What it does. 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. Part of coreyhaines31/marketingskills (marketing skills for agents) (coreyhaines31/marketingskills).

Upstream	coreyhaines31/marketingskills
Skill file	skills/onboarding/SKILL.md
License	MIT
Author	Corey Haines
Fetched	2026-09-10

Install

• npx skills add coreyhaines31/marketingskills --skill onboarding, or copy the skill folder into ~/.claude/skills/onboarding/.
• Raw file: curl -sL https://raw.githubusercontent.com/coreyhaines31/marketingskills/HEAD/skills/onboarding/SKILL.md

SKILL.md (verbatim)

name: onboarding
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.
metadata:
  version: 2.0.1

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:

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?

---

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

The action that correlates most strongly with retention:

• What do retained users do that churned users don't?
• What's the earliest indicator of future engagement?

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

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

---

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

1. What action most correlates with retention?
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?

---

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

Other files in this skill

• evals/evals.json
• references/activation-models.md
• references/experiments.md
• references/minimum-path-to-value.md

references/activation-models.md (verbatim)

Activation Models

The activation model is how you let a user experience value before they pay. It shapes signup volume, conversion, and the entire onboarding path. Pick the model before you design the flow.

The 5 activation models

1. Freemium

A free tier that never expires, with paid tiers for more capacity or features.

• Best when: the free tier delivers real value and naturally hits limits that motivate upgrading.
• Risk: give away too much and users never need to pay (see Evernote below).

2. Free trial

Full (or near-full) access for a fixed window: 3, 7, 14, or 30 days.

• Shorter trials create urgency and force faster time-to-value; longer trials suit complex products with longer setup.
• Credit-card requirement is the key lever: requiring a card up front cuts signups by 50–70%, but the users who do sign up convert 2–3× better. Fewer, higher-intent leads vs. more, lower-intent leads — choose based on your funnel goals.

3. Paid trial

A low-cost paid entry, typically $7–10 for 7 days.

• Filters out tire-kickers while lowering the barrier vs. full price.
• Signals seriousness on both sides and pre-collects payment details.

4. Money-back guarantee

Charge full price up front, with a no-questions refund window.

• Removes purchase risk without giving anything away for free.
• Works when the product delivers value quickly enough to beat the refund window.

5. Consultation / white-glove

A human conversation (demo, call, or hands-on setup) gates access — the Superhuman model.

• Best for high-touch, high-price, or complex products where a human ensures the user reaches value.
• Doesn't scale cheaply, but converts and retains well when done right.

Model-Market Fit

Model-Market Fit (Brian Balfour): "your market dictates your model."

You don't get to freely choose your activation model — your market chooses it for you. Price point, buyer sophistication, sales complexity, time-to-value, and competitor norms all constrain what will work. A self-serve $20/mo tool and a $50k enterprise platform cannot use the same model. Match the model to the market before optimizing the onboarding inside it.

The Evernote vs. Notion parable

Two lessons on how much to give away:

• Evernote — gave away too much free. The free tier was generous enough that most users never needed to upgrade. Free was a destination, not a doorway. Growth without matching monetization.
• Notion — hook, then limit. Let users experience real value, then hit meaningful limits (blocks, members, features) that create a natural, well-timed reason to pay.

The principle: the free experience should hook, not satisfy. Give enough value to prove the product and build the habit — but structure the limits so that continued value requires upgrading.

Choosing

1. Start from your market (Model-Market Fit), not your preference.
2. Decide the card-vs-no-card tradeoff explicitly: volume of leads vs. quality of leads.
3. Design the free/trial experience to hook and then limit — never to fully satisfy.
4. Whatever the model, the onboarding inside it still needs the shortest possible path to value (see minimum-path-to-value.md).

references/experiments.md (verbatim)

Onboarding Experiment Ideas

Comprehensive list of A/B tests and experiments for user onboarding and activation.

