revenue-optimizer（收入优化器）

Revenue Optimizer

Build revenue features and monetization systems. Analyze existing codebases to understand features, calculate costs, and create data-driven pricing strategies.

Workflow

1. Discover - Scan codebase for features, services, and integrations
2. Cost Analysis - Calculate per-user and per-feature costs from services
3. Design - Create pricing tiers based on value + cost data
4. Implement - Build payment integration, pricing logic, and checkout flows
5. Optimize - Add conversion optimization and revenue tracking

Feature Discovery

Scan codebase to build feature inventory:

Feature Discovery Process:
1. Scan routes/endpoints → identify user-facing features
2. Scan components/pages → map UI features
3. Scan service integrations → identify cost-generating features
4. Scan database models → understand data entities
5. Cross-reference → map features to their cost drivers

Look for these patterns:

• Routes/Controllers: Each endpoint = potential feature
• React/Vue components: Feature-specific UI modules
• Service clients: AWS SDK, OpenAI, Stripe, Twilio, etc.
• Background jobs: Compute-intensive operations
• Storage operations: S3, database writes, file uploads

Example feature inventory output:

Features Discovered:
├── Core (low cost): Auth, dashboard, CRUD
├── Premium (medium cost): PDF export, email, file storage
└── High-Value (high cost): AI analysis, video processing, real-time sync

Cost Analysis

Analyze services to calculate true costs per user/feature. See references/cost-analysis.md for detailed patterns.

Service Detection

Scan for these cost sources:

• Config files: .env, config/, secrets
• Package.json/requirements.txt: SDK dependencies
• Infrastructure: terraform/, cloudformation/, docker-compose
• Code imports: aws-sdk, openai, stripe, twilio, etc.

Cost Mapping

Map fixed costs, variable costs (per user), and feature costs (per use). See references/cost-analysis.md for detailed cost mapping patterns and output format.

Pricing Strategy Design

Combine feature value + cost data:

1. Calculate cost floor (break-even per user)
2. Assess feature value (what users pay for alternatives)
3. Set price = max(cost + margin, perceived value)
4. Group features into tiers by cost similarity:

- Free: Low-cost features only, cap variable costs, goal < $0.50/user/month - Pro: Medium-cost features, price at 3-5x cost, primary revenue driver - Enterprise: High-cost features (AI, video), value-based pricing (10x+ cost OK)

Optimal Price = (Cost Floor x 0.3) + (Value Ceiling x 0.7) where Cost Floor = Cost to Serve / (1 - Target Margin).

See references/pricing-patterns.md for implementation examples.

Complete Analysis Example

When asked to create a pricing strategy, produce a full analysis:

PRICING STRATEGY REPORT
=======================================

CODEBASE ANALYSIS
---------------------------------------
Services: AWS S3, OpenAI GPT-4, SendGrid, Auth0, Vercel, PlanetScale

Features:
  Core (6): Dashboard, project mgmt, collaboration, reporting
  Premium (3): PDF export (Lambda), analytics (Postgres), API access
  AI-Powered (2): AI writing + smart suggestions (GPT-4)

COST BREAKDOWN
---------------------------------------
Fixed (Monthly):
  Vercel $20 + PlanetScale $29 + Auth0 $0 = $49/month

Variable (Per User/Month):
  Auth0 $0.02 + Storage $0.01 + Email $0.01 = $0.04/user

Feature (Per Use):
  AI Writing $0.03 | PDF Export $0.01 | API $0.001

USAGE PATTERNS
---------------------------------------
  API Calls/month:   Casual 50% ~50 | Regular 40% ~500 | Power 10% ~5K
  AI Generations:    Casual ~5 | Regular ~50 | Power ~300

Tier Limits: Free 100 API/10 AI | Pro 5K API/100 AI | Business unlimited

REVENUE MODEL
---------------------------------------
Distribution: Free 80% | Pro 15% | Business 5%
ARPU: (80% x $0) + (15% x $19) + (5% x $49) = $5.30/user
LTV: ($5.30 x 0.87) / 0.04 = $115
Cost to Serve: Free $0.10 | Pro $2.50 | Business $12
Break-Even: 62 users

12-Month Projection (15% growth):
  M1: 100 users, $530 MRR
  M6: 266 users, $1,410 MRR
  M12: 814 users, $4,314 MRR -- $51,768 ARR

RECOMMENDED TIERS
---------------------------------------
FREE ($0)       3 projects | 100 API | 10 AI | 500MB
PRO ($19/mo)    Unlimited | 5K API | 100 AI | 10GB | Margin 87%
BUSINESS ($49)  All Pro + 50K API | 500 AI | 50GB | 5 seats | Margin 76%
ENTERPRISE      Custom $200+ | Unlimited | SSO | SLA

Overage: AI $0.10/use | API $0.005/call
=======================================

Payment Provider Selection

For detailed integration patterns, see:

• Stripe: references/stripe.md

Pricing Tier Design

Common patterns:

• Good-Better-Best: 3 tiers with clear value escalation
• Freemium: Free tier with premium upsell
• Usage-Based: Pay per API call, storage, or compute
• Per-Seat: Charge per team member

For tier structure examples and implementation, see references/pricing-patterns.md.

Subscription Implementation

Key components:

1. Subscription state management - Track active, canceled, past_due
2. Webhook handling - Process payment events reliably
3. Entitlement system - Gate features based on plan
4. Billing portal - Self-service plan management

For subscription system patterns, see references/subscription-patterns.md.

Checkout Optimization

Conversion-focused checkout implementation:

• Minimize form fields (email → payment in 2 steps max)
• Show trust signals (security badges, money-back guarantee)
• Display social proof near purchase button
• Offer annual discount prominently (20-40% standard)
• Pre-select recommended plan

For checkout implementation details, see references/checkout-optimization.md.

Feature Gating Pattern

// Entitlement check pattern
async function checkFeatureAccess(userId: string, feature: string): Promise<boolean> {
  const subscription = await getSubscription(userId);
  const plan = PLANS[subscription.planId];
  return plan.features.includes(feature);
}

// Usage in route/component
if (!await checkFeatureAccess(user.id, 'advanced_export')) {
  return showUpgradePrompt('advanced_export');
}

Revenue Tracking

Essential metrics to implement:

• MRR (Monthly Recurring Revenue)
• Churn Rate (cancellations / total subscribers)
• LTV (Lifetime Value = ARPU / churn rate)
• Conversion Rate (paid / total signups)

Implementation: Send events to analytics (Mixpanel, Amplitude, or custom) on:

• subscription.created
• subscription.upgraded
• subscription.canceled
• payment.succeeded
• payment.failed

Quick Implementation Checklist

• Payment provider account and API keys configured
• Webhook endpoint receiving and verifying events
• Subscription state synced to database
• Feature entitlement checks on protected routes
• Billing portal or plan management UI
• Upgrade prompts at key user moments
• Revenue events tracked in analytics
• Failed payment retry and dunning emails