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.
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.
The action that correlates most strongly with retention:
Examples by product type:
| 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:
When to use:
Best practices:
Empty states are onboarding opportunities, not dead ends.
Good empty state:
When to use: Complex UI, features that aren't self-evident, power features users might miss
Best practices:
Trigger-based emails:
Email should:
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:
添加到 ChromeSignup → 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:
For comprehensive experiment ideas: See references/experiments.md