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feat: add startup-business-analyst plugin
Comprehensive startup analysis plugin with market sizing, financial modeling, team planning, and strategic research for early-stage companies. - 5 skills: market sizing, financial modeling, team planning, competitive analysis, metrics - 3 commands: market-opportunity, financial-projections, business-case - 1 agent: startup-analyst - Covers TAM/SAM/SOM, unit economics, competitive landscape, hiring plans
This commit is contained in:
Seth Hobson
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---
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name: competitive-landscape
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description: This skill should be used when the user asks to "analyze competitors", "assess competitive landscape", "identify differentiation", "evaluate market positioning", "apply Porter's Five Forces", or requests competitive strategy analysis.
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version: 1.0.0
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---
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# Competitive Landscape Analysis
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Comprehensive frameworks for analyzing competition, identifying differentiation opportunities, and developing winning market positioning strategies.
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## Overview
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Understand competitive dynamics using proven frameworks (Porter's Five Forces, Blue Ocean Strategy, positioning maps) to identify opportunities and craft defensible competitive advantages.
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## Porter's Five Forces
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Analyze industry attractiveness and competitive intensity.
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### Force 1: Threat of New Entrants
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**Barriers to Entry:**
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- Capital requirements
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- Economies of scale
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- Switching costs
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- Brand loyalty
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- Regulatory barriers
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- Access to distribution
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- Network effects
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**High Threat:** Low barriers, easy to enter (e.g., simple SaaS tools)
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**Low Threat:** High barriers (e.g., regulated industries, hardware)
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**Analysis Questions:**
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- How easy is it for new competitors to enter?
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- What would it cost to launch a competing product?
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- Are there network effects or switching costs protecting incumbents?
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### Force 2: Bargaining Power of Suppliers
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**Supplier Power Factors:**
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- Supplier concentration
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- Availability of substitutes
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- Importance to supplier
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- Switching costs
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- Forward integration threat
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**High Power:** Few suppliers, critical inputs (e.g., cloud infrastructure providers)
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**Low Power:** Many alternatives, commoditized (e.g., generic services)
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**Analysis Questions:**
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- Who are our critical suppliers?
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- Could they raise prices or reduce quality?
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- Can we switch suppliers easily?
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### Force 3: Bargaining Power of Buyers
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**Buyer Power Factors:**
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- Buyer concentration
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- Volume purchased
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- Product differentiation
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- Price sensitivity
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- Backward integration threat
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**High Power:** Few large customers, standardized products (e.g., enterprise deals)
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**Low Power:** Many small customers, differentiated product (e.g., consumer subscriptions)
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**Analysis Questions:**
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- Can customers easily switch to competitors?
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- Do few customers generate most revenue?
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- How price-sensitive are buyers?
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### Force 4: Threat of Substitutes
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**Substitute Considerations:**
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- Alternative solutions
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- Price-performance tradeoff
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- Switching costs
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- Buyer propensity to substitute
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**High Threat:** Many alternatives, low switching cost (e.g., productivity software)
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**Low Threat:** Unique solution, high switching cost (e.g., ERP systems)
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**Analysis Questions:**
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- What alternative ways can customers solve this problem?
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- How do substitutes compare on price and performance?
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- What's the cost to switch to a substitute?
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### Force 5: Competitive Rivalry
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**Rivalry Intensity Factors:**
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- Number of competitors
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- Industry growth rate
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- Product differentiation
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- Exit barriers
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- Strategic stakes
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**High Rivalry:** Many competitors, slow growth, commoditized (e.g., email marketing)
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**Low Rivalry:** Few competitors, fast growth, differentiated (e.g., emerging AI tools)
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**Analysis Questions:**
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- How many direct competitors exist?
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- Is the market growing or stagnant?
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- How differentiated are offerings?
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- Are competitors competing on price or value?
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### Forces Analysis Summary
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Create a scorecard:
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| Force | Intensity (1-5) | Impact | Key Factors |
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|-------|-----------------|--------|-------------|
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| New Entrants | 3 | Medium | Low barriers but network effects |
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| Supplier Power | 2 | Low | Many cloud providers |
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| Buyer Power | 4 | High | Enterprise customers concentrated |
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| Substitutes | 3 | Medium | Manual processes alternative |
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| Rivalry | 4 | High | 10+ direct competitors |
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**Overall Assessment:** Moderate industry attractiveness with high rivalry and buyer power
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## Blue Ocean Strategy
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Identify uncontested market space through value innovation.
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### Four Actions Framework
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**Eliminate:**
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What factors can be eliminated that the industry takes for granted?
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**Reduce:**
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What factors can be reduced well below industry standard?
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**Raise:**
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What factors can be raised well above industry standard?
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**Create:**
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What factors can be created that the industry never offered?
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### Strategy Canvas
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Map your offering vs. competitors on key factors.
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**Example: Budget Hotels**
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```
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High | ★ Traditional Hotels
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| ★ Budget Hotels (new)
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Low |___________________________________
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Price Luxury Convenience Cleanliness
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Budget Hotel Strategy:
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- Eliminate: Luxury amenities, room service
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- Reduce: Lobby size, staff
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- Raise: Cleanliness, online booking
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- Create: Self-service kiosks, mobile app
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```
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### Value Innovation
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Find the sweet spot: Lower cost + higher value
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**Steps:**
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1. Map industry competing factors
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2. Identify factors to eliminate/reduce (cost savings)
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3. Identify factors to raise/create (differentiation)
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4. Validate that combination creates new market space
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## Competitive Positioning
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### Positioning Map
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Plot competitors on 2-3 key dimensions.
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**Example Dimensions:**
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- Price vs. Features
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- Complexity vs. Ease of Use
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- Enterprise vs. SMB Focus
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- Self-Service vs. High-Touch
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- Generalist vs. Specialist
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**How to Create:**
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1. Choose 2 dimensions most important to customers
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2. Plot all competitors
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3. Identify gaps (white space)
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4. Validate gap represents real customer need
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**Example:**
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```
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High Price
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| ★ Enterprise A ★ Enterprise B
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| ● Our Position (gap)
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| ★ Competitor C ★ Competitor D
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Low Price |____________________________________________
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Simple Complex
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```
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### Differentiation Strategy
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**How to Differentiate:**
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1. **Product Differentiation**
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- Unique features
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- Superior performance
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- Better design/UX
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- Integration ecosystem
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2. **Service Differentiation**
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- Customer support quality
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- Onboarding experience
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- Response time
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- Success programs
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3. **Brand Differentiation**
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- Trust and reputation
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- Thought leadership
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- Community
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- Values alignment
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4. **Price Differentiation**
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- Premium positioning
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- Value positioning
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- Transparent pricing
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- Flexible packaging
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### Positioning Statement Framework
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```
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For [target customer]
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Who [statement of need or opportunity]
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Our product is [product category]
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That [statement of key benefit]
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Unlike [primary competitive alternative]
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Our product [statement of primary differentiation]
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```
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**Example:**
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```
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For e-commerce companies
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Who struggle with email marketing automation
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Our product is an AI-powered email platform
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That increases conversion rates by 40%
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Unlike Klaviyo and Mailchimp
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Our product uses AI to personalize at scale
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```
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## Competitive Intelligence
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### Information Gathering
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**Public Sources:**
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- Company websites and blogs
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- Press releases and news
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- Job postings (hint at strategy)
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- Customer reviews (G2, Capterra)
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- Social media and forums
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- Glassdoor (employee insights)
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- SEC filings (public companies)
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- Patent filings
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**Direct Research:**
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- Customer interviews
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- Win/loss analysis
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- Sales team feedback
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- Product demos and trials
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- Conference attendance
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### Competitor Profile Template
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For each key competitor, document:
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**Company Overview:**
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- Founded, HQ, funding, size
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- Leadership team
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- Company stage and trajectory
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**Product:**
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- Core features
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- Target customers
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- Pricing and packaging
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- Technology stack
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- Recent launches
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**Go-to-Market:**
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- Sales model (self-serve, sales-led)
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- Marketing strategy
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- Distribution channels
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- Partnerships
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**Strengths:**
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- What they do better than anyone
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- Key competitive advantages
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- Market position
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**Weaknesses:**
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- Gaps in product
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- Customer complaints
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- Operational challenges
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**Strategy:**
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- Stated direction
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- Inferred priorities
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- Likely next moves
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## Competitive Pricing Analysis
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### Price Positioning
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**Premium (Top 25%):**
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- Superior product/service
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- Strong brand
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- High-touch sales
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- Enterprise focus
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**Mid-Market (Middle 50%):**
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- Balanced value
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- Standard features
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- Mixed sales model
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- Broad market
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**Value (Bottom 25%):**
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- Basic functionality
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- Self-service
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- Cost leadership
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- High volume, low margin
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### Pricing Comparison Matrix
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| Competitor | Entry Price | Mid Tier | Enterprise | Model |
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|-----------|-------------|----------|------------|-------|
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| Competitor A | $29/mo | $99/mo | Custom | Subscription |
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| Competitor B | $49/mo | $199/mo | $499/mo | Subscription |
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| Us | $39/mo | $129/mo | Custom | Subscription |
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**Analysis:**
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- Are we priced competitively?
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- What does our pricing signal?
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- Are there gaps in our packaging?
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## Go-to-Market Strategy
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### Market Entry Strategies
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**Direct Competition:**
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- Head-to-head against established players
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- Requires differentiation and resources
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- Example: Better features at lower price
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**Niche Focus:**
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- Target underserved segment
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- Become specialist vs. generalist
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- Example: "Salesforce for real estate"
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**Disruptive Innovation:**
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- Target non-consumers or low end
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- Improve over time to move upmarket
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- Example: Freemium model disrupting enterprise
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**Platform Play:**
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- Build ecosystem and network effects
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- Aggregate complementary services
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- Example: Marketplace or API platform
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### Beachhead Market
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**Characteristics of Good Beachhead:**
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- Specific, reachable segment
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- Acute pain you solve well
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- Limited competition
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- Willing to pay
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- Can lead to expansion
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**Example:**
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Instead of "project management software", target "project management for construction teams"
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## Competitive Advantage
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### Sustainable Advantages
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**Network Effects:**
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- Value increases with users
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- Example: Slack, marketplaces
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**Switching Costs:**
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- High cost to change
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- Example: CRM systems with data
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**Economies of Scale:**
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- Unit costs decrease with volume
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- Example: Cloud infrastructure
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**Brand:**
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- Trust and reputation
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- Example: Security software
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**Proprietary Technology:**
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- Patents or trade secrets
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- Example: Algorithms, data
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**Regulatory:**
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- Licenses or approvals
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- Example: Fintech, healthcare
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### Testing Your Advantage
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Ask:
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- Can competitors copy this in < 2 years?
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- Does this matter to customers?
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- Do we execute this better than anyone?
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- Is this advantage durable?
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If "no" to any, it's not a sustainable advantage.
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## Competitive Monitoring
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### What to Track
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**Product Changes:**
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- New features
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- Pricing changes
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- Packaging adjustments
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**Market Signals:**
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- Funding announcements
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- Key hires (especially leadership)
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- Customer wins/losses
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- Partnerships
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**Performance Metrics:**
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- Revenue (if public or disclosed)
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- Customer count
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- Growth rate
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- Market share estimates
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### Monitoring Cadence
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**Weekly:**
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- Product release notes
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- News mentions
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**Monthly:**
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- Win/loss analysis review
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- Positioning map updates
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**Quarterly:**
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- Deep competitive review
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- Strategy adjustment
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**Annually:**
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- Major strategy reassessment
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- Market trends analysis
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## Additional Resources
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### Reference Files
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- **`references/frameworks-deep-dive.md`** - Detailed application of each framework with worksheets
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- **`references/intel-sources.md`** - Comprehensive list of competitive intelligence sources
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### Example Files
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- **`examples/competitor-analysis.md`** - Complete competitive analysis for a SaaS startup
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- **`examples/positioning-workshop.md`** - Step-by-step positioning development process
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## Quick Start
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To analyze competitive landscape:
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1. **Identify competitors** - Direct, indirect, and future threats
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2. **Apply Porter's Five Forces** - Assess industry attractiveness
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3. **Create positioning map** - Visualize competitive space
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4. **Profile top 3-5 competitors** - Deep dive on key rivals
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5. **Identify differentiation** - What makes you unique
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6. **Analyze pricing** - Where do you fit?
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7. **Assess advantages** - What's defensible?
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8. **Develop strategy** - How to win
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For detailed frameworks and examples, see `references/` and `examples/`.
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@@ -0,0 +1,404 @@
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---
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name: market-sizing-analysis
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description: This skill should be used when the user asks to "calculate TAM", "determine SAM", "estimate SOM", "size the market", "calculate market opportunity", "what's the total addressable market", or requests market sizing analysis for a startup or business opportunity.
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||||
version: 1.0.0
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---
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# Market Sizing Analysis
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Comprehensive market sizing methodologies for calculating Total Addressable Market (TAM), Serviceable Available Market (SAM), and Serviceable Obtainable Market (SOM) for startup opportunities.
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## Overview
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Market sizing provides the foundation for startup strategy, fundraising, and business planning. Calculate market opportunity using three complementary methodologies: top-down (industry reports), bottom-up (customer segment calculations), and value theory (willingness to pay).
