Onboarding
Corey HainesCommunityCreated by Corey Haines
- Skill
- Guidelines
- Business and productivity
- MIT
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AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a structured framework for auditing and redesigning user onboarding experiences. It focuses on identifying the 'aha moment'—the specific action that correlates with long-term retention—and streamlining the path to that value. By applying principles like the Endowed Progress Effect and the Peak-End Rule, the skill helps you remove friction, design effective checklists, and implement data-driven activation strategies to ensure new users successfully adopt your product.
What it does
- Defines the Minimum Path to Value (MPTV) to reduce user drop-off.
- Identifies the core 'aha moment' that drives long-term retention.
- Provides patterns for effective onboarding checklists and empty states.
- Offers strategies for coordinating in-app guidance with email nurturing.
- Outlines methods for measuring activation rates and time-to-activation.
- Suggests experiment ideas to test flow improvements and motivation mechanics.
When to use it
- When users sign up but fail to become active or retained users.
- When you need to optimize the first-run experience or onboarding flow.
- When you are struggling with low activation rates or high churn after signup.
- When you want to implement or improve an onboarding checklist or empty state strategy.
- When you need to define or refine your product's activation metrics.
Advantages
- Focuses on behavioral psychology to increase user motivation.
- Prioritizes data-driven activation definitions over vanity metrics.
- Provides actionable, modular components for building onboarding flows.
- Helps balance user friction with necessary setup steps.
- Includes clear frameworks for measuring success and identifying bottlenecks.
Usage examples
- “Our B2B SaaS product has a 60% drop-off after signup. How can I improve our onboarding flow?”
- The agent will guide you through an audit of your current flow, help define your activation 'aha moment', and suggest specific interventions like simplifying the MPTV or adding a progress-based checklist.
- “We want to implement an onboarding checklist. What are the best practices?”
- The agent will provide guidelines on checklist length (3-7 items), ordering by value, using progress bars, and ensuring the checklist is dismissable to avoid trapping users.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/coreyhaines31/onboarding/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip onboarding.zip -d .agents/skills
Documentation by Corey Haines
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.
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:
Product Context - What type of product? B2B or B2C? Core value proposition?
Activation Definition - What's the "aha moment"? What action indicates a user "gets it"?
Current State - What happens after signup? Where do users drop off?
Core Principles
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).
2. One Goal Per Session
Focus first session on one successful outcome. Save advanced features for later.
3. Do, Don't Show
Interactive > Tutorial. Doing the thing > Learning about the thing.
4. Progress Creates Motivation
Show advancement. Celebrate completions. Make the path visible. (See onboarding psychology below for the mechanisms.)
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.
Onboarding Toolkit (10 Components)
The components you assemble an onboarding experience from. Use the fewest that reach value:
| Component | Purpose |
|---|---|
| Welcome forms | Capture role/goal to personalize the path (keep short — Hick's Law) |
| Initial screens | First-run screens that orient and point to one clear action |
| Drip emails | Multi-touch nurture — one concept per email, don't overload |
| Skippable tutorials | Optional guidance users can bypass — never trap them |
| Videos | Show complex workflows visually |
| Docs / help center | Self-serve reference for when users get stuck |
| Onboarding calls | Human touch for complex or high-value accounts |
| Data inputs | Getting the user's real data in so value feels "real" |
| Checklists | Ordered, value-first steps with visible progress (see below) |
| Empty states | Guided first-action opportunities, not dead ends (see below) |
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.
Find Your Aha Moment
Find early value actions associated with later retention, using a defined cohort and timeline:
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.
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.
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.
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.
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
Activation Metrics
% of signups who reach activation
Time to activation
Steps to activation
Activation by cohort/source
Onboarding Flow Design
Immediate Post-Signup (First 30 Seconds)
| Approach | Best For | Risk |
|---|---|---|
| Product-first | Simple products, B2C, mobile | Blank slate overwhelm |
| Guided setup | Products needing personalization | Adds friction before value |
| Value-first | Products with demo data | May not feel "real" |
Whatever you choose:
Clear single next action
No dead ends
Progress indication if multi-step
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)
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
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
Multi-Channel Onboarding
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
Handling Stalled Users
Detection
Define "stalled" criteria (X days inactive, incomplete setup)
Re-engagement Tactics
Email sequence - Reminder of value, address blockers, offer help
In-app recovery - Welcome back, pick up where left off
Human touch - For high-value accounts, personal outreach
Measurement
Key Metrics
| Metric | Description |
|---|---|
| Activation rate | % reaching activation event |
| Time to activation | How long to first value |
| Onboarding completion | % completing setup |
| Day 1/7/30 retention | Return rate by timeframe |
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.
Output Format
Onboarding Audit
For each issue: Finding → Impact → Recommendation → Priority
Onboarding Flow Design
Activation goal
Step-by-step flow
Checklist items (if applicable)
Empty state copy
Email sequence triggers
Metrics plan
Common Patterns by Product Type
| Product Type | Key Steps |
|---|---|
| B2B SaaS | Setup wizard → First value action → Team invite → Deep setup |
| Marketplace | Complete profile → Browse → First transaction → Repeat loop |
| Mobile App | Permissions → Quick win → Push setup → Habit loop |
| Content Platform | Follow/customize → Consume → Create → Engage |
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
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.
Task-Specific Questions
Which early action predicts later retention, using what activation window and fully observed signup cohort?
What happens immediately after signup?
Where do users currently drop off?
What's your activation rate target?
Do you have cohort analysis on successful vs. churned users?
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
Files
- ATTRIBUTION.mdAdded by AutoGineer881 B
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md11.3 KiB
- evals/evals.json8.0 KiB
- references/activation-models.md4.0 KiB
- references/experiments.md7.6 KiB
- references/minimum-path-to-value.md3.1 KiB
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Security
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Attribution and licence
- Created by
- Corey Haines
- Publisher
- Corey Haines (Community)
- Source
- coreyhaines31/marketingskills · skills/onboarding · commit 96798cf
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Corey Haines or Corey Haines.
Download ZIP
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