Contents

• Flow Simplification Experiments (reduce friction, step sequencing, progress & motivation)
• Guided Experience Experiments (product tours, CTA optimization, UI guidance)
• Personalization Experiments (user segmentation, dynamic content)
• Quick Wins & Engagement Experiments (time-to-value, motivation mechanics, support & help)
• Email & Multi-Channel Experiments (onboarding emails, email content, feedback loops)
• Re-engagement Experiments (stalled user recovery, return experience)
• Technical & UX Experiments (performance, mobile onboarding, accessibility)
• Metrics to Track

Flow Simplification Experiments

Reduce Friction

Test	Hypothesis
Email verification timing	During vs. after onboarding
Empty states vs. dummy data	Pre-populated examples
Pre-filled templates	Accelerate setup with templates
OAuth options	Faster account linking
Required step count	Fewer required steps
Optional vs. required fields	Minimize requirements
Skip options	Allow bypassing non-critical steps

Step Sequencing

Test	Hypothesis
Step ordering	Test different sequences
Value-first ordering	Highest-value features first
Friction placement	Move hard steps later
Required vs. optional balance	Ratio of required steps
Single vs. branching paths	One path vs. personalized
Quick start vs. full setup	Minimal path to value

Progress & Motivation

Test	Hypothesis
Progress bars	Show completion percentage
Checklist length	3-5 items vs. 5-7 items
Gamification	Badges, rewards, achievements
Completion messaging	"X% complete" visibility
Starting point	Begin at 20% vs. 0%
Celebration moments	Acknowledge completions

---

Guided Experience Experiments

Product Tours

Test	Hypothesis
Interactive tours	Tools like Navattic, Storylane
Tooltip vs. modal guidance	Subtle vs. attention-grabbing
Video tutorials	For complex workflows
Self-paced vs. guided	User control vs. structured
Tour length	Shorter vs. comprehensive
Tour triggering	Automatic vs. user-initiated

CTA Optimization

Test	Hypothesis
CTA text variations	Action-oriented copy testing
CTA placement	Position within screens
In-app tooltips	Feature discovery prompts
Sticky CTAs	Persist during onboarding
CTA contrast	Visual prominence
Secondary CTAs	"Learn more" vs. primary only

UI Guidance

Test	Hypothesis
Hotspot highlights	Draw attention to key features
Coachmarks	Contextual tips
Feature announcements	New feature discovery
Contextual help	Help where users need it
Search vs. guided	Self-service vs. directed

---

Personalization Experiments

User Segmentation

Test	Hypothesis
Role-based onboarding	Different paths by role
Goal-based paths	Customize by stated goal
Role-specific dashboards	Relevant default views
Use-case question	Personalize based on answer
Industry-specific paths	Vertical customization
Experience-based	Beginner vs. expert paths

Dynamic Content

Test	Hypothesis
Personalized welcome	Name, company, role
Industry examples	Relevant use cases
Dynamic recommendations	Based on user answers
Template suggestions	Pre-filled for segment
Feature highlighting	Relevant to stated goals
Benchmark data	Industry-specific metrics

---

Quick Wins & Engagement Experiments

Time-to-Value

Test	Hypothesis
First quick win	"Complete your first X"
Success messages	After key actions
Progress celebrations	Milestone moments
Next step suggestions	After each completion
Value demonstration	Show what they achieved
Outcome preview	What success looks like

Motivation Mechanics

Test	Hypothesis
Achievement badges	Gamification elements
Streaks	Consecutive day engagement
Leaderboards	Social comparison (if appropriate)
Rewards	Incentives for completion
Unlock mechanics	Features revealed progressively

Support & Help

Test	Hypothesis
Free onboarding calls	For complex products
Contextual help	Throughout onboarding
Chat support	Availability during onboarding
Proactive outreach	For stuck users
Self-service resources	Help docs, videos
Community access	Peer support early

---

Email & Multi-Channel Experiments

Onboarding Emails

Test	Hypothesis
Founder welcome email	Personal vs. generic
Behavior-based triggers	Action/inaction based
Email timing	Immediate vs. delayed
Email frequency	More vs. fewer touches
Quick tips format	Short actionable content
Video in email	More engaging format

Email Content

Test	Hypothesis
Subject lines	Open rate optimization
Personalization depth	Name vs. behavior-based
CTA prominence	Single clear action
Social proof inclusion	Testimonials in email
Urgency messaging	Trial reminders
Plain text vs. designed	Format testing