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## Core Concepts
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### The Three-Tier Market Framework
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**TAM (Total Addressable Market)**
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- Total revenue opportunity if achieving 100% market share
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- Defines the universe of potential customers
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- Used for long-term vision and market validation
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- Example: All email marketing software revenue globally
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**SAM (Serviceable Available Market)**
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- Portion of TAM targetable with current product/service
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- Accounts for geographic, segment, or capability constraints
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- Represents realistic addressable opportunity
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- Example: AI-powered email marketing for e-commerce in North America
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**SOM (Serviceable Obtainable Market)**
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- Realistic market share achievable in 3-5 years
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- Accounts for competition, resources, and market dynamics
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- Used for financial projections and fundraising
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- Example: 2-5% of SAM based on competitive landscape
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### When to Use Each Methodology
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**Top-Down Analysis**
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- Use when established market research exists
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- Best for mature, well-defined markets
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- Validates market existence and growth
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- Starts with industry reports and narrows down
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**Bottom-Up Analysis**
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- Use when targeting specific customer segments
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- Best for new or niche markets
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- Most credible for investors
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- Builds from customer data and pricing
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**Value Theory**
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- Use when creating new market categories
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- Best for disruptive innovations
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- Estimates based on value creation
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- Calculates willingness to pay for problem solution
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## Three-Methodology Framework
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### Methodology 1: Top-Down Analysis
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Start with total market size and narrow to addressable segments.
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**Process:**
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1. Identify total market category from research reports
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2. Apply geographic filters (target regions)
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3. Apply segment filters (target industries/customers)
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4. Calculate competitive positioning adjustments
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**Formula:**
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```
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TAM = Total Market Category Size
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SAM = TAM × Geographic % × Segment %
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SOM = SAM × Realistic Capture Rate (2-5%)
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```
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**When to use:** Established markets with available research (e.g., SaaS, fintech, e-commerce)
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**Strengths:** Quick, uses credible data, validates market existence
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**Limitations:** May overestimate for new categories, less granular
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### Methodology 2: Bottom-Up Analysis
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Build market size from customer segment calculations.
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**Process:**
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1. Define target customer segments
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2. Estimate number of potential customers per segment
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3. Determine average revenue per customer
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4. Calculate realistic penetration rates
|
||||
|
||||
**Formula:**
|
||||
```
|
||||
TAM = Σ (Segment Size × Annual Revenue per Customer)
|
||||
SAM = TAM × (Segments You Can Serve / Total Segments)
|
||||
SOM = SAM × Realistic Penetration Rate (Year 3-5)
|
||||
```
|
||||
|
||||
**When to use:** B2B, niche markets, specific customer segments
|
||||
|
||||
**Strengths:** Most credible for investors, granular, defensible
|
||||
|
||||
**Limitations:** Requires detailed customer research, time-intensive
|
||||
|
||||
### Methodology 3: Value Theory
|
||||
|
||||
Calculate based on value created and willingness to pay.
|
||||
|
||||
**Process:**
|
||||
1. Identify problem being solved
|
||||
2. Quantify current cost of problem (time, money, inefficiency)
|
||||
3. Calculate value of solution (savings, gains, efficiency)
|
||||
4. Estimate willingness to pay (typically 10-30% of value)
|
||||
5. Multiply by addressable customer base
|
||||
|
||||
**Formula:**
|
||||
```
|
||||
Value per Customer = Problem Cost × % Solved by Solution
|
||||
Price per Customer = Value × Willingness to Pay % (10-30%)
|
||||
TAM = Total Potential Customers × Price per Customer
|
||||
SAM = TAM × % Meeting Buy Criteria
|
||||
SOM = SAM × Realistic Adoption Rate
|
||||
```
|
||||
|
||||
**When to use:** New categories, disruptive innovations, unclear existing markets
|
||||
|
||||
**Strengths:** Shows value creation, works for new markets
|
||||
|
||||
**Limitations:** Requires assumptions, harder to validate
|
||||
|
||||
## Step-by-Step Process
|
||||
|
||||
### Step 1: Define the Market
|
||||
|
||||
Clearly specify what market is being measured.
|
||||
|
||||
**Questions to answer:**
|
||||
- What problem is being solved?
|
||||
- Who are the target customers?
|
||||
- What's the product/service category?
|
||||
- What's the geographic scope?
|
||||
- What's the time horizon?
|
||||
|
||||
**Example:**
|
||||
- Problem: E-commerce companies struggle with email marketing automation
|
||||
- Customers: E-commerce stores with >$1M annual revenue
|
||||
- Category: AI-powered email marketing software
|
||||
- Geography: North America initially, global expansion
|
||||
- Horizon: 3-5 year opportunity
|
||||
|
||||
### Step 2: Gather Data Sources
|
||||
|
||||
Identify credible data for calculations.
|
||||
|
||||
**Top-Down Sources:**
|
||||
- Industry research reports (Gartner, Forrester, IDC)
|
||||
- Government statistics (Census, BLS, trade associations)
|
||||
- Public company filings and earnings
|
||||
- Market research firms (Statista, CB Insights, PitchBook)
|
||||
|
||||
**Bottom-Up Sources:**
|
||||
- Customer interviews and surveys
|
||||
- Sales data and CRM records
|
||||
- Industry databases (LinkedIn, ZoomInfo, Crunchbase)
|
||||
- Competitive intelligence
|
||||
- Academic research
|
||||
|
||||
**Value Theory Sources:**
|
||||
- Customer problem quantification
|
||||
- Time/cost studies
|
||||
- ROI case studies
|
||||
- Pricing research and willingness-to-pay surveys
|
||||
|
||||
### Step 3: Calculate TAM
|
||||
|
||||
Apply chosen methodology to determine total market.
|
||||
|
||||
**For Top-Down:**
|
||||
1. Find total category size from research
|
||||
2. Document data source and year
|
||||
3. Apply growth rate if needed
|
||||
4. Validate with multiple sources
|
||||
|
||||
**For Bottom-Up:**
|
||||
1. Count total potential customers
|
||||
2. Calculate average annual revenue per customer
|
||||
3. Multiply to get TAM
|
||||
4. Break down by segment
|
||||
|
||||
**For Value Theory:**
|
||||
1. Quantify total addressable customer base
|
||||
2. Calculate value per customer
|
||||
3. Estimate pricing based on value
|
||||
4. Multiply for TAM
|
||||
|
||||
### Step 4: Calculate SAM
|
||||
|
||||
Narrow TAM to serviceable addressable market.
|
||||
|
||||
**Apply Filters:**
|
||||
- Geographic constraints (regions you can serve)
|
||||
- Product limitations (features you currently have)
|
||||
- Customer requirements (size, industry, use case)
|
||||
- Distribution channel access
|
||||
- Regulatory or compliance restrictions
|
||||
|
||||
**Formula:**
|
||||
```
|
||||
SAM = TAM × (% matching all filters)
|
||||
```
|
||||
|
||||
**Example:**
|
||||
- TAM: $10B global email marketing
|
||||
- Geographic filter: 40% (North America)
|
||||
- Product filter: 30% (e-commerce focus)
|
||||
- Feature filter: 60% (need AI capabilities)
|
||||
- SAM = $10B × 0.40 × 0.30 × 0.60 = $720M
|
||||
|
||||
### Step 5: Calculate SOM
|
||||
|
||||
Determine realistic obtainable market share.
|
||||
|
||||
**Consider:**
|
||||
- Current market share of competitors
|
||||
- Typical market share for new entrants (2-5%)
|
||||
- Resources available (funding, team, time)
|
||||
- Go-to-market effectiveness
|
||||
- Competitive advantages
|
||||
- Time to achieve (3-5 years typically)
|
||||
|
||||
**Conservative Approach:**
|
||||
```
|
||||
SOM (Year 3) = SAM × 2%
|
||||
SOM (Year 5) = SAM × 5%
|
||||
```
|
||||
|
||||
**Example:**
|
||||
- SAM: $720M
|
||||
- Year 3 SOM: $720M × 2% = $14.4M
|
||||
- Year 5 SOM: $720M × 5% = $36M
|
||||
|
||||
### Step 6: Validate and Triangulate
|
||||
|
||||
Cross-check using multiple methods.
|
||||
|
||||
**Validation Techniques:**
|
||||
1. Compare top-down and bottom-up results (should be within 30%)
|
||||
2. Check against public company revenues in space
|
||||
3. Validate customer count assumptions
|
||||
4. Sense-check pricing assumptions
|
||||
5. Review with industry experts
|
||||
6. Compare to similar market categories
|
||||
|
||||
**Red Flags:**
|
||||
- TAM that's too small (< $1B for VC-backed startups)
|
||||
- TAM that's too large (unsupported by data)
|
||||
- SOM that's too aggressive (> 10% in 5 years for new entrant)
|
||||
- Inconsistency between methodologies (> 50% difference)
|
||||
|
||||
## Industry-Specific Considerations
|
||||
|
||||
### SaaS Markets
|
||||
|
||||
**Key Metrics:**
|
||||
- Number of potential businesses in target segment
|
||||
- Average contract value (ACV)
|
||||
- Typical market penetration rates
|
||||
- Expansion revenue potential
|
||||
|
||||
**TAM Calculation:**
|
||||
```
|
||||
TAM = Total Target Companies × Average ACV × (1 + Expansion Rate)
|
||||
```
|
||||
|
||||
### Marketplace Markets
|
||||
|
||||
**Key Metrics:**
|
||||
- Gross Merchandise Value (GMV) of category
|
||||
- Take rate (% of GMV you capture)
|
||||
- Total transactions or users
|
||||
|
||||
**TAM Calculation:**
|
||||
```
|
||||
TAM = Total Category GMV × Expected Take Rate
|
||||
```
|
||||
|
||||
### Consumer Markets
|
||||
|
||||
**Key Metrics:**
|
||||
- Total addressable users/households
|
||||
- Average revenue per user (ARPU)
|
||||
- Engagement frequency
|
||||
|
||||
**TAM Calculation:**
|
||||
```
|
||||
TAM = Total Users × ARPU × Purchase Frequency per Year
|
||||
```
|
||||
|
||||
### B2B Services
|
||||
|
||||
**Key Metrics:**
|
||||
- Number of target companies by size/industry
|
||||
- Average project value or retainer
|
||||
- Typical buying frequency
|
||||
|
||||
**TAM Calculation:**
|
||||
```
|
||||
TAM = Total Target Companies × Average Deal Size × Deals per Year
|
||||
```
|
||||
|
||||
## Presenting Market Sizing
|
||||
|
||||
### For Investors
|
||||
|
||||
**Structure:**
|
||||
1. Market definition and problem scope
|
||||
2. TAM/SAM/SOM with methodology
|
||||
3. Data sources and assumptions
|
||||
4. Growth projections and drivers
|
||||
5. Competitive landscape context
|
||||
|
||||
**Key Points:**
|
||||
- Lead with bottom-up calculation (most credible)
|
||||
- Show triangulation with top-down
|
||||
- Explain conservative assumptions
|
||||
- Link to revenue projections
|
||||
- Highlight market growth rate
|
||||
|
||||
### For Strategy
|
||||
|
||||
**Structure:**
|
||||
1. Addressable customer segments
|
||||
2. Prioritization by opportunity size
|
||||
3. Entry strategy by segment
|
||||
4. Expected penetration timeline
|
||||
5. Resource requirements
|
||||
|
||||
**Key Points:**
|
||||
- Focus on SAM and SOM
|
||||
- Show segment-level detail
|
||||
- Connect to go-to-market plan
|
||||
- Identify expansion opportunities
|
||||
- Discuss competitive positioning
|
||||
|
||||
## Common Mistakes to Avoid
|
||||
|
||||
**Mistake 1: Confusing TAM with SAM**
|
||||
- Don't claim entire market as addressable
|
||||
- Apply realistic product/geographic constraints
|
||||
- Be honest about serviceable market
|
||||
|
||||
**Mistake 2: Overly Aggressive SOM**
|
||||
- New entrants rarely capture > 5% in 5 years
|
||||
- Account for competition and resources
|
||||
- Show realistic ramp timeline
|
||||
|
||||
**Mistake 3: Using Only Top-Down**
|
||||
- Investors prefer bottom-up validation
|
||||
- Top-down alone lacks credibility
|
||||
- Always triangulate with multiple methods
|
||||
|
||||
**Mistake 4: Cherry-Picking Data**
|
||||
- Use consistent, recent data sources
|
||||
- Don't mix methodologies inappropriately
|
||||
- Document all assumptions clearly
|
||||
|
||||
**Mistake 5: Ignoring Market Dynamics**
|
||||
- Account for market growth/decline
|
||||
- Consider competitive intensity
|
||||
- Factor in switching costs and barriers
|
||||
|
||||
## Additional Resources
|
||||
|
||||
### Reference Files
|
||||
|
||||
For detailed methodologies and frameworks:
|
||||
- **`references/methodology-deep-dive.md`** - Comprehensive guide to each methodology with step-by-step worksheets
|
||||
- **`references/data-sources.md`** - Curated list of market research sources, databases, and tools
|
||||
- **`references/industry-templates.md`** - Specific templates for SaaS, marketplace, consumer, B2B, and fintech markets
|
||||
|
||||
### Example Files
|
||||
|
||||
Working examples with complete calculations:
|
||||
- **`examples/saas-market-sizing.md`** - Complete TAM/SAM/SOM for a B2B SaaS product
|
||||
- **`examples/marketplace-sizing.md`** - Marketplace platform market opportunity calculation
|
||||
- **`examples/value-theory-example.md`** - Value-based market sizing for disruptive innovation
|
||||
|
||||
Use these examples as templates for your own market sizing analysis. Each includes real numbers, data sources, and assumptions documented clearly.
