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:
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 |
Email |
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
Templates
Data