Feedback Loops

Test	Hypothesis
NPS during onboarding	When to ask
Blocking question	"What's stopping you?"
NPS follow-up	Actions based on score
In-app feedback	Thumbs up/down on features
Survey timing	When to request feedback
Feedback incentives	Reward for completing

---

Re-engagement Experiments

Stalled User Recovery

Test	Hypothesis
Re-engagement email timing	When to send
Personal outreach	Human vs. automated
Simplified path	Reduced steps for returners
Incentive offers	Discount or extended trial
Problem identification	Ask what's blocking
Demo offer	Live walkthrough

Return Experience

Test	Hypothesis
Welcome back message	Acknowledge return
Progress resume	Pick up where left off
Changed state	What happened while away
Re-onboarding	Fresh start option
Urgency messaging	Trial time remaining

---

Technical & UX Experiments

Performance

Test	Hypothesis
Load time optimization	Faster = higher completion
Progressive loading	Perceived performance
Offline capability	Mobile experience
Error handling	Graceful failure recovery

Mobile Onboarding

Test	Hypothesis
Touch targets	Size and spacing
Swipe navigation	Mobile-native patterns
Screen count	Fewer screens needed
Input optimization	Mobile-friendly forms
Permission timing	When to ask

Accessibility

Test	Hypothesis
Screen reader support	Accessibility impact
Keyboard navigation	Non-mouse users
Color contrast	Visibility
Font sizing	Readability

---

Metrics to Track

For all experiments, measure:

Metric	Description
Activation rate	% reaching activation event
Time to activation	Hours/days to first value
Step completion rate	% completing each step
Drop-off points	Where users abandon
Return rate	Users who come back
Day 1/7/30 retention	Engagement over time
Feature adoption	Which features get used
Support requests	Volume during onboarding

references/minimum-path-to-value.md (verbatim)

Minimum Path to Value (MPTV)

Minimum Path to Value (MPTV) — the least number of steps to experience enough value to make a confident decision.

Not the fastest path to any value, and not the full feature tour. It's the shortest route to a moment that's convincing enough for the user to decide "yes, this is for me." Everything else waits.

Why fewer steps win: Hick's Law

Hick's Law — the time and effort to make a decision grows with the number and complexity of choices. Every step, field, and option in onboarding is another decision. More decisions = more hesitation, more drop-off.

MPTV is the deliberate application of Hick's Law to onboarding: strip the path down to the fewest decisions required to reach value.

The abandonment reality

You have far less time and patience than you think:

• 40–60% of users who sign up for a free trial abandon after a single session — and never return.
• 75–80% of trial abandonment happens within the first day.

The decision to stick or bail is made almost immediately. If value isn't reached in the first session, most users are already gone. MPTV exists because the window is that small.

The process: inventory → remove → reconstruct

Build (or fix) your MPTV in three passes:

1. Take inventory. List every step between signup and value — every screen, form field, click, confirmation, permission prompt, and empty state. Be exhaustive and honest. Most teams underestimate their own step count by half.

2. Remove the nonessential. For each step ask: does the user have to do this to reach value right now? If not, cut it, defer it, pre-fill it, or make it skippable. Default to removal. Configuration, profile completeness, advanced settings, and "nice to know" education are almost never essential to first value.

3. Reconstruct / iterate. Rebuild the path with only what survived, in value-first order. Then measure and iterate — the first reconstruction is a hypothesis, not a finish line. Watch where users still stall and cut again.

Benchmark patterns

Products with famously short paths to value:

Product	MPTV pattern
Stripe	Get a working payment integration in ~7 lines of code / ~60% activation — value (a real charge) before any account polish.
Calendly	3-step setup to a shareable, working booking link. Value is a link you can send immediately.
Notion	Progressive disclosure — starts nearly empty, reveals features only as the user needs them. The path to first value (a written page) is trivial; depth unfolds later.

The pattern across all three: reach a real, usable outcome fast, and hide complexity until it's asked for.

Applying it

• Define the value moment first (the aha moment — see SKILL.md). MPTV is the path to that moment.
• Count your current steps before optimizing. You can't remove what you haven't inventoried.
• Treat every retained step as guilty until proven essential.
• Measure step-completion and time-to-value after each reconstruction; the abandonment stats mean your margin for error is one session.

Back to coreyhaines31/marketingskills (marketing skills for agents) or Agent skills.