Revenue Optimizer

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

Workflow

Discover - Scan codebase for features, services, and integrations
Cost Analysis - Calculate per-user and per-feature costs from services
Design - Create pricing tiers based on value + cost data
Implement - Build payment integration, pricing logic, and checkout flows
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 Features (low cost)
│   ├── User authentication (Cognito/Auth0)
│   ├── Dashboard views (read-only)
│   └── Basic CRUD operations
├── Premium Features (medium cost)
│   ├── PDF export (uses Puppeteer/Lambda)
│   ├── Email notifications (SendGrid)
│   └── File storage (S3)
└── High-Value Features (high cost)
    ├── AI analysis (OpenAI API)
    ├── Video processing (FFmpeg/Lambda)
    └── Real-time sync (WebSockets)

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

Cost Analysis Output:
├── Fixed Costs (monthly)
│   ├── Hosting: $50 (Vercel Pro)
│   ├── Database: $25 (PlanetScale)
│   └── Monitoring: $20 (Datadog)
│   └── Total Fixed: $95/month
├── Variable Costs (per user/month)
│   ├── Auth: $0.05/MAU (Auth0)
│   ├── Storage: $0.023/GB (S3)
│   └── Email: $0.001/email (SendGrid)
├── Feature Costs (per use)
│   ├── AI Analysis: $0.03/request (GPT-4)
│   ├── PDF Export: $0.01/export (Lambda)
│   └── SMS: $0.0075/message (Twilio)
└── Recommended Minimums:
    ├── Break-even at 100 users: $0.95/user
    ├── With 70% margin: $3.17/user
    └── AI feature: charge $0.10/use or limit free tier

Pricing Strategy Design

Combine feature value + cost data:

Pricing Strategy Framework:
1. Calculate cost floor (break-even)
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

Cost-Informed Tier Design

Tier Design Process:
├── Free Tier
│   ├── Include: Low-cost features only
│   ├── Limit: Usage caps on variable costs
│   └── Goal: < $0.50 cost/user/month
├── Pro Tier  
│   ├── Include: Medium-cost features
│   ├── Price: 3-5x your cost (healthy margin)
│   └── Goal: Primary revenue driver
└── Enterprise
    ├── Include: High-cost features (AI, video, etc.)
    ├── Price: Value-based (10x+ cost acceptable)
    └── Goal: High-margin, lower volume

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 Detected:
  • AWS S3 (file storage)
  • OpenAI GPT-4 (AI features)
  • SendGrid (email)
  • Auth0 (authentication)
  • Vercel (hosting)
  • PlanetScale (database)

Features Discovered:
  ├── Core (6 features)
  │   ├── User dashboard
  │   ├── Project management
  │   ├── Team collaboration
  │   └── Basic reporting
  ├── Premium (3 features)
  │   ├── PDF export → uses Lambda
  │   ├── Advanced analytics → uses Postgres aggregations
  │   └── API access → rate-limited endpoints
  └── AI-Powered (2 features)
      ├── AI writing assistant → uses GPT-4
      └── Smart suggestions → uses GPT-4

💰 COST BREAKDOWN
───────────────────────────────────────────────────────────
Fixed Costs (Monthly):
  Vercel Pro .............. $20
  PlanetScale Scaler ...... $29
  Auth0 (base) ............ $0
  ─────────────────────────────
  Total Fixed             $49/month

Variable Costs (Per Active User):
  Auth0 MAU ............... $0.02
  Storage (avg 500MB) ..... $0.01
  Email (avg 10/month) .... $0.01
  ─────────────────────────────
  Total Variable          $0.04/user/month

Feature Costs (Per Use):
  AI Writing (1K tokens) .. $0.03/use
  PDF Export .............. $0.01/use
  API Call ................ $0.001/call

📊 USAGE PATTERN ANALYSIS
───────────────────────────────────────────────────────────
Feature Usage Distribution:

  API Calls/month:
  ├── Casual (50%):     ~50 calls    │██░░░░░░░░│
  ├── Regular (40%):    ~500 calls   │██████░░░░│
  └── Power (10%):      ~5,000 calls │██████████│
  
  AI Generations/month:
  ├── Casual (50%):     ~5 uses      │█░░░░░░░░░│
  ├── Regular (40%):    ~50 uses     │█████░░░░░│
  └── Power (10%):      ~300 uses    │██████████│

