Growth Model Design

Purpose

This recipe produces a Growth Model Blueprint — selecting the right primary growth engine (viral, paid, content, sales-led, product-led, or partnership-led) based on unit economics, ACV, and product architecture — plus financial projections and a 90-day test plan. Products are built to fit channels, not the reverse. [src1]

Prerequisites

• PMF confirmed — Sean Ellis score > 40% or strong retention curves — PMF Measurement
• Unit economics calculated — fully-loaded CAC, ARPU, gross margin, LTV, payback period
• Current channel data — how customers are currently acquired, volume and cost per channel
• ACV / deal size clarity — average annual contract value or transaction value
• Product architecture understanding — self-serve capability, onboarding complexity, network effects

Constraints

• PMF must be confirmed. Designing a growth model without PMF accelerates losses. [src1]
• Unit economics must support the model — paid requires LTV:CAC > 3:1, viral requires K-factor > 0.5.
• Concentrate on one primary engine first. Diversifying too early prevents learning. [src2]
• Channel-product fit is non-negotiable — $10/mo ACV cannot support sales-led.
• Test with < $5K before committing — 4-6 week validation window.

Tool Selection Decision

Which growth model?
├── ACV < $100/yr AND self-serve
│   └── PATH A: Viral / PLG — sharing, freemium, referral loops
├── ACV $100-$1K/yr AND self-serve with optional help
│   └── PATH B: PLG + Content — self-serve + content-driven awareness
├── ACV $1K-$10K/yr AND guided onboarding
│   └── PATH C: Content + Paid + PLG Hybrid — inbound + PQLs
├── ACV $10K-$50K/yr AND sales-required
│   └── PATH D: Sales-Led + Content — outbound/inbound hybrid
└── ACV > $50K/yr AND complex implementation
    └── PATH E: Enterprise Sales + Partnership

Execution Flow

Step 1: Map the Growth Engine Decision Matrix

Duration: 1-2 hours · Tool: Spreadsheet

Plot startup on selection matrix using three variables: ACV (determines acquisition budget), product complexity / time-to-value (determines viable channels), and natural distribution advantage (built-in sharing, searchable problem, trust requirements, ecosystem integration). Score each engine 1-5 on fit. [src1]

Verify: All three variables scored, top 2-3 engines identified · If failed: Default to lowest-CAC engine

Step 2: Model Unit Economics for Top Engines

Duration: 1-2 hours · Tool: Spreadsheet

Build unit economics model for each viable engine: PLG (free signups × conversion × ARPU), Content (traffic × conversion), Paid (CPC / conversion chain), Sales (AE cost / deals), Partnership (rev share + sourced deals). Calculate CAC, payback, LTV:CAC, break-even month. [src3]

Verify: Unit economics modeled for 2+ engines · If failed: Use conservative benchmarks, mark as “to validate”

Step 3: Evaluate Channel-Product Fit

Duration: 45-60 minutes · Tool: Spreadsheet

Score each engine on Balfour’s four fits: Market-Product, Product-Channel (weighted 40%), Channel-Model, Model-Market. Primary engine = highest combined score. [src1]

Verify: Four-fits scored, primary engine selected · If failed: If tie, choose shorter time-to-validation

Step 4: Design the Growth Loop

Duration: 1-2 hours · Tool: Document + diagram

Map the specific loop: Input (trigger) → Activation (aha moment) → Value delivery → Output trigger (invite/share/review) → Amplification. Define conversion rate, time delay, key metric, and intervention point at each step. Calculate loop efficiency and K-factor. [src2]

Verify: Complete loop documented with conversion rates · If failed: If loop cannot close, product may need changes

Step 5: Build the 90-Day Test Plan

Duration: 45-60 minutes · Tool: Spreadsheet + document

Design minimum viable test: budget < $5K, 4-6 week duration. Define success criteria (target CAC, K-factor, lead volume) and kill criteria before starting. Engine-specific tests: PLG (ship referral, measure K-factor), Content (publish 8-12 pieces, measure organic conversions), Paid ($2K-$5K ad test), Sales (founder does 20-30 outbound sequences), Partnership (recruit 3-5 partners). [src4]

Verify: Test plan has success/kill criteria, budget, timeline · If failed: If no engine looks viable, problem may be pricing or product

Output Schema

{
  "output_type": "growth_model_blueprint",
  "format": "XLSX + MD",
  "sections": [
    {"name": "engine_ranking", "type": "array", "description": "Engines ranked by four-fits score"},
    {"name": "primary_engine", "type": "string", "description": "Selected primary growth engine"},
    {"name": "unit_economics_by_engine", "type": "object", "description": "CAC, payback, LTV:CAC per engine"},
    {"name": "growth_loop", "type": "object", "description": "Loop steps with conversion rates"},
    {"name": "test_plan", "type": "object", "description": "90-day test with budget and criteria"},
    {"name": "financial_projection", "type": "object", "description": "12-month projection for chosen engine"}
  ]
}

Quality Benchmarks

If below minimum: Model at least the obvious engine (based on ACV) plus one alternative before selecting.

Error Handling

Cost Breakdown

Anti-Patterns

Wrong: Diversifying across 4-5 channels at once

Each channel gets 20% attention, none reaches proficiency, team learns nothing conclusive. [src2]

Correct: Concentrate on one primary engine

Master one growth engine before adding a second. The first engine should be profitable and understood.

Wrong: Copying competitor’s growth strategy

Competitor with $5M funding can afford different CAC than a bootstrapped startup. Product-channel fit is specific to your product.

Correct: Choose based on your four fits

Score your specific product against each channel using the four-fits framework. [src1]

When This Matters

Use this recipe after PMF is confirmed and scaling readiness assessment shows green/yellow across all dimensions. The growth model determines how the startup will acquire customers profitably at scale. Without this, startups either burn cash on unprofitable channels or miss their growth window.