw lines 117 to 131
132### Empty States
134Empty states are onboarding opportunities, not dead ends.
136**Good empty state:**
137- Explains what this area is for
138- Shows what it looks like with data
139- Clear primary action to add first item
140- Optional: Pre-populate with example data

Empty States

Empty states are onboarding opportunities, not dead ends.

Good empty state:

  • Explains what this area is for
  • Shows what it looks like with data
  • Clear primary action to add first item
  • Optional: Pre-populate with example data
Raw lines 132 to 141
142### Tooltips and Guided Tours
144**When to use:** Complex UI, features that aren't self-evident, power features users might miss
146**Best practices:**
147- Max 3-5 steps per tour
148- Dismissable at any time
149- Don't repeat for returning users
151---

Tooltips and Guided Tours

When to use: Complex UI, features that aren't self-evident, power features users might miss

Best practices:

  • Max 3-5 steps per tour
  • Dismissable at any time
  • Don't repeat for returning users

Raw lines 142 to 152
153## Multi-Channel Onboarding

Multi-Channel Onboarding

Raw lines 153 to 154
155### Email + In-App Coordination
157**Trigger-based emails:**
158- Welcome email (immediate)
159- Incomplete onboarding (24h, 72h)
160- Activation achieved (celebration + next step)
161- Feature discovery (days 3, 7, 14)
163**Email should:**
164- Reinforce in-app actions, not duplicate them
165- Drive back to product with specific CTA
166- Be personalized based on actions taken
168---

Email + In-App Coordination

Trigger-based emails:

  • Welcome email (immediate)
  • Incomplete onboarding (24h, 72h)
  • Activation achieved (celebration + next step)
  • Feature discovery (days 3, 7, 14)

Email should:

  • Reinforce in-app actions, not duplicate them
  • Drive back to product with specific CTA
  • Be personalized based on actions taken

Raw lines 155 to 169
170## Handling Stalled Users

Handling Stalled Users

Raw lines 170 to 171
172### Detection
173Define "stalled" criteria (X days inactive, incomplete setup)

Detection

Define "stalled" criteria (X days inactive, incomplete setup)

Raw lines 172 to 174
175### Re-engagement Tactics
1771. **Email sequence** - Reminder of value, address blockers, offer help
1782. **In-app recovery** - Welcome back, pick up where left off
1793. **Human touch** - For high-value accounts, personal outreach
181---

Re-engagement Tactics

  1. Email sequence - Reminder of value, address blockers, offer help
  2. In-app recovery - Welcome back, pick up where left off
  3. Human touch - For high-value accounts, personal outreach

Raw lines 175 to 182
183## Measurement
185### Key Metrics
187| Metric | Description |
188|--------|-------------|
189| Activation rate | % reaching activation event |
190| Time to activation | How long to first value |
191| Onboarding completion | % completing setup |
192| Day 1/7/30 retention | Return rate by timeframe |

Key Metrics

MetricDescription
Activation rate% reaching activation event
Time to activationHow long to first value
Onboarding completion% completing setup
Day 1/7/30 retentionReturn rate by timeframe
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194### Funnel Analysis
196Track drop-off at each step:
197```
198Signup → Step 1 → Step 2 → Activation → Retention
199100% 80% 60% 40% 25%
200```
202Identify biggest drops and focus there.
204---

Funnel Analysis

Track drop-off at each step:

Signup → Step 1 → Step 2 → Activation → Retention
100%      80%       60%       40%         25%

Identify biggest drops and focus there.