|
||||
|
||||
## Quick Start
|
||||
|
||||
To perform market sizing analysis:
|
||||
|
||||
1. **Define the market** - Problem, customers, category, geography
|
||||
2. **Choose methodology** - Bottom-up (preferred) or top-down + triangulation
|
||||
3. **Gather data** - Industry reports, customer data, competitive intelligence
|
||||
4. **Calculate TAM** - Apply methodology formula
|
||||
5. **Narrow to SAM** - Apply product, geographic, segment filters
|
||||
6. **Estimate SOM** - 2-5% realistic capture rate
|
||||
7. **Validate** - Cross-check with alternative methods
|
||||
8. **Document** - Show methodology, sources, assumptions
|
||||
9. **Present** - Structure for audience (investors, strategy, operations)
|
||||
|
||||
For detailed step-by-step guidance on each methodology, reference the files in `references/` directory. For complete worked examples, see `examples/` directory.
|
||||
@@ -0,0 +1,349 @@
|
||||
# SaaS Market Sizing Example: AI-Powered Email Marketing for E-Commerce
|
||||
|
||||
Complete TAM/SAM/SOM calculation for a B2B SaaS startup using bottom-up and top-down methodologies.
|
||||
|
||||
## Company Overview
|
||||
|
||||
**Product:** AI-powered email marketing automation platform
|
||||
**Target:** E-commerce companies with $1M+ annual revenue
|
||||
**Geography:** North America (initial), global expansion planned
|
||||
**Pricing:** $500/month average (scales by email volume)
|
||||
**Timeline:** 3-5 year market opportunity
|
||||
|
||||
## Methodology 1: Bottom-Up Analysis (Primary)
|
||||
|
||||
### Step 1: Define Target Customer Segments
|
||||
|
||||
**Segment Criteria:**
|
||||
- E-commerce companies (D2C and marketplace sellers)
|
||||
- $1M+ in annual revenue
|
||||
- North America based
|
||||
- Currently using email marketing
|
||||
|
||||
**Segment Breakdown:**
|
||||
|
||||
| Segment | Annual Revenue | Count | ACV | Priority |
|
||||
|---------|---------------|-------|-----|----------|
|
||||
| Small E-commerce | $1M-$5M | 85,000 | $3,600 | High |
|
||||
| Mid-Market E-commerce | $5M-$50M | 18,000 | $9,600 | High |
|
||||
| Enterprise E-commerce | $50M+ | 2,500 | $24,000 | Medium |
|
||||
|
||||
**Data Sources:**
|
||||
- U.S. Census Bureau: E-commerce business counts
|
||||
- Shopify, BigCommerce, WooCommerce: Published merchant counts
|
||||
- Statista: E-commerce market statistics
|
||||
- LinkedIn Sales Navigator: Company search validation
|
||||
|
||||
### Step 2: Calculate TAM (Total Addressable Market)
|
||||
|
||||
**Formula:**
|
||||
```
|
||||
TAM = Σ (Segment Count × Annual Contract Value)
|
||||
```
|
||||
|
||||
**Calculation:**
|
||||
```
|
||||
Small E-commerce: 85,000 × $3,600 = $306M
|
||||
Mid-Market: 18,000 × $9,600 = $173M
|
||||
Enterprise: 2,500 × $24,000 = $60M
|
||||
--------
|
||||
TAM (North America): $539M
|
||||
```
|
||||
|
||||
**Global Expansion Multiplier:**
|
||||
- North America = 35% of global e-commerce market
|
||||
- Global TAM = $539M / 0.35 = $1.54B
|
||||
|
||||
**TAM = $1.54B globally, $539M North America**
|
||||
|
||||
### Step 3: Calculate SAM (Serviceable Available Market)
|
||||
|
||||
**Filters Applied:**
|
||||
|
||||
1. **Geographic Filter: North America Only (Year 1-2)**
|
||||
- Base TAM: $539M
|
||||
- Filter: 100% (starting in North America)
|
||||
- Result: $539M
|
||||
|
||||
2. **Product Capability Filter: AI-Ready Customers**
|
||||
- Customers ready to adopt AI email marketing
|
||||
- Excludes: Companies with basic email needs only
|
||||
- Filter: 45% (based on survey data)
|
||||
- Result: $539M × 0.45 = $242M
|
||||
|
||||
3. **Current Tool Filter: Addressable Switching Market**
|
||||
- Customers using incumbent tools who would switch
|
||||
- Excludes: Recently switched, custom built solutions
|
||||
- Filter: 70% (typical B2B SaaS switching market)
|
||||
- Result: $242M × 0.70 = $169M
|
||||
|
||||
**SAM = $169M**
|
||||
|
||||
**SAM Breakdown by Segment:**
|
||||
```
|
||||
Small E-commerce: $306M × 0.45 × 0.70 = $96M (57%)
|
||||
Mid-Market: $173M × 0.45 × 0.70 = $54M (32%)
|
||||
Enterprise: $60M × 0.45 × 0.70 = $19M (11%)
|
||||
```
|
||||
|
||||
### Step 4: Calculate SOM (Serviceable Obtainable Market)
|
||||
|
||||
**Market Share Assumptions:**
|
||||
|
||||
**Year 3 Target: 2.5% of SAM**
|
||||
- Typical new entrant market share
|
||||
- Requires strong product-market fit
|
||||
- Assumes $10M in funding for GTM
|
||||
|
||||
**Year 5 Target: 5% of SAM**
|
||||
- Achievable with scale and brand
|
||||
- Requires effective sales and marketing
|
||||
- Assumes additional funding for growth
|
||||
|
||||
**Calculation:**
|
||||
```
|
||||
SOM (Year 3) = $169M × 2.5% = $4.2M ARR
|
||||
SOM (Year 5) = $169M × 5.0% = $8.5M ARR
|
||||
```
|
||||
|
||||
**SOM by Segment (Year 5):**
|
||||
```
|
||||
Small E-commerce: $96M × 5% = $4.8M ARR (565 customers)
|
||||
Mid-Market: $54M × 5% = $2.7M ARR (281 customers)
|
||||
Enterprise: $19M × 5% = $1.0M ARR (42 customers)
|
||||
--------
|
||||
Total: $8.5M ARR (888 customers)
|
||||
```
|
||||
|
||||
### Bottom-Up Summary
|
||||
|
||||
| Metric | North America | Notes |
|
||||
|--------|---------------|-------|
|
||||
| **TAM** | $539M | All e-commerce $1M+ revenue |
|
||||
| **SAM** | $169M | AI-ready, addressable switching market |
|
||||
| **SOM (Year 3)** | $4.2M | 2.5% market share, 495 customers |
|
||||
| **SOM (Year 5)** | $8.5M | 5% market share, 888 customers |
|
||||
|
||||
## Methodology 2: Top-Down Analysis (Validation)
|
||||
|
||||
### Step 1: Identify Total Market Category
|
||||
|
||||
**Market Category:** Email Marketing Software
|
||||
**Source:** Gartner Market Share Report (2024)
|
||||
|
||||
**Global Email Marketing Software Market:**
|
||||
- Market Size: $7.5B (2024)
|
||||
- Growth Rate: 12% CAGR
|
||||
- Geography: Worldwide
|
||||
|
||||
**Data Source:** Gartner, "Market Share: Email Marketing Software, Worldwide, 2024"
|
||||
|
||||
### Step 2: Apply Geographic Filter
|
||||
|
||||
**North America Market Share:**
|
||||
- North America = 40% of global software spending
|
||||
- Email Marketing NA = $7.5B × 0.40 = $3.0B
|
||||
|
||||
### Step 3: Apply Segment Filters
|
||||
|
||||
**E-Commerce Focus:**
|
||||
- E-commerce email marketing = 25% of total email marketing
|
||||
- E-commerce segment = $3.0B × 0.25 = $750M
|
||||
|
||||
**$1M+ Revenue Filter:**
|
||||
- Companies with $1M+ revenue = 65% of e-commerce market
|
||||
- TAM = $750M × 0.65 = $488M
|
||||
|
||||
**AI-Powered Subset:**
|
||||
- AI-powered email marketing = 35% of market (growing rapidly)
|
||||
- SAM = $488M × 0.35 = $171M
|
||||
|
||||
### Top-Down Summary
|
||||
|
||||
| Metric | Amount | Calculation |
|
||||
|--------|--------|-------------|
|
||||
| **TAM** | $488M | NA e-commerce email marketing $1M+ |
|
||||
| **SAM** | $171M | AI-powered subset |
|
||||
|
||||
## Triangulation and Validation
|
||||
|
||||
### Comparing Methodologies
|
||||
|
||||
| Metric | Bottom-Up | Top-Down | Variance |
|
||||
|--------|-----------|----------|----------|
|
||||
| **TAM** | $539M | $488M | +10% |
|
||||
| **SAM** | $169M | $171M | -1% |
|
||||
|
||||
**Validation Result:** ✅ Excellent alignment (< 2% variance on SAM)
|
||||
|
||||
**Why alignment matters:**
|
||||
- Bottom-up and top-down within 10% gives high confidence
|
||||
- SAM alignment of 1% is exceptional
|
||||
- Use bottom-up as primary (more granular)
|
||||
- Reference top-down for validation
|
||||
|
||||
### Public Company Validation
|
||||
|
||||
**Klaviyo (Public, KVYO):**
|
||||
- 2024 Revenue: ~$700M
|
||||
- Focus: E-commerce email/SMS marketing
|
||||
- Market Share: ~46% of our SAM
|
||||
- Validates large e-commerce email market exists
|
||||
|
||||
**Mailchimp (Intuit-owned):**
|
||||
- 2024 Revenue: ~$800M (estimated)
|
||||
- Broader focus, includes SMBs
|
||||
- Significant e-commerce customer base
|
||||
|
||||
**Validation:** Market leaders have $700M-$800M revenue, supporting $1.5B+ global TAM
|
||||
|
||||
### Sanity Checks
|
||||
|
||||
**Customer Count Check:**
|
||||
✅ 888 customers at Year 5 (5% market share) = reasonable
|
||||
✅ Implies ~14,000 total addressable customers
|
||||
✅ Aligns with estimated 105,000 e-commerce cos $1M+ in NA
|
||||
|
||||
**Average Revenue Check:**
|
||||
✅ $8.5M ARR / 888 customers = $9,571 ACV
|
||||
✅ Within expected range of $3.6K-$24K by segment
|
||||
✅ Weighted average makes sense given segment mix
|
||||
|
||||
**Market Share Check:**
|
||||
✅ 5% market share in Year 5 is achievable for well-funded startup
|
||||
✅ Lower than Klaviyo (46%), appropriate for new entrant
|
||||
✅ Room for growth beyond Year 5
|
||||
|
||||
## Growth Projections
|
||||
|
||||
### Market Growth Assumptions
|
||||
|
||||
**Email Marketing Market CAGR: 12%**
|
||||
- Source: Gartner market forecast
|
||||
- Drivers: E-commerce growth, marketing automation adoption
|
||||
|
||||
**AI Subset Growth: 25% CAGR**
|
||||
- Higher than overall market
|
||||
- AI adoption accelerating in marketing
|
||||
- More companies seeking AI-powered tools
|
||||
|
||||
### SAM Evolution (5-Year Forecast)
|
||||
|
||||
| Year | SAM | Growth | Notes |
|
||||
|------|-----|--------|-------|
|
||||
| 2026 | $169M | - | Starting point |
|
||||
| 2027 | $211M | +25% | AI adoption accelerating |
|
||||
| 2028 | $264M | +25% | Mainstream adoption begins |
|
||||
| 2029 | $330M | +25% | AI becomes table stakes |
|
||||
| 2030 | $413M | +25% | Market maturity |
|
||||
|
||||
**Growing SAM Impact:**
|
||||
- Year 5 SOM of 5% applied to $413M SAM = $20.6M potential
|
||||
- Provides headroom for growth
|
||||
- Supports expansion beyond initial 5% share
|
||||
|
||||
## Competitive Context
|
||||
|
||||
### Market Share Distribution
|
||||
|
||||
**Current Leaders:**
|
||||
- Klaviyo: ~46% share
|
||||
- Mailchimp: ~35% share
|
||||
- Others: ~19% share (fragmented)
|
||||
|
||||
**Market Dynamics:**
|
||||
- Two dominant players
|
||||
- Long tail of smaller competitors
|
||||
- Opportunity in AI-differentiated positioning
|
||||
- Typical SaaS market consolidation pattern
|
||||
|
||||
**Implications for SOM:**
|
||||
- 5% share requires strong differentiation
|
||||
- AI capabilities could drive 10-15% share long-term
|
||||
- Acquisition potential if unable to reach scale
|
||||
|
||||
## Investment Thesis Validation
|
||||
|
||||
### Market Opportunity Score: ✅ Strong
|
||||
|
||||
**Positives:**
|
||||
✅ Large market: $1.5B+ global TAM
|
||||
✅ Growing market: 12% CAGR, 25% for AI subset
|
||||
✅ Addressable: $169M SAM with clear path to customers
|
||||
✅ Achievable: $8.5M Year 5 ARR reasonable
|
||||
✅ Validation: Public companies prove market exists
|
||||
|
||||
**Risks:**
|
||||
⚠️ Competition: Klaviyo and Mailchimp are strong
|
||||
⚠️ Switching costs: Customers invested in current tools
|
||||
⚠️ Market share: 5% requires excellent execution
|
||||
|
||||
**Verdict:** Market opportunity supports venture-scale outcome ($100M+ exit possible)
|
||||
|
||||
## Presentation to Investors
|
||||
|
||||
### Slide 1: Market Opportunity Summary
|
||||
|
||||
```
|
||||
AI-Powered Email Marketing for E-Commerce
|
||||
|
||||
TAM: $1.5B Global, $539M North America
|
||||
SAM: $169M (AI-ready e-commerce companies)
|
||||
SOM: $8.5M ARR by Year 5 (5% market share)
|
||||
|
||||
Market Growing 25% CAGR (AI subset)
|
||||
Validated by Klaviyo ($700M revenue)
|
||||
```
|
||||
|
||||
### Slide 2: Bottom-Up Validation
|
||||
|
||||
```
|
||||
Target: 105,000 E-Commerce Companies ($1M+ revenue)
|
||||
|
||||
Segment Breakdown:
|
||||
• Small ($1M-$5M): 85,000 companies × $3,600 ACV
|
||||
• Mid-Market ($5M-$50M): 18,000 × $9,600
|
||||
• Enterprise ($50M+): 2,500 × $24,000
|
||||
|
||||
Year 5: 888 customers, $8.5M ARR (5% market share)
|
||||
```
|
||||
|
||||
### Slide 3: Market Validation
|
||||
|
||||
```
|
||||
Top-Down: $171M SAM (Gartner + market filters)
|
||||
Bottom-Up: $169M SAM (<2% variance)
|
||||
|
||||
Public Company Validation:
|
||||
• Klaviyo: $700M revenue (46% market share)
|
||||
• Mailchimp: $800M revenue (Intuit-owned)
|
||||
|
||||
Demonstrates large, proven market
|
||||
```
|
||||
|
||||
## Key Takeaways
|
||||
|
||||
**Market Sizing Results:**
|
||||
- TAM: $1.5B globally, $539M North America
|
||||
- SAM: $169M (North America, AI-ready customers)
|
||||
- SOM: $4.2M (Year 3), $8.5M (Year 5)
|
||||
|
||||
**Methodology:**
|
||||
- Bottom-up primary (most granular and credible)
|
||||
- Top-down validation (<2% variance on SAM)
|
||||
- Public company validation (Klaviyo, Mailchimp)
|
||||
|
||||
**Investment Implications:**
|
||||
- Market supports venture-scale outcome
|
||||
- 5% market share achievable with strong execution
|
||||
- Growing market (25% CAGR) provides tailwinds
|
||||
- Competitive but differentiated positioning possible
|
||||
|
||||
**Next Steps:**
|
||||
1. Validate pricing assumptions with customer research
|
||||
2. Refine segment prioritization based on GTM capacity
|
||||
3. Update SAM annually as market evolves
|
||||
4. Track Klaviyo/Mailchimp as competitive benchmarks
|
||||
5. Monitor AI adoption rates in e-commerce segment
|
||||
|
||||
This bottom-up market sizing provides a defensible, data-driven foundation for business planning and fundraising.