Tier Limit Strategy:
  ├── Free:   100 API, 10 AI     (80% casual under)
  ├── Pro:    5,000 API, 100 AI  (95% regular under)
  └── Business: Unlimited

📈 REVENUE MODEL
───────────────────────────────────────────────────────────
User Distribution: Free 80% │ Pro 15% │ Business 5%

ARPU: (80%×$0) + (15%×$19) + (5%×$49) = $5.30/user

LTV = (ARPU × Margin) / Churn
    = ($5.30 × 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
  Cost: $0.10 │ Purpose: Lead generation

PRO ($19/mo · $190/yr save 17%)
  ✓ Unlimited │ 5K API │ 100 AI │ 10GB │ Email support
  Cost: $2.50 │ Margin: 87%

BUSINESS ($49/mo · $490/yr) ⭐ RECOMMENDED
  ✓ All Pro + 50K API │ 500 AI │ 50GB │ 5 seats │ Priority
  Cost: $12 │ Margin: 76%

ENTERPRISE (Custom · $200+)
  ✓ Unlimited │ SSO │ SLA │ Dedicated support

⚠️ OVERAGE: AI $0.10/use │ API $0.005/call

═══════════════════════════════════════════════════════════

Payment Provider Selection

| Provider | Best For | Integration Complexity | |----------|----------|------------------------| | Stripe | SaaS, subscriptions, global | Low | | Paddle | SaaS with tax compliance | Low | | LemonSqueezy | Digital products, simple | Very Low | | PayPal | Marketplaces, existing users | Medium |

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:

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

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

Usage Pattern Analysis

Analyze how users consume features to set optimal tier limits:

Usage Analysis Output:
├── Feature Usage Distribution
│   ├── API Calls
│   │   ├── Casual users (50%): ~50/month
│   │   ├── Regular users (40%): ~500/month
│   │   └── Power users (10%): ~5,000/month
│   └── AI Generations
│       ├── Casual: ~5/month
│       ├── Regular: ~50/month
│       └── Power: ~500/month
├── Consumption Patterns
│   ├── Peak usage: Mon-Fri, 9am-6pm
│   ├── Seasonal spikes: Q4 (+30%)
│   └── Growth trend: +15%/month
└── Tier Limit Recommendations
    ├── Free: 100 API calls (covers 80% of casual)
    ├── Pro: 5,000 API calls (covers 95% of regular)
    └── Enterprise: Unlimited

Set limits so users naturally upgrade:

Free tier: Limit at 80th percentile of casual users
Pro tier: Limit at 95th percentile of regular users
Enterprise: Unlimited or custom

See references/usage-revenue-modeling.md for detailed patterns.

Revenue Modeling

Calculate key SaaS metrics for pricing decisions:

Revenue Model:
├── ARPU (Average Revenue Per User)
│   ├── Free (80%): $0
│   ├── Pro (15%): $29
│   ├── Enterprise (5%): $99
│   └── Blended ARPU: $9.30
├── LTV Calculation
│   ├── ARPU: $9.30
│   ├── Gross Margin: 85%
│   ├── Monthly Churn: 3%
│   └── LTV = ($9.30 × 0.85) / 0.03 = $263
├── Break-Even Analysis
│   ├── Fixed costs: $500/month
│   ├── Variable cost/user: $0.50
│   ├── ARPU: $9.30
│   └── Break-even: 57 users
└── 12-Month Projection
    ├── Month 1: 100 users, $930 MRR
    ├── Month 6: 400 users, $3,720 MRR
    └── Month 12: 1,200 users, $11,160 MRR

Optimal Tier Pricing Formula

Optimal Price = (Cost Floor × 0.3) + (Value Ceiling × 0.7)

Where:
- Cost Floor = Cost to Serve / (1 - Target Margin)
- Value Ceiling = min(Perceived Value, Competitor Price × 1.2)

Example:
- Cost to serve Pro user: $3/month
- Target margin: 80%
- Cost floor: $3 / 0.20 = $15
- Competitor price: $25
- Value ceiling: $30
- Optimal: ($15 × 0.3) + ($30 × 0.7) = $25.50 → $25/month

See references/usage-revenue-modeling.md for full revenue modeling.

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