Raw lines 194 to 205
206## Output Format
208### Onboarding Audit
209For each issue: Finding → Impact → Recommendation → Priority

Onboarding Audit

For each issue: Finding → Impact → Recommendation → Priority

Raw lines 208 to 210
211### Onboarding Flow Design
212- Activation goal
213- Step-by-step flow
214- Checklist items (if applicable)
215- Empty state copy
216- Email sequence triggers
217- Metrics plan
219---

Onboarding Flow Design

  • Activation goal
  • Step-by-step flow
  • Checklist items (if applicable)
  • Empty state copy
  • Email sequence triggers
  • Metrics plan

Raw lines 211 to 220
221## Common Patterns by Product Type
223| Product Type | Key Steps |
224|--------------|-----------|
225| B2B SaaS | Setup wizard → First value action → Team invite → Deep setup |
226| Marketplace | Complete profile → Browse → First transaction → Repeat loop |
227| Mobile App | Permissions → Quick win → Push setup → Habit loop |
228| Content Platform | Follow/customize → Consume → Create → Engage |
230---

Common Patterns by Product Type

Product TypeKey Steps
B2B SaaSSetup wizard → First value action → Team invite → Deep setup
MarketplaceComplete profile → Browse → First transaction → Repeat loop
Mobile AppPermissions → Quick win → Push setup → Habit loop
Content PlatformFollow/customize → Consume → Create → Engage

Raw lines 221 to 231
232## Experiment Ideas
234When recommending experiments, consider tests for:
235- Flow simplification (step count, ordering)
236- Progress and motivation mechanics
237- Personalization by role or goal
238- Support and help availability
240**For comprehensive experiment ideas**: See [references/experiments.md](references/experiments.md)
242---

Experiment Ideas

When recommending experiments, consider tests for:

  • Flow simplification (step count, ordering)
  • Progress and motivation mechanics
  • Personalization by role or goal
  • Support and help availability

For comprehensive experiment ideas: See references/experiments.md


Raw lines 232 to 243
Reads a file references/experiments.md :240
244## References
246- **[references/minimum-path-to-value.md](references/minimum-path-to-value.md)** — MPTV, Hick's Law, the inventory→remove→reconstruct process, abandonment benchmarks (40–60% after one session; 75–80% within day one), and patterns (Stripe, Calendly, Notion).
247- **[references/activation-models.md](references/activation-models.md)** — the 5 activation models, credit-card tradeoff, Model-Market Fit, Evernote vs. Notion.
248- **[references/experiments.md](references/experiments.md)** — comprehensive A/B test and experiment ideas.
250---

References

  • references/minimum-path-to-value.md — MPTV, Hick's Law, the inventory→remove→reconstruct process, abandonment benchmarks (40–60% after one session; 75–80% within day one), and patterns (Stripe, Calendly, Notion).
  • references/activation-models.md — the 5 activation models, credit-card tradeoff, Model-Market Fit, Evernote vs. Notion.
  • references/experiments.md — comprehensive A/B test and experiment ideas.

Raw lines 244 to 251
252## Task-Specific Questions
2541. Which early action predicts later retention, using what activation window and fully observed signup cohort?
2552. What happens immediately after signup?
2563. Where do users currently drop off?
2574. What's your activation rate target?
2585. Do you have cohort analysis on successful vs. churned users?
260---

Task-Specific Questions

  1. Which early action predicts later retention, using what activation window and fully observed signup cohort?
  2. What happens immediately after signup?
  3. Where do users currently drop off?
  4. What's your activation rate target?
  5. Do you have cohort analysis on successful vs. churned users?

Raw lines 252 to 261
262## Related Skills
264- **signup**: For optimizing the signup before onboarding
265- **emails**: For onboarding email series
266- **paywalls**: For converting to paid during/after onboarding
267- **ab-testing**: For testing onboarding changes

Related Skills

  • signup: For optimizing the signup before onboarding
  • emails: For onboarding email series
  • paywalls: For converting to paid during/after onboarding
  • ab-testing: For testing onboarding changes
Raw lines 262 to 267
Names a skill paywalls :266
Names a skill ab-testing :267

From coreyhaines31/marketingskills at 88c79f6, 2026-10-30. Skills read by DeepSeek V4.1 Flash on 2026-11-04. Summary and techniques by Claude Opus 5.5 on 2026-11-06.