|
||||
@@ -0,0 +1,360 @@
|
||||
# Market Sizing Data Sources
|
||||
|
||||
Curated list of credible sources for market research and sizing analysis.
|
||||
|
||||
## Industry Research Reports
|
||||
|
||||
### Premium Research Firms
|
||||
|
||||
**Gartner** (https://www.gartner.com)
|
||||
- Technology market forecasts and sizing
|
||||
- Magic Quadrants for competitive positioning
|
||||
- Typical cost: $5K-$50K per report
|
||||
- Best for: Enterprise software, IT services, emerging tech
|
||||
|
||||
**Forrester** (https://www.forrester.com)
|
||||
- Business technology and digital transformation
|
||||
- Wave evaluations for vendor comparison
|
||||
- Typical cost: $3K-$30K per report
|
||||
- Best for: Marketing tech, customer experience, B2B
|
||||
|
||||
**IDC** (https://www.idc.com)
|
||||
- IT market intelligence and sizing
|
||||
- Detailed segment breakdowns
|
||||
- Typical cost: $4K-$40K per report
|
||||
- Best for: Hardware, software, IT services
|
||||
|
||||
**McKinsey** (https://www.mckinsey.com/featured-insights)
|
||||
- Free insights and reports
|
||||
- Strategic industry analysis
|
||||
- Best for: Industry trends, macroeconomic context
|
||||
|
||||
### Accessible Research
|
||||
|
||||
**Statista** (https://www.statista.com)
|
||||
- Cost: $39/month individual, $199/month business
|
||||
- Coverage: 80,000+ topics across industries
|
||||
- Best for: Quick market size estimates, charts, trends
|
||||
|
||||
**CB Insights** (https://www.cbinsights.com)
|
||||
- Cost: Custom pricing (typically $10K+/year)
|
||||
- Coverage: Venture capital, startup markets
|
||||
- Best for: Emerging markets, competitive intelligence
|
||||
|
||||
**PitchBook** (https://pitchbook.com)
|
||||
- Cost: Institutional pricing
|
||||
- Coverage: Private company valuations, M&A, VC
|
||||
- Best for: Startup valuations, funding trends
|
||||
|
||||
**Grand View Research** (https://www.grandviewresearch.com)
|
||||
- Cost: $2K-$5K per report
|
||||
- Coverage: B2C and emerging markets
|
||||
- Best for: Consumer markets, healthcare, cleantech
|
||||
|
||||
## Government and Public Data
|
||||
|
||||
### U.S. Government Sources
|
||||
|
||||
**U.S. Census Bureau** (https://www.census.gov)
|
||||
- Free, authoritative demographic data
|
||||
- Economic census every 5 years
|
||||
- Best for: Business counts, demographics, spending
|
||||
|
||||
**Bureau of Labor Statistics** (https://www.bls.gov)
|
||||
- Free employment and economic data
|
||||
- Industry-specific statistics
|
||||
- Best for: Employment trends, wages, productivity
|
||||
|
||||
**SEC EDGAR** (https://www.sec.gov/edgar)
|
||||
- Free public company filings
|
||||
- 10-K, 10-Q reports with segment revenue
|
||||
- Best for: Validating market size with public company data
|
||||
|
||||
**Data.gov** (https://www.data.gov)
|
||||
- Free government datasets
|
||||
- Aggregates across agencies
|
||||
- Best for: Specialized industry data
|
||||
|
||||
### International Sources
|
||||
|
||||
**OECD** (https://data.oecd.org)
|
||||
- Free international economic data
|
||||
- Best for: Cross-country comparisons
|
||||
|
||||
**World Bank** (https://data.worldbank.org)
|
||||
- Free global development data
|
||||
- Best for: Emerging markets, macro trends
|
||||
|
||||
**Eurostat** (https://ec.europa.eu/eurostat)
|
||||
- Free European Union statistics
|
||||
- Best for: European market sizing
|
||||
|
||||
## Trade Associations
|
||||
|
||||
Industry associations often publish market research:
|
||||
|
||||
**Software & SaaS**
|
||||
- Software & Information Industry Association (SIIA)
|
||||
- Cloud Security Alliance (CSA)
|
||||
|
||||
**E-commerce & Retail**
|
||||
- National Retail Federation (NRF)
|
||||
- Digital Commerce 360
|
||||
|
||||
**Financial Services**
|
||||
- American Bankers Association (ABA)
|
||||
- Financial Technology Association (FTA)
|
||||
|
||||
**Healthcare**
|
||||
- Healthcare Information and Management Systems Society (HIMSS)
|
||||
- American Hospital Association (AHA)
|
||||
|
||||
**Manufacturing**
|
||||
- National Association of Manufacturers (NAM)
|
||||
- Industrial Internet Consortium (IIC)
|
||||
|
||||
## Company and Customer Data
|
||||
|
||||
### B2B Databases
|
||||
|
||||
**LinkedIn Sales Navigator** ($99/month)
|
||||
- Company and employee counts
|
||||
- Industry filters
|
||||
- Best for: B2B customer counting
|
||||
|
||||
**ZoomInfo** (Custom pricing)
|
||||
- Company databases with firmographics
|
||||
- Contact data
|
||||
- Best for: B2B TAM calculations
|
||||
|
||||
**Crunchbase** ($29-$99/month)
|
||||
- Startup company data
|
||||
- Funding and employee information
|
||||
- Best for: Tech startup markets
|
||||
|
||||
**BuiltWith** ($295-$995/month)
|
||||
- Technology usage data
|
||||
- Website analytics
|
||||
- Best for: Technology adoption sizing
|
||||
|
||||
### Consumer Data
|
||||
|
||||
**Euromonitor** (Custom pricing)
|
||||
- Consumer market research
|
||||
- Best for: B2C product markets
|
||||
|
||||
**Nielsen** (Custom pricing)
|
||||
- Consumer behavior and media
|
||||
- Best for: CPG, retail, media markets
|
||||
|
||||
**Mintel** (Custom pricing)
|
||||
- Consumer trends and insights
|
||||
- Best for: B2C products and services
|
||||
|
||||
## Search and Discovery Tools
|
||||
|
||||
### Market Research Aggregators
|
||||
|
||||
**Research and Markets** (https://www.researchandmarkets.com)
|
||||
- Aggregates reports from 100+ publishers
|
||||
- $500-$10K per report
|
||||
- Search across all major research firms
|
||||
|
||||
**MarketsandMarkets** (https://www.marketsandmarkets.com)
|
||||
- Custom and syndicated research
|
||||
- $4K-$10K per report
|
||||
- Good for niche B2B markets
|
||||
|
||||
### Free Search Tools
|
||||
|
||||
**Google Scholar** (https://scholar.google.com)
|
||||
- Free academic research
|
||||
- Best for: Emerging technologies, academic validation
|
||||
|
||||
**SSRN** (https://www.ssrn.com)
|
||||
- Free working papers
|
||||
- Best for: Financial services, economics
|
||||
|
||||
**arXiv** (https://arxiv.org)
|
||||
- Free preprints in CS, physics, etc.
|
||||
- Best for: AI/ML, scientific markets
|
||||
|
||||
## Competitive Intelligence
|
||||
|
||||
### Public Company Analysis
|
||||
|
||||
**Yahoo Finance** (Free)
|
||||
- Public company financials
|
||||
- Segment revenue from earnings
|
||||
|
||||
**Seeking Alpha** (Free + Premium)
|
||||
- Earnings transcripts
|
||||
- Analyst estimates
|
||||
|
||||
**Public company investor relations**
|
||||
- Annual reports (10-K)
|
||||
- Investor presentations
|
||||
|
||||
### Private Company Intelligence
|
||||
|
||||
**PrivCo** (Custom pricing)
|
||||
- Private company financials
|
||||
- M&A transaction data
|
||||
|
||||
**Owler** (Free + Premium)
|
||||
- Company profiles and news
|
||||
- Revenue estimates
|
||||
|
||||
**SimilarWeb** (Free + Premium)
|
||||
- Website traffic analytics
|
||||
- Best for: Online business sizing
|
||||
|
||||
## Survey and Primary Research
|
||||
|
||||
### Survey Tools
|
||||
|
||||
**SurveyMonkey** ($25-$75/month)
|
||||
- DIY surveys
|
||||
- Best for: Customer willingness to pay
|
||||
|
||||
**Typeform** ($25-$83/month)
|
||||
- Conversational surveys
|
||||
- Best for: User research
|
||||
|
||||
**Qualtrics** (Enterprise pricing)
|
||||
- Professional research platform
|
||||
- Best for: Large-scale studies
|
||||
|
||||
### Panel Providers
|
||||
|
||||
**Respondent.io** ($100-$200 per response)
|
||||
- Recruit professionals for interviews
|
||||
- Best for: B2B customer research
|
||||
|
||||
**UserTesting** ($49 per participant)
|
||||
- User research and testing
|
||||
- Best for: Product validation
|
||||
|
||||
**Google Surveys** ($0.10-$3.50 per response)
|
||||
- Quick consumer surveys
|
||||
- Best for: Basic consumer insights
|
||||
|
||||
## Data Quality Checklist
|
||||
|
||||
When evaluating sources:
|
||||
|
||||
**Authority**
|
||||
- [ ] Who published the research?
|
||||
- [ ] What's their reputation?
|
||||
- [ ] Do they have industry expertise?
|
||||
|
||||
**Methodology**
|
||||
- [ ] How was data collected?
|
||||
- [ ] What's the sample size?
|
||||
- [ ] When was research conducted?
|
||||
|
||||
**Recency**
|
||||
- [ ] Is data current (< 2 years old)?
|
||||
- [ ] Has market changed significantly?
|
||||
- [ ] Are growth rates still applicable?
|
||||
|
||||
**Consistency**
|
||||
- [ ] Do multiple sources agree?
|
||||
- [ ] Are definitions consistent?
|
||||
- [ ] Do numbers triangulate?
|
||||
|
||||
**Relevance**
|
||||
- [ ] Does it match your market definition?
|
||||
- [ ] Is geography appropriate?
|
||||
- [ ] Are segments aligned?
