startup-business-models
Revenue model design, unit economics, pricing strategy, and monetization optimization
$ 설치
git clone https://github.com/vasilyu1983/AI-Agents-public /tmp/AI-Agents-public && cp -r /tmp/AI-Agents-public/frameworks/claude-code-kit/framework/skills/startup-business-models ~/.claude/skills/AI-Agents-public// tip: Run this command in your terminal to install the skill
SKILL.md
name: startup-business-models description: Revenue model design, unit economics, pricing strategy, and monetization optimization version: "1.0"
Startup Business Models
Systematic framework for designing, analyzing, and optimizing revenue models and unit economics.
When to Use This Skill
Use this skill when:
- Designing or analyzing revenue models (subscription, usage-based, marketplace, freemium)
- Calculating unit economics (LTV, CAC, payback period, gross margin)
- Creating or optimizing pricing strategy and tier design
- Evaluating business model viability for investors
- Building financial models for startups
- Analyzing customer economics by segment or cohort
Related Skills:
- startup-idea-validation - Validate before building
- startup-competitive-analysis - Market positioning
- startup-fundraising - Investor metrics and pitch
- startup-go-to-market - GTM strategy
Decision Tree: What Business Model Analysis?
BUSINESS MODEL QUESTION
│
├─► "How should I charge?" ────────► Revenue Model Selection
│ └─► Model comparison, hybrid strategies
│
├─► "What price?" ─────────────────► Pricing Strategy
│ └─► Value-based, competition, willingness-to-pay
│
├─► "Is it profitable?" ───────────► Unit Economics Analysis
│ └─► LTV, CAC, margins, payback
│
├─► "Which customers are best?" ───► Customer Economics
│ └─► Segment profitability, cohorts
│
├─► "How do I grow revenue?" ──────► Revenue Expansion
│ └─► Upsell, cross-sell, pricing tiers
│
└─► "Full model design" ───────────► COMPREHENSIVE ANALYSIS
└─► All dimensions
Revenue Model Types
Model Taxonomy
| Model | Description | Best For | Examples |
|---|---|---|---|
| Subscription | Recurring fee for access | Predictable value delivery | SaaS, media, software |
| Usage-Based | Pay per unit consumed | Variable consumption | Cloud, API, telecom |
| Freemium | Free tier + paid upgrades | Network effects, low marginal cost | Slack, Dropbox, Spotify |
| Marketplace | Take-rate on transactions | Two-sided platforms | Uber, Airbnb, eBay |
| Transaction | Fee per transaction | Payment, financial services | Stripe, PayPal |
| License | One-time or periodic fee | Enterprise software | Microsoft, Adobe (legacy) |
| Advertising | Monetize attention | Scale audiences | Google, Meta, TikTok |
| Hardware + Service | Device + recurring service | IoT, connected products | Peloton, Nest |
| Outcome-Based | Pay for results | High-value, measurable outcomes | Performance marketing |
Model Selection Framework
HIGH VALUE, PREDICTABLE DELIVERY
│
├─► Subscription
│
VARIABLE VALUE, VARIABLE USAGE
│
├─► Usage-Based or Hybrid
│
PLATFORM/NETWORK EFFECTS
│
├─► Freemium → Upgrade
│
TWO-SIDED MARKET
│
├─► Marketplace (Take-Rate)
│
TRANSACTION-ENABLING
│
└─► Transaction Fees
Hybrid Models (2024-2025 Trend)
| Hybrid | Components | Examples |
|---|---|---|
| Subscription + Usage | Base fee + overage | AWS, Twilio |
| Freemium + Usage | Free tier + usage-based premium | OpenAI API |
| Subscription + Transaction | Platform fee + take-rate | Shopify |
| Outcome + Subscription | Base + success fee | Performance agencies |
Unit Economics Framework
Core Metrics
| Metric | Formula | Target | Notes |
|---|---|---|---|
| LTV | ARPU × Gross Margin × (1 / Churn Rate) | 3x+ CAC | Lifetime customer value |
| CAC | Sales & Marketing Spend / New Customers | LTV/3 | Customer acquisition cost |
| LTV:CAC | LTV / CAC | >3:1 | Efficiency ratio |
| Payback | CAC / (ARPU × Gross Margin) | <12 months | Months to recover CAC |
