Optimizes the post-signup user journey to maximize activation rates and time-to-value. It designs onboarding flows, checklists, and first-run experiences that guide new users to their 'aha moment' and establish retention habits.
Say it in your own words; the assistant finds this recipe by itself. Examples:
Use this skill when users are signing up but failing to activate, complete setup, or return to the product. It is appropriate for designing or improving the post-signup journey, defining activation metrics, and creating onboarding checklists or empty states. It addresses specific issues like low activation rates, high drop-off after registration, or users not understanding the product's core value.
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.
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:
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).
Focus first session on one successful outcome. Save advanced features for later.
Interactive > Tutorial. Doing the thing > Learning about the thing.
Show advancement. Celebrate completions. Make the path visible. (See onboarding psychology below for the mechanisms.)
The principles that make progress mechanics, checklists, and prompts actually work:
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) |
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 early value actions associated with later retention, using a defined cohort and timeline:
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
| 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
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 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
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
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
Define "stalled" criteria (X days inactive, incomplete setup)
| 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 |
Track drop-off at each step:
Signup → Step 1 → Step 2 → Activation → Retention
100% 80% 60% 40% 25%
Identify biggest drops and focus there.
For each issue: Finding → Impact → Recommendation → Priority
| 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 |
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
LICENSESKILL.mdevals/evals.jsonreferences/activation-models.mdreferences/experiments.mdreferences/minimum-path-to-value.mdVendored from coreyhaines31/marketingskills, commit e85f3cbc2e4a, path skills/onboarding, licence MIT. The upstream licence file ships inside the skill.