|
||||
|
||||
## Free vs. Paid Strategy
|
||||
|
||||
**Start with free sources:**
|
||||
1. Government data for customer counts
|
||||
2. Public company filings for segment revenue
|
||||
3. Trade associations for industry trends
|
||||
4. Google Scholar for academic research
|
||||
|
||||
**Upgrade to paid when:**
|
||||
- Raising institutional funding (investors expect premium sources)
|
||||
- Need detailed segment breakdowns
|
||||
- Market is niche or emerging
|
||||
- Free sources are outdated or insufficient
|
||||
|
||||
**Cost-effective approach:**
|
||||
- Buy 1-2 key reports that cover your core market
|
||||
- Use free sources for triangulation
|
||||
- Supplement with primary research (customer interviews)
|
||||
- Cite mix of free and paid sources
|
||||
|
||||
## Citation Best Practices
|
||||
|
||||
Always cite sources in market sizing:
|
||||
|
||||
**Format:**
|
||||
```
|
||||
Market Size: $X.XB
|
||||
Source: [Publisher], [Report Name], [Date]
|
||||
URL: [link if available]
|
||||
```
|
||||
|
||||
**Example:**
|
||||
```
|
||||
Email Marketing Software TAM: $7.5B (2024)
|
||||
Source: Gartner, "Market Share: Email Marketing Software, Worldwide, 2024"
|
||||
Note: Includes all email marketing software revenue globally
|
||||
```
|
||||
|
||||
**Include:**
|
||||
- Publisher and report name
|
||||
- Publication date
|
||||
- Geography and scope
|
||||
- Any adjustments made
|
||||
- Link to source (if public)
|
||||
|
||||
## Keeping Research Current
|
||||
|
||||
**Set Google Alerts**
|
||||
- Industry keywords
|
||||
- Company names
|
||||
- Market terms
|
||||
|
||||
**Follow Research Firms**
|
||||
- Twitter accounts
|
||||
- LinkedIn updates
|
||||
- Free newsletter summaries
|
||||
|
||||
**Track Public Companies**
|
||||
- Earnings calendars
|
||||
- Investor relations pages
|
||||
- Annual reports
|
||||
|
||||
**Join Industry Groups**
|
||||
- LinkedIn groups
|
||||
- Slack communities
|
||||
- Trade associations
|
||||
|
||||
**Review Annually**
|
||||
- Update market size with new data
|
||||
- Adjust growth assumptions
|
||||
- Revisit methodology if market changed
|
||||
|
||||
## Emergency Research Guide
|
||||
|
||||
**Need market size in < 2 hours?**
|
||||
|
||||
1. **Check Statista** (15 min) - Quick industry overview
|
||||
2. **Find public companies** (30 min) - Get segment revenue from 10-Ks
|
||||
3. **LinkedIn search** (20 min) - Count potential B2B customers
|
||||
4. **Google Scholar** (20 min) - Find academic papers
|
||||
5. **Calculate bottom-up** (30 min) - Customers × Price
|
||||
6. **Triangulate** (15 min) - Compare sources
|
||||
|
||||
**Document everything:**
|
||||
- Write down all sources
|
||||
- Note all assumptions
|
||||
- Show your methodology
|
||||
- Caveat data quality
|
||||
|
||||
Better to have a defensible estimate with clear limitations than no data at all.
|
||||
@@ -0,0 +1,446 @@
|
||||
---
|
||||
name: startup-financial-modeling
|
||||
description: This skill should be used when the user asks to "create financial projections", "build a financial model", "forecast revenue", "calculate burn rate", "estimate runway", "model cash flow", or requests 3-5 year financial planning for a startup.
|
||||
version: 1.0.0
|
||||
---
|
||||
|
||||
# Startup Financial Modeling
|
||||
|
||||
Build comprehensive 3-5 year financial models with revenue projections, cost structures, cash flow analysis, and scenario planning for early-stage startups.
|
||||
|
||||
## Overview
|
||||
|
||||
Financial modeling provides the quantitative foundation for startup strategy, fundraising, and operational planning. Create realistic projections using cohort-based revenue modeling, detailed cost structures, and scenario analysis to support decision-making and investor presentations.
|
||||
|
||||
## Core Components
|
||||
|
||||
### Revenue Model
|
||||
|
||||
**Cohort-Based Projections:**
|
||||
Build revenue from customer acquisition and retention by cohort.
|
||||
|
||||
**Formula:**
|
||||
```
|
||||
MRR = Σ (Cohort Size × Retention Rate × ARPU)
|
||||
ARR = MRR × 12
|
||||
```
|
||||
|
||||
**Key Inputs:**
|
||||
- Monthly new customer acquisitions
|
||||
- Customer retention rates by month
|
||||
- Average revenue per user (ARPU)
|
||||
- Pricing and packaging assumptions
|
||||
- Expansion revenue (upsells, cross-sells)
|
||||
|
||||
### Cost Structure
|
||||
|
||||
**Operating Expenses Categories:**
|
||||
|
||||
1. **Cost of Goods Sold (COGS)**
|
||||
- Hosting and infrastructure
|
||||
- Payment processing fees
|
||||
- Customer support (variable portion)
|
||||
- Third-party services per customer
|
||||
|
||||
2. **Sales & Marketing (S&M)**
|
||||
- Customer acquisition cost (CAC)
|
||||
- Marketing programs and advertising
|
||||
- Sales team compensation
|
||||
- Marketing tools and software
|
||||
|
||||
3. **Research & Development (R&D)**
|
||||
- Engineering team compensation
|
||||
- Product management
|
||||
- Design and UX
|
||||
- Development tools and infrastructure
|
||||
|
||||
4. **General & Administrative (G&A)**
|
||||
- Executive team
|
||||
- Finance, legal, HR
|
||||
- Office and facilities
|
||||
- Insurance and compliance
|
||||
|
||||
### Cash Flow Analysis
|
||||
|
||||
**Components:**
|
||||
- Beginning cash balance
|
||||
- Cash inflows (revenue, fundraising)
|
||||
- Cash outflows (operating expenses, CapEx)
|
||||
- Ending cash balance
|
||||
- Monthly burn rate
|
||||
- Runway (months of cash remaining)
|
||||
|
||||
**Formula:**
|
||||
```
|
||||
Runway = Current Cash Balance / Monthly Burn Rate
|
||||
Monthly Burn = Monthly Revenue - Monthly Expenses
|
||||
```
|
||||
|
||||
### Headcount Planning
|
||||
|
||||
**Role-Based Hiring Plan:**
|
||||
Track headcount by department and role.
|
||||
|
||||
**Key Metrics:**
|
||||
- Fully-loaded cost per employee
|
||||
- Revenue per employee
|
||||
- Headcount by department (% of total)
|
||||
|
||||
**Typical Ratios (Early-Stage SaaS):**
|
||||
- Engineering: 40-50%
|
||||
- Sales & Marketing: 25-35%
|
||||
- G&A: 10-15%
|
||||
- Customer Success: 5-10%
|
||||
|
||||
## Financial Model Structure
|
||||
|
||||
### Three-Scenario Framework
|
||||
|
||||
**Conservative Scenario (P10):**
|
||||
- Slower customer acquisition
|
||||
- Lower pricing or conversion
|
||||
- Higher churn rates
|
||||
- Extended sales cycles
|
||||
- Used for cash management
|
||||
|
||||
**Base Scenario (P50):**
|
||||
- Most likely outcomes
|
||||
- Realistic assumptions
|
||||
- Primary planning scenario
|
||||
- Used for board reporting
|
||||
|
||||
**Optimistic Scenario (P90):**
|
||||
- Faster growth
|
||||
- Better unit economics
|
||||
- Lower churn
|
||||
- Used for upside planning
|
||||
|
||||
### Time Horizon
|
||||
|
||||
**Detailed Projections: 3 Years**
|
||||
- Monthly detail for Year 1
|
||||
- Monthly detail for Year 2
|
||||
- Quarterly detail for Year 3
|
||||
|
||||
**High-Level Projections: Years 4-5**
|
||||
- Annual projections
|
||||
- Key metrics only
|
||||
- Support long-term planning
|
||||
|
||||
## Step-by-Step Process
|
||||
|
||||
### Step 1: Define Business Model
|
||||
|
||||
Clarify revenue model and pricing.
|
||||
|
||||
**SaaS Model:**
|
||||
- Subscription pricing tiers
|
||||
- Annual vs. monthly contracts
|
||||
- Free trial or freemium approach
|
||||
- Expansion revenue strategy
|
||||
|
||||
**Marketplace Model:**
|
||||
- GMV projections
|
||||
- Take rate (% of transactions)
|
||||
- Buyer and seller economics
|
||||
- Transaction frequency
|
||||
|
||||
**Transactional Model:**
|
||||
- Transaction volume
|
||||
- Revenue per transaction
|
||||
- Frequency and seasonality
|
||||
|
||||
### Step 2: Build Revenue Projections
|
||||
|
||||
Use cohort-based methodology for accuracy.
|
||||
|
||||
**Monthly Customer Acquisition:**
|
||||
Define new customers acquired each month.
|
||||
|
||||
**Retention Curve:**
|
||||
Model customer retention over time.
|
||||
|
||||
**Typical SaaS Retention:**
|
||||
- Month 1: 100%
|
||||
- Month 3: 90%
|
||||
- Month 6: 85%
|
||||
- Month 12: 75%
|
||||
- Month 24: 70%
|
||||
|
||||
**Revenue Calculation:**
|
||||
For each cohort, calculate retained customers × ARPU for each month.
|
||||
|
||||
### Step 3: Model Cost Structure
|
||||
|
||||
Break down costs by category and behavior.
|
||||
|
||||
**Fixed vs. Variable:**
|
||||
- Fixed: Salaries, software, rent
|
||||
- Variable: Hosting, payment processing, support
|
||||
|
||||
**Scaling Assumptions:**
|
||||
- COGS as % of revenue
|
||||
- S&M as % of revenue (CAC payback)
|
||||
- R&D growth rate
|
||||
- G&A as % of total expenses
|
||||
|
||||
### Step 4: Create Hiring Plan
|
||||
|
||||
Model headcount growth by role and department.
|
||||
|
||||
**Inputs:**
|
||||
- Starting headcount
|
||||
- Hiring velocity by role
|
||||
- Fully-loaded compensation by role
|
||||
- Benefits and taxes (typically 1.3-1.4x salary)
|
||||
|
||||
**Example:**
|
||||
```
|
||||
Engineer: $150K salary × 1.35 = $202K fully-loaded
|
||||
Sales Rep: $100K OTE × 1.30 = $130K fully-loaded
|
||||
```
|
||||
|
||||
### Step 5: Project Cash Flow
|
||||
|
||||
Calculate monthly cash position and runway.
|
||||
|
||||
**Monthly Cash Flow:**
|
||||
```
|
||||
Beginning Cash
|
||||
+ Revenue Collected (consider payment terms)
|
||||
- Operating Expenses Paid
|
||||
- CapEx
|
||||
= Ending Cash
|
||||
```
|
||||
|
||||
**Runway Calculation:**
|
||||
```
|
||||
If Ending Cash < 0:
|
||||
Funding Need = Negative Cash Balance
|
||||
Runway = 0
|
||||
Else:
|
||||
Runway = Ending Cash / Average Monthly Burn
|
||||
```
|
||||
|
||||
### Step 6: Calculate Key Metrics
|
||||
|
||||
Track metrics that matter for stage.
|
||||
|
||||
**Revenue Metrics:**
|
||||
- MRR / ARR
|
||||
- Growth rate (MoM, YoY)
|
||||
- Revenue by segment or cohort
|
||||
|
||||
**Unit Economics:**
|
||||
- CAC (Customer Acquisition Cost)
|
||||
- LTV (Lifetime Value)
|
||||
- CAC Payback Period
|
||||
- LTV / CAC Ratio
|
||||
|
||||
**Efficiency Metrics:**
|
||||
- Burn multiple (Net Burn / Net New ARR)
|
||||
- Magic number (Net New ARR / S&M Spend)
|
||||
- Rule of 40 (Growth % + Profit Margin %)
|
||||
|
||||
**Cash Metrics:**
|
||||
- Monthly burn rate
|
||||
- Runway (months)
|
||||
- Cash efficiency
|
||||
|
||||
### Step 7: Scenario Analysis
|
||||
|
||||
Create three scenarios with different assumptions.