| Gross Margin | (Revenue - COGS) / Revenue | >70% (SaaS) | Profitability per unit |
| Net Revenue Retention | (Starting MRR + Expansion - Churn) / Starting MRR | >100% | Growth from existing |
| Churn Rate | Lost Customers / Total Customers | <5% annual | Customer retention |
LTV Calculation Methods
Simple LTV:
LTV = ARPU × Average Customer Lifetime
Where: Average Customer Lifetime = 1 / Monthly Churn Rate
Margin-Adjusted LTV:
LTV = ARPU × Gross Margin × (1 / Churn Rate)
Cohort-Based LTV (Most Accurate):
LTV = Σ (Revenue per Cohort Month × Retention Rate at Month)
CAC Calculation
Fully-Loaded CAC:
CAC = (Sales Salaries + Marketing Spend + Sales Tools +
Marketing Tools + Content + Events + Agency Fees) /
New Customers Acquired
By Channel:
| Channel | Spend | Customers | CAC |
|---|---|---|---|
| Paid Search | $X | N | $X |
| Content/SEO | $X | N | $X |
| Sales Outbound | $X | N | $X |
| Referral | $X | N | $X |
| Blended | $X | N | $X |
Unit Economics by Stage
| Stage | LTV:CAC | Payback | Focus |
|---|---|---|---|
| Pre-PMF | N/A | N/A | Finding product-market fit |
| Early | 1-2x | 18-24 mo | Proving unit economics work |
| Growth | 3-4x | 12-18 mo | Scaling efficiently |
| Scale | 4-5x+ | <12 mo | Optimizing profitability |
Pricing Strategy
Pricing Approaches
| Approach | Method | When to Use |
|---|---|---|
| Value-Based | Price = % of customer value | B2B, clear ROI |
| Competition-Based | Price relative to alternatives | Commoditized markets |
| Cost-Plus | Cost + target margin | Low differentiation |
| Willingness-to-Pay | Research-based WTP | New markets, no reference |
Value-Based Pricing Framework
1. QUANTIFY CUSTOMER VALUE
└─► What's the $ impact of your solution?
2. IDENTIFY VALUE DRIVERS
└─► Time saved? Revenue gained? Cost reduced?
3. SET PRICE AS % OF VALUE
└─► Typically 10-30% of quantified value
4. VALIDATE WITH CUSTOMERS
└─► Willingness-to-pay research
Pricing Tiers Design
| Element | Free | Starter | Pro | Enterprise |
|---|---|---|---|---|
| Target | Individuals | Small teams | Growth teams | Large orgs |
| Price | $0 | $X/mo | $X/mo | Custom |
| Limits | X users, Y usage | X users, Y usage | X users, Y usage | Unlimited |
| Features | Core only | Core + Basic | Core + Advanced | All + Custom |
| Support | Community | Priority | Dedicated | |
| Billing | — | Monthly/Annual | Monthly/Annual | Annual |
Pricing Levers
| Lever | Options | Considerations |
|---|---|---|
| Metric | Per seat, per usage, flat | Align with value delivery |
| Frequency | Monthly, annual, one-time | Cash flow vs. commitment |
| Discounts | Volume, annual, startup | Incentive alignment |
| Bundling | All-in-one vs. à la carte | Simplicity vs. customization |
| Anchoring | Show expensive option first | Psychological pricing |
Willingness-to-Pay Research
Van Westendorp Method (Price Sensitivity Meter):
| Question | Purpose |
|---|---|
| "At what price is this too expensive?" | Upper bound |
| "At what price is this expensive but acceptable?" | Premium threshold |
| "At what price is this a bargain?" | Value perception |
| "At what price is this too cheap (suspicious)?" | Lower bound |
Gabor-Granger Method:
1. Show product at price point A
2. "Would you buy at this price?" Y/N
3. If Yes → Show higher price
4. If No → Show lower price
5. Repeat to find demand curve
SaaS Metrics Deep Dive
MRR Components
| Component | Definition | Formula |
|---|---|---|
| New MRR | From new customers | Sum(New Customer MRR) |
| Expansion MRR | Upgrades + add-ons | Sum(Upsell + Cross-sell) |
| Contraction MRR | Downgrades | Sum(Downgrade MRR) |
| Churn MRR | Lost customers | Sum(Churned Customer MRR) |
| Net New MRR | Monthly change | New + Expansion - Contraction - Churn |
Cohort Analysis Template
| Cohort | M0 | M1 | M2 | M3 | M6 | M12 |
|---|---|---|---|---|---|---|
| Jan 2024 | 100% | 95% | 90% | 88% | 82% | 75% |
| Feb 2024 | 100% | 93% | 88% | 85% | 80% | — |
