When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value — "activation rate," "empty states," "onboarding checklist," "aha moment," "users sign up but don't use the product." Use when users sign up but don't stick around. For signup/registration optimization, see signup-flow-cro. For email sequences, see email-sequence.
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Get users to their "aha moment" fast and build habits that drive long-term retention.
Product context: If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it first and tailor output to it; only ask for what it doesn't cover.
Understand first:
The action most strongly correlated with retention: what retained users do that churned users don't; the earliest indicator of future engagement.
Examples by product type:
Activation metrics: % of signups reaching activation, time to activation, steps to activation, activation by cohort/source.
| 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, 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).
Onboarding opportunities, not dead ends: explain what the area is for, show what it looks like with data, offer one clear action to add the first item, optionally pre-populate 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:
Email should: reinforce in-app actions (not duplicate them), drive back to product with a specific CTA, personalize based on actions taken.
Detection: define "stalled" criteria (X days inactive, incomplete setup).
Re-engagement tactics:
| 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; focus on the biggest drops.
Signup → Step 1 → Step 2 → Activation → Retention
100% 80% 60% 40% 25%
Onboarding Audit — per 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
| 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 |
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
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Act as a Senior Accessibility Engineer to audit a page, component, or design against WCAG 2.2 AA. Produces a triaged finding list (critical/serious/moderate), focus-order map, contrast report, ARIA decision tree, and a screen-reader test plan. Use when shipping new UI, hardening an existing flow, or preparing for VPAT/accessibility conformance.
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When the user wants to plan, design, or implement an A/B test or experiment — "split test," "variant copy," "multivariate test," "hypothesis," "statistical significance," "how long should I run this test," or comparing two versions. For tracking implementation, see analytics-tracking. For page-level conversion optimization, see page-cro.
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When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, full variations — for any paid platform; 'ad copy variations,' 'RSA headlines,' 'bulk ad copy,' 'creative testing,' 'write me some ads.' For campaign strategy and targeting, see paid-ads. For landing page copy, see copywriting.
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When the user wants content cited by LLMs or surfaced in AI-generated answers — 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'AI Overviews,' 'optimize for ChatGPT/Perplexity/Claude,' 'AI citations,' 'zero-click search.' For traditional technical/on-page audits, see seo-audit. For structured data, see schema-markup.
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When the user wants to set up, improve, or audit analytics tracking and measurement — "GA4," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "tracking plan," "attribution," "Mixpanel," "Segment," "are my events firing," or how to measure marketing results. For A/B test measurement, see ab-test-setup.
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Architectural decision advisor for cloud, data, and SaaS distributed systems. Use when the user asks "should we use X or Y", weighs a tradeoff, or needs a decision matrix, scaling analysis, cost-at-scale review, data-tier design, multi-tenancy model, or API/resilience guidance. For full technical blueprints, use enterprise-design.
日本語の概要は準備中です。原文の説明を表示しています。