|
||||
|
||||
**Variable Assumptions:**
|
||||
- Customer acquisition rate (±30%)
|
||||
- Churn rate (±20%)
|
||||
- Average contract value (±15%)
|
||||
- CAC (±25%)
|
||||
|
||||
**Fixed Assumptions:**
|
||||
- Pricing structure
|
||||
- Core operating expenses
|
||||
- Hiring plan (adjust timing, not roles)
|
||||
|
||||
## Business Model Templates
|
||||
|
||||
### SaaS Financial Model
|
||||
|
||||
**Revenue Drivers:**
|
||||
- New MRR (customers × ARPU)
|
||||
- Expansion MRR (upsells)
|
||||
- Contraction MRR (downgrades)
|
||||
- Churned MRR (lost customers)
|
||||
|
||||
**Key Ratios:**
|
||||
- Gross margin: 75-85%
|
||||
- S&M as % revenue: 40-60% (early stage)
|
||||
- CAC payback: < 12 months
|
||||
- Net retention: 100-120%
|
||||
|
||||
**Example Projection:**
|
||||
```
|
||||
Year 1: $500K ARR, 50 customers, $100K MRR by Dec
|
||||
Year 2: $2.5M ARR, 200 customers, $208K MRR by Dec
|
||||
Year 3: $8M ARR, 600 customers, $667K MRR by Dec
|
||||
```
|
||||
|
||||
### Marketplace Financial Model
|
||||
|
||||
**Revenue Drivers:**
|
||||
- GMV (Gross Merchandise Value)
|
||||
- Take rate (% of GMV)
|
||||
- Net revenue = GMV × Take rate
|
||||
|
||||
**Key Ratios:**
|
||||
- Take rate: 10-30% depending on category
|
||||
- CAC for buyers vs. sellers
|
||||
- Contribution margin: 60-70%
|
||||
|
||||
**Example Projection:**
|
||||
```
|
||||
Year 1: $5M GMV, 15% take rate = $750K revenue
|
||||
Year 2: $20M GMV, 15% take rate = $3M revenue
|
||||
Year 3: $60M GMV, 15% take rate = $9M revenue
|
||||
```
|
||||
|
||||
### E-Commerce Financial Model
|
||||
|
||||
**Revenue Drivers:**
|
||||
- Traffic (visitors)
|
||||
- Conversion rate
|
||||
- Average order value (AOV)
|
||||
- Purchase frequency
|
||||
|
||||
**Key Ratios:**
|
||||
- Gross margin: 40-60%
|
||||
- Contribution margin: 20-35%
|
||||
- CAC payback: 3-6 months
|
||||
|
||||
### Services / Agency Financial Model
|
||||
|
||||
**Revenue Drivers:**
|
||||
- Billable hours or projects
|
||||
- Hourly rate or project fee
|
||||
- Utilization rate
|
||||
- Team capacity
|
||||
|
||||
**Key Ratios:**
|
||||
- Gross margin: 50-70%
|
||||
- Utilization: 70-85%
|
||||
- Revenue per employee
|
||||
|
||||
## Fundraising Integration
|
||||
|
||||
### Funding Scenario Modeling
|
||||
|
||||
**Pre-Money Valuation:**
|
||||
Based on metrics and comparables.
|
||||
|
||||
**Dilution:**
|
||||
```
|
||||
Post-Money = Pre-Money + Investment
|
||||
Dilution % = Investment / Post-Money
|
||||
```
|
||||
|
||||
**Use of Funds:**
|
||||
Allocate funding to extend runway and achieve milestones.
|
||||
|
||||
**Example:**
|
||||
```
|
||||
Raise: $5M at $20M pre-money
|
||||
Post-Money: $25M
|
||||
Dilution: 20%
|
||||
|
||||
Use of Funds:
|
||||
- Product Development: $2M (40%)
|
||||
- Sales & Marketing: $2M (40%)
|
||||
- G&A and Operations: $0.5M (10%)
|
||||
- Working Capital: $0.5M (10%)
|
||||
```
|
||||
|
||||
### Milestone-Based Planning
|
||||
|
||||
**Identify Key Milestones:**
|
||||
- Product launch
|
||||
- First $1M ARR
|
||||
- Break-even on CAC
|
||||
- Series A fundraise
|
||||
|
||||
**Funding Amount:**
|
||||
Ensure runway to achieve next milestone + 6 months buffer.
|
||||
|
||||
## Common Pitfalls
|
||||
|
||||
**Pitfall 1: Overly Optimistic Revenue**
|
||||
- New startups rarely hit aggressive projections
|
||||
- Use conservative customer acquisition assumptions
|
||||
- Model realistic churn rates
|
||||
|
||||
**Pitfall 2: Underestimating Costs**
|
||||
- Add 20% buffer to expense estimates
|
||||
- Include fully-loaded compensation
|
||||
- Account for software and tools
|
||||
|
||||
**Pitfall 3: Ignoring Cash Flow Timing**
|
||||
- Revenue ≠ cash (payment terms)
|
||||
- Expenses paid before revenue collected
|
||||
- Model cash conversion carefully
|
||||
|
||||
**Pitfall 4: Static Headcount**
|
||||
- Hiring takes time (3-6 months to fill roles)
|
||||
- Ramp time for productivity (3-6 months)
|
||||
- Account for attrition (10-15% annually)
|
||||
|
||||
**Pitfall 5: Not Scenario Planning**
|
||||
- Single scenario is never accurate
|
||||
- Always model conservative case
|
||||
- Plan for what you'll do if base case fails
|
||||
|
||||
## Model Validation
|
||||
|
||||
**Sanity Checks:**
|
||||
- [ ] Revenue growth rate is achievable (3x in Year 2, 2x in Year 3)
|
||||
- [ ] Unit economics are realistic (LTV/CAC > 3, payback < 18 months)
|
||||
- [ ] Burn multiple is reasonable (< 2.0 in Year 2-3)
|
||||
- [ ] Headcount scales with revenue (revenue per employee growing)
|
||||
- [ ] Gross margin is appropriate for business model
|
||||
- [ ] S&M spending aligns with CAC and growth targets
|
||||
|
||||
**Benchmark Against Peers:**
|
||||
Compare key metrics to similar companies at similar stage.
|
||||
|
||||
**Investor Feedback:**
|
||||
Share model with advisors or investors for feedback on assumptions.
|
||||
|
||||
## Additional Resources
|
||||
|
||||
### Reference Files
|
||||
|
||||
For detailed model structures and advanced techniques:
|
||||
- **`references/model-templates.md`** - Complete financial model templates by business model
|
||||
- **`references/unit-economics.md`** - Deep dive on CAC, LTV, payback, and efficiency metrics
|
||||
- **`references/fundraising-scenarios.md`** - Modeling funding rounds and dilution
|
||||
|
||||
### Example Files
|
||||
|
||||
Working financial models with formulas:
|
||||
- **`examples/saas-financial-model.md`** - Complete 3-year SaaS model with cohort analysis
|
||||
- **`examples/marketplace-model.md`** - Marketplace GMV and take rate projections
|
||||
- **`examples/scenario-analysis.md`** - Three-scenario framework with sensitivities
|
||||
|
||||
## Quick Start
|
||||
|
||||
To create a startup financial model:
|
||||
|
||||
1. **Define business model** - Revenue drivers and pricing
|
||||
2. **Project revenue** - Cohort-based with retention
|
||||
3. **Model costs** - COGS, S&M, R&D, G&A by month
|
||||
4. **Plan headcount** - Hiring by role and department
|
||||
5. **Calculate cash flow** - Revenue - expenses = burn/runway
|
||||
6. **Compute metrics** - CAC, LTV, burn multiple, runway
|
||||
7. **Create scenarios** - Conservative, base, optimistic
|
||||
8. **Validate assumptions** - Sanity check and benchmark
|
||||
9. **Integrate fundraising** - Model funding rounds and milestones
|
||||
|
||||
For complete templates and formulas, reference the `references/` and `examples/` files.
|
||||
@@ -0,0 +1,502 @@
|
||||
---
|
||||
name: startup-metrics-framework
|
||||
description: This skill should be used when the user asks about "key startup metrics", "SaaS metrics", "CAC and LTV", "unit economics", "burn multiple", "rule of 40", "marketplace metrics", or requests guidance on tracking and optimizing business performance metrics.
|
||||
version: 1.0.0
|
||||
---
|
||||
|
||||
# Startup Metrics Framework
|
||||
|
||||
Comprehensive guide to tracking, calculating, and optimizing key performance metrics for different startup business models from seed through Series A.
|
||||
|
||||
## Overview
|
||||
|
||||
Track the right metrics at the right stage. Focus on unit economics, growth efficiency, and cash management metrics that matter for fundraising and operational excellence.
|
||||
|
||||
## Universal Startup Metrics
|
||||
|
||||
### Revenue Metrics
|
||||
|
||||
**MRR (Monthly Recurring Revenue)**
|
||||
```
|
||||
MRR = Σ (Active Subscriptions × Monthly Price)
|
||||
```
|
||||
|
||||
**ARR (Annual Recurring Revenue)**
|
||||
```
|
||||
ARR = MRR × 12
|
||||
```
|
||||
|
||||
**Growth Rate**
|
||||
```
|
||||
MoM Growth = (This Month MRR - Last Month MRR) / Last Month MRR
|
||||
YoY Growth = (This Year ARR - Last Year ARR) / Last Year ARR
|
||||
```
|
||||
|
||||
**Target Benchmarks:**
|
||||
- Seed stage: 15-20% MoM growth
|
||||
- Series A: 10-15% MoM growth, 3-5x YoY
|
||||
- Series B+: 100%+ YoY (Rule of 40)
|
||||
|
||||
### Unit Economics
|
||||
|
||||
**CAC (Customer Acquisition Cost)**
|
||||
```
|
||||
CAC = Total S&M Spend / New Customers Acquired
|
||||
```
|
||||
|
||||
Include: Sales salaries, marketing spend, tools, overhead
|
||||
|
||||
**LTV (Lifetime Value)**
|
||||
```
|
||||
LTV = ARPU × Gross Margin% × (1 / Churn Rate)
|
||||
```
|
||||
|
||||
Simplified:
|
||||
```
|
||||
LTV = ARPU × Average Customer Lifetime × Gross Margin%
|
||||
```
|
||||
|
||||
**LTV:CAC Ratio**
|
||||
```
|
||||
LTV:CAC = LTV / CAC
|
||||
```
|
||||
|
||||
**Benchmarks:**
|
||||
- LTV:CAC > 3.0 = Healthy
|
||||
- LTV:CAC 1.0-3.0 = Needs improvement
|
||||
- LTV:CAC < 1.0 = Unsustainable
|
||||
|
||||
**CAC Payback Period**
|
||||
```
|
||||
CAC Payback = CAC / (ARPU × Gross Margin%)
|
||||
```
|
||||
|
||||
**Benchmarks:**
|
||||
- < 12 months = Excellent
|
||||
- 12-18 months = Good
|
||||
- > 24 months = Concerning
|
||||
|
||||
### Cash Efficiency Metrics
|
||||
|
||||
**Burn Rate**
|
||||
```
|
||||
Monthly Burn = Monthly Revenue - Monthly Expenses
|
||||
```
|
||||
|
||||
Negative burn = losing money (typical early-stage)
|
||||
|
||||
**Runway**
|
||||
```
|
||||
Runway (months) = Cash Balance / Monthly Burn Rate
|
||||
```
|
||||
|
||||
**Target:** Always maintain 12-18 months runway
|
||||
|
||||
**Burn Multiple**
|
||||
```
|
||||
Burn Multiple = Net Burn / Net New ARR
|
||||
```
|
||||
|
||||
**Benchmarks:**
|
||||
- < 1.0 = Exceptional efficiency
|
||||
- 1.0-1.5 = Good
|
||||
- 1.5-2.0 = Acceptable
|
||||
- > 2.0 = Inefficient
|
||||
|
||||
Lower is better (spending less to generate ARR)
|
||||
|
||||
## SaaS Metrics
|
||||
|
||||
### Revenue Composition
|
||||
|
||||
**New MRR**
|
||||
New customers × ARPU
|
||||
|
||||
**Expansion MRR**
|
||||
Upsells and cross-sells from existing customers
|
||||
|
||||
**Contraction MRR**
|
||||
Downgrades from existing customers
|
||||
|
||||
**Churned MRR**
|
||||
Lost customers
|
||||
|
||||
**Net New MRR Formula:**
|
||||
```
|
||||
Net New MRR = New MRR + Expansion MRR - Contraction MRR - Churned MRR
|
||||
```
|
||||
|
||||
### Retention Metrics
|
||||
|
||||
**Logo Retention**
|
||||
```
|
||||
Logo Retention = (Customers End - New Customers) / Customers Start
|
||||
```
|
||||
|
||||
**Dollar Retention (NDR - Net Dollar Retention)**
|
||||
```
|
||||
NDR = (ARR Start + Expansion - Contraction - Churn) / ARR Start
|
||||
```
|
||||
|
||||
**Benchmarks:**
|
||||
- NDR > 120% = Best-in-class
|
||||
- NDR 100-120% = Good
|
||||
- NDR < 100% = Needs work
|
||||
|
||||
**Gross Retention**
|
||||
```
|
||||
Gross Retention = (ARR Start - Churn - Contraction) / ARR Start
|
||||
```
|
||||
|
||||
**Benchmarks:**
|
||||
- > 90% = Excellent
|
||||
- 85-90% = Good
|
||||
- < 85% = Concerning
|
||||
|
||||
### SaaS-Specific Metrics
|
||||
|
||||
**Magic Number**
|
||||
```
|
||||
Magic Number = Net New ARR (quarter) / S&M Spend (prior quarter)
|
||||
```
|
||||
|
||||
**Benchmarks:**
|
||||
- > 0.75 = Efficient, ready to scale
|
||||
- 0.5-0.75 = Moderate efficiency
|
||||
- < 0.5 = Inefficient, don't scale yet
|
||||
|
||||
**Rule of 40**
|
||||
```
|
||||
Rule of 40 = Revenue Growth Rate% + Profit Margin%
|
||||
```
|
||||
|
||||
**Benchmarks:**
|
||||
- > 40% = Excellent
|
||||
- 20-40% = Acceptable
|
||||
- < 20% = Needs improvement
|
||||
|
||||
**Example:**
|
||||
50% growth + (10%) margin = 40% ✓
|
||||
|
||||
**Quick Ratio**
|
||||
```
|
||||
Quick Ratio = (New MRR + Expansion MRR) / (Churned MRR + Contraction MRR)
|
||||
```
|
||||
|
||||
**Benchmarks:**
|
||||
- > 4.0 = Healthy growth
|
||||
- 2.0-4.0 = Moderate
|
||||
- < 2.0 = Churn problem
|
||||
|
||||
## Marketplace Metrics
|
||||
|
||||
### GMV (Gross Merchandise Value)
|
||||
|
||||
**Total Transaction Volume:**
|
||||
```
|
||||
GMV = Σ (Transaction Value)
|
||||
```
|
||||
|
||||
**Growth Rate:**
|
||||
```
|
||||
GMV Growth Rate = (Current Period GMV - Prior Period GMV) / Prior Period GMV
|
||||
```
|
||||
|
||||
**Target:** 20%+ MoM early-stage
|
||||
|
||||
### Take Rate
|
||||
|
||||
```
|
||||
Take Rate = Net Revenue / GMV
|
||||
```
|
||||
|
||||
**Typical Ranges:**
|
||||
- Payment processors: 2-3%
|
||||
- E-commerce marketplaces: 10-20%
|
||||
- Service marketplaces: 15-25%
|
||||
- High-value B2B: 5-15%
|
||||
|
||||
### Marketplace Liquidity
|
||||
|
||||
**Time to Transaction**
|
||||
How long from listing to sale/match?