| Mar 2024 | 100% | 94% | 89% | 86% | — | — |
Net Revenue Retention (NRR)
NRR = (Starting MRR + Expansion - Contraction - Churn) / Starting MRR × 100%
Benchmarks:
- <100%: Leaky bucket (fix churn first)
- 100-110%: Healthy
- 110-120%: Strong
- >120%: Exceptional (enterprise, land-and-expand)
Marketplace Economics
Key Marketplace Metrics
| Metric | Formula | Benchmark |
|---|---|---|
| GMV | Total transaction value | Growth rate |
| Take Rate | Revenue / GMV | 5-30% |
| Liquidity | Successful transactions / Attempts | >80% |
| CAC Supply | Cost to acquire seller/provider | — |
| CAC Demand | Cost to acquire buyer/consumer | — |
| ARPU | Revenue per active user | — |
Take Rate by Category
| Category | Typical Take Rate | Notes |
|---|---|---|
| Rideshare | 20-30% | High service component |
| E-commerce | 10-15% | Logistics adds value |
| Services | 15-25% | Trust/vetting value |
| B2B | 5-15% | Lower, higher volume |
| Digital goods | 15-30% | No physical logistics |
Marketplace Unit Economics
Buyer Side:
LTV = Transactions/Year × AOV × Take Rate × Retention Years
Seller Side:
LTV = GMV/Year × Take Rate × Retention Years
Combined:
Platform LTV = Buyer LTV + Seller LTV - Cross-Subsidization
Revenue Expansion Strategies
Expansion Revenue Levers
| Lever | Mechanism | Example |
|---|---|---|
| Seat Expansion | More users in org | Slack per-user pricing |
| Usage Growth | Natural consumption increase | AWS compute |
| Tier Upgrade | Move to higher plan | Free → Pro → Enterprise |
| Add-on Sales | Complementary products | Salesforce add-ons |
| Cross-sell | Related products | HubSpot suite |
| Price Increase | Annual adjustments | Annual price escalators |
Land and Expand Framework
LAND (Initial Deal)
│
└─► Small team, specific use case, low ACV
│
▼
ADOPT (Prove Value)
│
└─► Usage growth, success metrics, champions
│
▼
EXPAND (Grow Account)
│
└─► More users, departments, use cases
│
▼
STRATEGIC (Enterprise Deal)
│
└─► Company-wide, multi-year, executive sponsor
Expansion Triggers
| Trigger | Signal | Action |
|---|---|---|
| Usage hitting limits | 80%+ of tier limits | Proactive upgrade offer |
| New use case request | Feature request in adjacent area | Cross-sell motion |
| Team growth | New users being added | Seat expansion |
| Success metrics | Strong ROI demonstrated | Enterprise pitch |
| Contract renewal | 90 days before renewal | Annual review, expansion conversation |
Model Comparison Framework
Decision Matrix
| Factor | Subscription | Usage-Based | Freemium | Marketplace |
|---|---|---|---|---|
| Predictability | High | Low | Medium | Medium |
| Scalability | Medium | High | High | High |
| Stickiness | High | Low | Medium | High |
| Sales complexity | Medium | High | Low | Medium |
| PMF signal | Renewal | Usage | Conversion | Liquidity |
| Best for stage | Post-PMF | Scale | Pre-PMF | Platform |
Revenue Model Scorecard
| Criterion | Weight | Model A | Model B | Model C |
|---|---|---|---|---|
| Customer alignment | 25% | |||
| Predictability | 20% | |||
| Scalability | 20% | |||
| Competitive positioning | 15% | |||
| Implementation complexity | 10% | |||
| Expansion potential | 10% | |||
| Weighted Score | 100% |
Resources
| Resource | Purpose |
|---|---|
| unit-economics-calculator.md | LTV, CAC, payback calculations |
| pricing-research-guide.md | WTP research methodology |
| saas-metrics-playbook.md | SaaS-specific metrics deep dive |
Templates
| Template | Purpose |
|---|---|
| business-model-canvas.md | Full model design |
| unit-economics-worksheet.md | Calculate and track metrics |
| pricing-tier-design.md | Design pricing tiers |
Data
| File | Purpose |
|---|---|
| sources.json | Business model resources |
Repository

vasilyu1983
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vasilyu1983/AI-Agents-public/frameworks/claude-code-kit/framework/skills/startup-business-models
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