|
||||
|
||||
**Fill Rate**
|
||||
% of requests that result in transaction
|
||||
|
||||
**Repeat Rate**
|
||||
% of users who transact multiple times
|
||||
|
||||
**Benchmarks:**
|
||||
- Fill rate > 80% = Strong liquidity
|
||||
- Repeat rate > 60% = Strong retention
|
||||
|
||||
### Marketplace Balance
|
||||
|
||||
**Supply/Demand Ratio:**
|
||||
Track relative growth of supply and demand sides.
|
||||
|
||||
**Warning Signs:**
|
||||
- Too much supply: Low fill rates, frustrated suppliers
|
||||
- Too much demand: Long wait times, frustrated customers
|
||||
|
||||
**Goal:** Balanced growth (1:1 ratio ideal, but varies by model)
|
||||
|
||||
## Consumer/Mobile Metrics
|
||||
|
||||
### Engagement Metrics
|
||||
|
||||
**DAU (Daily Active Users)**
|
||||
Unique users active each day
|
||||
|
||||
**MAU (Monthly Active Users)**
|
||||
Unique users active each month
|
||||
|
||||
**DAU/MAU Ratio**
|
||||
```
|
||||
DAU/MAU = DAU / MAU
|
||||
```
|
||||
|
||||
**Benchmarks:**
|
||||
- > 50% = Exceptional (daily habit)
|
||||
- 20-50% = Good
|
||||
- < 20% = Weak engagement
|
||||
|
||||
**Session Frequency**
|
||||
Average sessions per user per day/week
|
||||
|
||||
**Session Duration**
|
||||
Average time spent per session
|
||||
|
||||
### Retention Curves
|
||||
|
||||
**Day 1 Retention:** % users who return next day
|
||||
**Day 7 Retention:** % users active 7 days after signup
|
||||
**Day 30 Retention:** % users active 30 days after signup
|
||||
|
||||
**Benchmarks (Day 30):**
|
||||
- > 40% = Excellent
|
||||
- 25-40% = Good
|
||||
- < 25% = Weak
|
||||
|
||||
**Retention Curve Shape:**
|
||||
- Flattening curve = good (users becoming habitual)
|
||||
- Steep decline = poor product-market fit
|
||||
|
||||
### Viral Coefficient (K-Factor)
|
||||
|
||||
```
|
||||
K-Factor = Invites per User × Invite Conversion Rate
|
||||
```
|
||||
|
||||
**Example:**
|
||||
10 invites/user × 20% conversion = 2.0 K-factor
|
||||
|
||||
**Benchmarks:**
|
||||
- K > 1.0 = Viral growth
|
||||
- K = 0.5-1.0 = Strong referrals
|
||||
- K < 0.5 = Weak virality
|
||||
|
||||
## B2B Metrics
|
||||
|
||||
### Sales Efficiency
|
||||
|
||||
**Win Rate**
|
||||
```
|
||||
Win Rate = Deals Won / Total Opportunities
|
||||
```
|
||||
|
||||
**Target:** 20-30% for new sales team, 30-40% mature
|
||||
|
||||
**Sales Cycle Length**
|
||||
Average days from opportunity to close
|
||||
|
||||
**Shorter is better:**
|
||||
- SMB: 30-60 days
|
||||
- Mid-market: 60-120 days
|
||||
- Enterprise: 120-270 days
|
||||
|
||||
**Average Contract Value (ACV)**
|
||||
```
|
||||
ACV = Total Contract Value / Contract Length (years)
|
||||
```
|
||||
|
||||
### Pipeline Metrics
|
||||
|
||||
**Pipeline Coverage**
|
||||
```
|
||||
Pipeline Coverage = Total Pipeline Value / Quota
|
||||
```
|
||||
|
||||
**Target:** 3-5x coverage (3-5x pipeline needed to hit quota)
|
||||
|
||||
**Conversion Rates by Stage:**
|
||||
- Lead → Opportunity: 10-20%
|
||||
- Opportunity → Demo: 50-70%
|
||||
- Demo → Proposal: 30-50%
|
||||
- Proposal → Close: 20-40%
|
||||
|
||||
## Metrics by Stage
|
||||
|
||||
### Pre-Seed (Product-Market Fit)
|
||||
|
||||
**Focus Metrics:**
|
||||
1. Active users growth
|
||||
2. User retention (Day 7, Day 30)
|
||||
3. Core engagement (sessions, features used)
|
||||
4. Qualitative feedback (NPS, interviews)
|
||||
|
||||
**Don't worry about:**
|
||||
- Revenue (may be zero)
|
||||
- CAC (not optimizing yet)
|
||||
- Unit economics
|
||||
|
||||
### Seed ($500K-$2M ARR)
|
||||
|
||||
**Focus Metrics:**
|
||||
1. MRR growth rate (15-20% MoM)
|
||||
2. CAC and LTV (establish baseline)
|
||||
3. Gross retention (> 85%)
|
||||
4. Core product engagement
|
||||
|
||||
**Start tracking:**
|
||||
- Sales efficiency
|
||||
- Burn rate and runway
|
||||
|
||||
### Series A ($2M-$10M ARR)
|
||||
|
||||
**Focus Metrics:**
|
||||
1. ARR growth (3-5x YoY)
|
||||
2. Unit economics (LTV:CAC > 3, payback < 18 months)
|
||||
3. Net dollar retention (> 100%)
|
||||
4. Burn multiple (< 2.0)
|
||||
5. Magic number (> 0.5)
|
||||
|
||||
**Mature tracking:**
|
||||
- Rule of 40
|
||||
- Sales efficiency
|
||||
- Pipeline coverage
|
||||
|
||||
## Metric Tracking Best Practices
|
||||
|
||||
### Data Infrastructure
|
||||
|
||||
**Requirements:**
|
||||
- Single source of truth (analytics platform)
|
||||
- Real-time or daily updates
|
||||
- Automated calculations
|
||||
- Historical tracking
|
||||
|
||||
**Tools:**
|
||||
- Mixpanel, Amplitude (product analytics)
|
||||
- ChartMogul, Baremetrics (SaaS metrics)
|
||||
- Looker, Tableau (BI dashboards)
|
||||
|
||||
### Reporting Cadence
|
||||
|
||||
**Daily:**
|
||||
- MRR, active users
|
||||
- Sign-ups, conversions
|
||||
|
||||
**Weekly:**
|
||||
- Growth rates
|
||||
- Retention cohorts
|
||||
- Sales pipeline
|
||||
|
||||
**Monthly:**
|
||||
- Full metric suite
|
||||
- Board reporting
|
||||
- Investor updates
|
||||
|
||||
**Quarterly:**
|
||||
- Trend analysis
|
||||
- Benchmarking
|
||||
- Strategy review
|
||||
|
||||
### Common Mistakes
|
||||
|
||||
**Mistake 1: Vanity Metrics**
|
||||
Don't focus on:
|
||||
- Total users (without retention)
|
||||
- Page views (without engagement)
|
||||
- Downloads (without activation)
|
||||
|
||||
Focus on actionable metrics tied to value.
|
||||
|
||||
**Mistake 2: Too Many Metrics**
|
||||
Track 5-7 core metrics intensely, not 50 loosely.
|
||||
|
||||
**Mistake 3: Ignoring Unit Economics**
|
||||
CAC and LTV are critical even at seed stage.
|
||||
|
||||
**Mistake 4: Not Segmenting**
|
||||
Break down metrics by customer segment, channel, cohort.
|
||||
|
||||
**Mistake 5: Gaming Metrics**
|
||||
Optimize for real business outcomes, not dashboard numbers.
|
||||
|
||||
## Investor Metrics
|
||||
|
||||
### What VCs Want to See
|
||||
|
||||
**Seed Round:**
|
||||
- MRR growth rate
|
||||
- User retention
|
||||
- Early unit economics
|
||||
- Product engagement
|
||||
|
||||
**Series A:**
|
||||
- ARR and growth rate
|
||||
- CAC payback < 18 months
|
||||
- LTV:CAC > 3.0
|
||||
- Net dollar retention > 100%
|
||||
- Burn multiple < 2.0
|
||||
|
||||
**Series B+:**
|
||||
- Rule of 40 > 40%
|
||||
- Efficient growth (magic number)
|
||||
- Path to profitability
|
||||
- Market leadership metrics
|
||||
|
||||
### Metric Presentation
|
||||
|
||||
**Dashboard Format:**
|
||||
```
|
||||
Current MRR: $250K (↑ 18% MoM)
|
||||
ARR: $3.0M (↑ 280% YoY)
|
||||
CAC: $1,200 | LTV: $4,800 | LTV:CAC = 4.0x
|
||||
NDR: 112% | Logo Retention: 92%
|
||||
Burn: $180K/mo | Runway: 18 months
|
||||
```
|
||||
|
||||
**Include:**
|
||||
- Current value
|
||||
- Growth rate or trend
|
||||
- Context (target, benchmark)
|
||||
|
||||
## Additional Resources
|
||||
|
||||
### Reference Files
|
||||
- **`references/metric-definitions.md`** - Complete definitions and formulas for 50+ metrics
|
||||
- **`references/benchmarks-by-stage.md`** - Target ranges for each metric by company stage
|
||||
- **`references/calculation-examples.md`** - Step-by-step calculation examples
|
||||
|
||||
### Example Files
|
||||
- **`examples/saas-metrics-dashboard.md`** - Complete metrics suite for B2B SaaS company
|
||||
- **`examples/marketplace-metrics.md`** - Marketplace-specific metrics with examples
|
||||
- **`examples/investor-metrics-deck.md`** - How to present metrics for fundraising
|
||||
|
||||
## Quick Start
|
||||
|
||||
To implement startup metrics framework:
|
||||
|
||||
1. **Identify business model** - SaaS, marketplace, consumer, B2B
|
||||
2. **Choose 5-7 core metrics** - Based on stage and model
|
||||
3. **Establish tracking** - Set up analytics and dashboards
|
||||
4. **Calculate unit economics** - CAC, LTV, payback
|
||||
5. **Set targets** - Use benchmarks for goals
|
||||
6. **Review regularly** - Weekly for core metrics
|
||||
7. **Share with team** - Align on goals and progress
|
||||
8. **Update investors** - Monthly/quarterly reporting
|
||||
|
||||
For detailed definitions, benchmarks, and examples, see `references/` and `examples/`.
|
||||
@@ -0,0 +1,392 @@
|
||||
---
|
||||
name: team-composition-analysis
|
||||
description: This skill should be used when the user asks to "plan team structure", "determine hiring needs", "design org chart", "calculate compensation", "plan equity allocation", or requests organizational design and headcount planning for a startup.
|
||||
version: 1.0.0
|
||||
---
|
||||
|
||||
# Team Composition Analysis
|
||||
|
||||
Design optimal team structures, hiring plans, compensation strategies, and equity allocation for early-stage startups from pre-seed through Series A.
|
||||
|
||||
## Overview
|
||||
|
||||
Build the right team at the right time with appropriate compensation and equity. Plan role-by-role hiring aligned with revenue milestones, budget constraints, and market benchmarks.
|
||||
|
||||
## Team Structure by Stage
|
||||
|
||||
### Pre-Seed (0-$500K ARR)
|
||||
|
||||
**Team Size: 2-5 people**
|
||||
|
||||
**Core Roles:**
|
||||
- Founders (2-3): Product, engineering, business
|
||||
- First engineer (if needed)
|
||||
- Contract roles: Design, marketing
|
||||
|
||||
**Focus:** Build and validate product-market fit
|
||||
|
||||
### Seed ($500K-$2M ARR)
|
||||
|
||||
**Team Size: 5-15 people**
|
||||
|
||||
**Key Hires:**
|
||||
- Engineering lead + 2-3 engineers
|
||||
- First sales/business development
|
||||
- Product manager
|
||||
- Marketing/growth lead
|
||||
|
||||
**Focus:** Scale product and prove repeatable sales
|
||||
|
||||
### Series A ($2M-$10M ARR)
|
||||
|
||||
**Team Size: 15-50 people**
|
||||
|
||||
**Department Build-Out:**
|
||||
- Engineering (40%): 6-20 people
|
||||
- Sales & Marketing (30%): 5-15 people
|
||||
- Customer Success (10%): 2-5 people
|
||||
- G&A (10%): 2-5 people
|
||||
- Product (10%): 2-5 people
|
||||
|
||||
**Focus:** Scale revenue and build repeatable processes
|
||||
|
||||
## Role-by-Role Planning
|
||||
|
||||
### Engineering Team
|
||||
|
||||
**Pre-Seed:**
|
||||
- Founders write code
|
||||
- 0-1 contract developers
|
||||
|
||||
**Seed:**
|
||||
- Engineering Lead (first $150K-$180K)
|
||||
- 2-3 Full-Stack Engineers ($120K-$150K)
|
||||
- 1 Frontend or Backend Specialist ($130K-$160K)
|
||||
|
||||
**Series A:**
|
||||
- VP Engineering ($180K-$250K + equity)
|
||||
- 2-3 Senior Engineers ($150K-$180K)
|
||||
- 3-5 Mid-Level Engineers ($120K-$150K)
|
||||
- 1-2 Junior Engineers ($90K-$120K)
|
||||
- 1 DevOps/Infrastructure ($140K-$170K)
|
||||
|
||||
### Sales & Marketing
|
||||
|
||||
**Pre-Seed:**
|
||||
- Founders do sales
|
||||
- Contract marketing help
|
||||
|
||||
**Seed:**
|
||||
- First Sales Hire / Head of Sales ($120K-$150K + commission)
|
||||
- Marketing/Growth Lead ($100K-$140K)
|
||||
- SDR or BDR (if B2B) ($50K-$70K + commission)
|
||||
|
||||
**Series A:**
|
||||
- VP Sales ($150K-$200K + commission + equity)
|
||||
- 3-5 Account Executives ($80K-$120K + commission)
|
||||
- 2-3 SDRs/BDRs ($50K-$70K + commission)
|
||||
- Marketing Manager ($90K-$130K)
|
||||
- Content/Demand Gen ($70K-$100K)
|
||||
|
||||
### Product Team
|
||||
|
||||
**Pre-Seed:**
|
||||
- Founder as product lead
|
||||
|
||||
**Seed:**
|
||||
- First Product Manager ($120K-$150K)
|
||||
- Contract designer
|
||||
|
||||
**Series A:**
|
||||
- Head of Product ($150K-$180K)
|
||||
- 1-2 Product Managers ($120K-$150K)
|
||||
- Product Designer ($100K-$140K)
|
||||
- UX Researcher (optional) ($90K-$130K)
|
||||
|
||||
### Customer Success
|
||||
|
||||
**Pre-Seed:**
|
||||
- Founders handle support
|
||||
|
||||
**Seed:**
|
||||
- First CS hire (optional) ($60K-$90K)
|
||||
|
||||
**Series A:**
|
||||
- CS Manager ($100K-$130K)
|
||||
- 2-4 CS Representatives ($60K-$90K)
|
||||
- Support Engineer (technical) ($80K-$120K)
|
||||
|
||||
### G&A (General & Administrative)
|
||||
|
||||
**Pre-Seed:**
|
||||
- Contractors (accounting, legal)
|
||||
|
||||
**Seed:**
|
||||
- Operations/Office Manager ($70K-$100K)
|
||||
- Contract CFO
|
||||
|
||||
**Series A:**
|
||||
- CFO or Finance Lead ($150K-$200K)
|
||||
- Recruiter ($80K-$120K)
|
||||
- Office Manager / EA ($60K-$90K)
|
||||
|
||||
## Compensation Strategy
|
||||
|
||||
### Base Salary Benchmarks (US, 2024)
|
||||
|
||||
**Engineering:**
|
||||
- Junior: $90K-$120K
|
||||
- Mid-Level: $120K-$150K
|
||||
- Senior: $150K-$180K
|
||||
- Staff/Principal: $180K-$220K
|
||||
- Engineering Manager: $160K-$200K
|
||||
- VP Engineering: $180K-$250K
|
||||
|
||||
**Sales:**
|
||||
- SDR/BDR: $50K-$70K base + $50K-$70K commission
|
||||
- Account Executive: $80K-$120K base + $80K-$120K commission
|
||||
- Sales Manager: $120K-$160K base + $80K-$120K commission
|
||||
- VP Sales: $150K-$200K base + $150K-$200K commission
|
||||
|
||||
**Product:**
|
||||
- Product Manager: $120K-$150K
|
||||
- Senior PM: $150K-$180K
|
||||
- Head of Product: $150K-$180K
|
||||
- VP Product: $180K-$220K
|
||||
|
||||
**Marketing:**
|
||||
- Marketing Manager: $90K-$130K
|
||||
- Content/Demand Gen: $70K-$100K
|
||||
- Head of Marketing: $130K-$170K
|
||||
- VP Marketing: $150K-$200K
|
||||
|
||||
**Customer Success:**
|
||||
- CS Representative: $60K-$90K
|
||||
- CS Manager: $100K-$130K
|
||||
- VP Customer Success: $140K-$180K
|
||||
|
||||
### Total Compensation Formula
|
||||
|
||||
```
|
||||
Total Comp = Base Salary × 1.30 (benefits & taxes) + Equity Value
|
||||
```
|
||||
|
||||
**Fully-Loaded Cost:**
|
||||
- Base salary
|
||||
- Payroll taxes (7.65% FICA)
|
||||
- Benefits (health insurance, 401k): $10K-$15K per employee
|
||||
- Other (workspace, equipment, software): $5K-$10K per employee
|
||||
|
||||
**Rule of Thumb:** Multiply base salary by 1.3-1.4 for fully-loaded cost
|
||||
|
||||
### Geographic Adjustments
|
||||
|
||||
**San Francisco / New York:** +20-30% above benchmarks
|
||||
**Seattle / Boston / Los Angeles:** +10-20%
|
||||
**Austin / Denver / Chicago:** +0-10%
|
||||
**Remote / Other US Cities:** -10-20%
|
||||
**International:** Varies widely by country
|
||||
|
||||
## Equity Allocation
|
||||
|
||||
### Equity by Role and Stage
|
||||
|
||||
**Founders:**
|
||||
- First founder: 40-60%
|
||||
- Second founder: 20-40%
|
||||
- Third founder: 10-20%
|
||||
- Vesting: 4 years with 1-year cliff
|
||||
|
||||
**Early Employees (Pre-Seed):**
|
||||
- First engineer: 0.5-2.0%
|
||||
- First 5 employees: 0.25-1.0% each
|
||||
|
||||
**Seed Stage Hires:**
|
||||
- VP/Head level: 0.5-1.5%
|
||||
- Senior IC: 0.1-0.5%
|
||||
- Mid-level: 0.05-0.25%
|
||||
- Junior: 0.01-0.1%
|
||||
|
||||
**Series A Hires:**
|
||||
- C-level (CTO, CFO): 1.0-3.0%
|
||||
- VP level: 0.3-1.0%
|
||||
- Director level: 0.1-0.5%
|
||||
- Senior IC: 0.05-0.2%
|
||||
- Mid-level: 0.01-0.1%
|
||||
- Junior: 0.005-0.05%
|
||||
|
||||
### Equity Pool Sizing
|
||||
|
||||
**Option Pool by Round:**
|
||||
- Pre-Seed: 10-15% reserved
|
||||
- Seed: 10-15% top-up
|
||||
- Series A: 10-15% top-up
|
||||
- Series B+: 5-10% per round
|
||||
|
||||
**Pre-Funding Dilution:**
|
||||
Investors often require option pool creation before investment, diluting founders.
|
||||
|
||||
**Example:**
|
||||
```
|
||||
Pre-money: $10M
|
||||
Investors want 15% option pool post-money
|
||||
|
||||
Calculation:
|
||||
Post-money: $15M ($10M + $5M investment)
|
||||
Option pool: $2.25M (15% × $15M)
|
||||
Founders diluted by pool creation before new money
|
||||
```
|
||||
|
||||
## Organizational Design
|
||||
|
||||
### Reporting Structure
|
||||
|
||||
**Pre-Seed:**
|
||||
```
|
||||
Founders (flat structure)
|
||||
├── Contractors
|
||||
└── First hires (report to founders)
|
||||
```
|
||||
|
||||
**Seed:**
|
||||
```
|
||||
CEO
|
||||
├── Engineering Lead (2-4 engineers)
|
||||
├── Sales/Growth Lead (1-2 reps)
|
||||
├── Product Manager
|
||||
└── Operations
|
||||
```
|
||||
|
||||
**Series A:**
|
||||
```
|
||||
CEO
|
||||
├── CTO / VP Engineering (6-20 people)
|
||||
│ ├── Engineering Manager(s)
|
||||
│ └── Individual Contributors
|
||||
├── VP Sales (5-15 people)
|
||||
│ ├── Sales Manager
|
||||
│ ├── Account Executives
|
||||
│ └── SDRs
|
||||
├── Head of Product (2-5 people)
|
||||
│ ├── Product Managers
|
||||
│ └── Designers
|
||||
├── Head of Customer Success (2-5 people)
|
||||
└── CFO / Finance Lead (2-5 people)
|
||||
├── Recruiter
|
||||
└── Operations
|
||||
```
|
||||
|
||||
### Span of Control
|
||||
|
||||
**Manager Ratios:**
|
||||
- First-line managers: 4-8 direct reports
|
||||
- Directors: 3-5 direct reports (managers)
|
||||
- VPs: 3-5 direct reports (directors)
|
||||
- CEO: 5-8 direct reports (executive team)
|
||||
|
||||
## Full-Time vs. Contract
|
||||
|
||||
### Use Full-Time for:
|
||||
- Core product development
|
||||
- Sales (revenue-generating roles)
|
||||
- Mission-critical operations
|
||||
- Institutional knowledge roles
|
||||
|
||||
### Use Contractors for:
|
||||
- Specialized short-term needs (legal, accounting)
|
||||
- Variable workload (design, marketing campaigns)
|
||||
- Skills outside core competency
|
||||
- Testing role before FTE hire
|
||||
- Geographic expansion before permanent presence
|
||||
|
||||
### Cost Comparison
|
||||
|
||||
**Full-Time:**
|
||||
- Lower hourly cost
|
||||
- Benefits and overhead
|
||||
- Long-term commitment
|
||||
- Cultural fit matters
|
||||
|
||||
**Contract:**
|
||||
- Higher hourly rate ($75-$200/hour vs. $40-$100/hour FTE equivalent)
|
||||
- No benefits or overhead
|
||||
- Flexible engagement
|
||||
- Easier to scale up/down
|
||||
|
||||
## Hiring Velocity
|
||||
|
||||
### Realistic Timeline
|
||||
|
||||
**Role Opening to Hire:**
|
||||
- Junior: 6-8 weeks
|
||||
- Mid-Level: 8-12 weeks
|
||||
- Senior: 12-16 weeks
|
||||
- Executive: 16-24 weeks
|
||||
|
||||
**Time to Productivity:**
|
||||
- Junior: 4-6 months
|
||||
- Mid-Level: 2-4 months
|
||||
- Senior: 1-3 months
|
||||
- Executive: 3-6 months
|
||||
|
||||
### Planning Buffer
|
||||
|
||||
Always add 2-3 months buffer to hiring plans.
|
||||
|
||||
**Example:**
|
||||
If need engineer by July 1:
|
||||
- Start recruiting: April 1 (12 weeks)
|
||||
- Productivity: September 1 (2 months ramp)
|
||||
|
||||
## Budget Planning
|
||||
|
||||
### Compensation as % of Revenue
|
||||
|
||||
**Early Stage (Seed):**
|
||||
- Total comp: 120-150% of revenue (burning cash to grow)
|
||||
- Engineering: 50-60%
|
||||
- Sales: 30-40%
|
||||
- Other: 20-30%
|
||||
|
||||
**Growth Stage (Series A):**
|
||||
- Total comp: 70-100% of revenue
|
||||
- Engineering: 35-45%
|
||||
- Sales: 25-35%
|
||||
- Other: 20-30%
|
||||
|
||||
### Headcount Budget Formula
|
||||
|
||||
```
|
||||
Total Comp Budget = Σ (Role Count × Fully-Loaded Cost × % of Year)
|
||||
|
||||
Example:
|
||||
3 Engineers × $202K × 100% = $606K
|
||||
2 AEs × $230K × 75% (mid-year start) = $345K
|
||||
1 PM × $162K × 100% = $162K
|
||||
Total: $1.1M
|
||||
```
|
||||
|
||||
## Additional Resources
|
||||
|
||||
### Reference Files
|
||||
- **`references/compensation-benchmarks.md`** - Detailed salary data by role, level, and location
|
||||
- **`references/equity-calculator.md`** - Equity sizing formulas and dilution scenarios
|
||||
|
||||
### Example Files
|
||||
- **`examples/seed-stage-hiring-plan.md`** - Complete hiring plan for seed-stage SaaS company
|
||||
- **`examples/org-chart-evolution.md`** - Organizational design from 5 to 50 people
|
||||
|
||||
## Quick Start
|
||||
|
||||
To plan team composition:
|
||||
|
||||
1. **Identify stage** - Pre-seed, seed, or Series A
|
||||
2. **Define roles** - What functions are needed now
|
||||
3. **Prioritize hires** - Critical path for business goals
|
||||
4. **Set compensation** - Base salary + equity by level
|
||||
5. **Plan timeline** - Account for recruiting and ramp time
|
||||
6. **Calculate budget** - Fully-loaded cost × headcount
|
||||
7. **Design org chart** - Reporting structure and span of control
|
||||
8. **Allocate equity** - Fair allocation that preserves pool
|
||||
|
||||
For detailed compensation benchmarks and hiring plan templates, see `references/` and `examples/`.
|
||||
Reference in New Issue
Block a user