cwinvestments/memstack-business-financial-model

Financial Model — Building financial projections...

Builds monthly revenue projections, expense forecasts, unit economics (CAC, LTV, payback), break-even analysis, cash flow tracking, and scenario modeling (best/base/worst).

Activation

When this skill activates, output:

Financial Model — Building financial projections...

Then execute the protocol below.

Context Guard

| Context | Status | |---------|--------| | User says "financial model", "projections", "revenue forecast" | ACTIVE | | User mentions MRR, churn, CAC, LTV, runway, or break-even | ACTIVE | | User wants to forecast revenue, expenses, or cash flow | ACTIVE | | User wants to set pricing tiers | DORMANT — use Pricing Strategy | | User wants to generate an invoice | DORMANT — use Invoice Generator |

Common Mistakes

| Mistake | Why It's Wrong | |---------|---------------| | "Hockey stick revenue" | Realistic projections beat optimistic fantasies. Start conservative, model scenarios. | | "Forget to model churn" | SaaS without churn modeling is fiction. Even 3% monthly churn compounds fast. | | "Revenue only, no expenses" | Revenue without expenses is a dream. Model all costs to see actual profitability. | | "One scenario only" | A single forecast is a guess. Model best/base/worst to understand the range. | | "Skip unit economics" | If CAC > LTV, growth loses money. Unit economics tell you if the business model works. |

Protocol

Step 1: Gather Business Data

If the user hasn't provided details, ask:

1. Business model — SaaS, e-commerce, service, marketplace, or other?
2. Revenue streams — subscriptions, one-time sales, services, ads?
3. Current numbers — existing revenue, customers, growth rate?
4. Pricing — price points, tiers, average revenue per user?
5. Costs — known fixed and variable costs?
6. Funding — bootstrapped or funded? Current cash balance?

Step 2: Revenue Model

SaaS / Subscription revenue:

Month N Revenue = (Previous customers - Churned + New) × ARPU

Where:
- Previous customers: end of prior month
- Churned: Previous × monthly churn rate
- New: Acquired through marketing/sales
- ARPU: Average Revenue Per User (monthly)

| Month | Starting | New | Churned | Ending | MRR | ARR | |-------|---------|-----|---------|--------|-----|-----| | 1 | 0 | [X] | 0 | [X] | $[X] | — | | 2 | [X] | [X] | [X] | [X] | $[X] | — | | 3 | [X] | [X] | [X] | [X] | $[X] | — | | ... | | | | | | | | 12 | [X] | [X] | [X] | [X] | $[X] | $[X] |

E-commerce / Transaction revenue:

Monthly Revenue = Visitors × Conversion Rate × Average Order Value

Where:
- Visitors: Monthly unique visitors (organic + paid)
- Conversion Rate: % of visitors who purchase (target: 1-3%)
- AOV: Average Order Value

Service revenue:

Monthly Revenue = Active Clients × Average Monthly Retainer
  + Project Revenue (one-time)

Step 3: Unit Economics

Key SaaS metrics:

CAC (Customer Acquisition Cost):
  = Total Sales & Marketing Spend ÷ New Customers Acquired
  Target: recover within 12 months

LTV (Customer Lifetime Value):
  = ARPU × Gross Margin% × (1 ÷ Monthly Churn Rate)
  Example: $50 × 80% × (1 ÷ 0.05) = $800

LTV:CAC Ratio:
  = LTV ÷ CAC
  Target: > 3:1 (every $1 spent acquires $3+ in lifetime value)

Payback Period:
  = CAC ÷ (ARPU × Gross Margin%)
  Example: $200 ÷ ($50 × 80%) = 5 months
  Target: < 12 months

Unit economics table:

| Metric | Value | Target | Status | |--------|-------|--------|--------| | ARPU (monthly) | $[X] | — | — | | Monthly churn rate | [X]% | <5% | [OK / At Risk] | | CAC | $[X] | — | — | | LTV | $[X] | >3× CAC | [OK / At Risk] | | LTV:CAC ratio | [X]:1 | >3:1 | [OK / At Risk] | | Payback period | [X] months | <12 months | [OK / At Risk] | | Gross margin | [X]% | >70% (SaaS) | [OK / At Risk] |

Step 4: Expense Forecast

Fixed costs (monthly):

| Category | Monthly Cost | Annual Cost | Notes | |----------|-------------|-------------|-------| | Salaries & wages | $[X] | $[X] | [Headcount × avg salary ÷ 12] | | Office / co-working | $[X] | $[X] | | | Software & tools | $[X] | $[X] | [List: hosting, SaaS tools, etc.] | | Insurance | $[X] | $[X] | | | Legal & accounting | $[X] | $[X] | | | Total fixed | $[X] | $[X] | |

Variable costs (scales with revenue):

| Category | Cost Basis | Monthly Estimate | Notes | |----------|-----------|-----------------|-------| | Hosting / infrastructure | [X]% of revenue | $[X] | Scales with users | | Payment processing | 2.9% + $0.30/txn | $[X] | Stripe standard rate | | Customer support | $[X] per 100 customers | $[X] | | | Sales commissions | [X]% of new revenue | $[X] | | | Marketing spend | $[X] fixed + [X]% of revenue | $[X] | | | Total variable | | $[X] | |

Total monthly burn:

Burn Rate = Fixed Costs + Variable Costs - Revenue
Runway = Cash Balance ÷ Monthly Burn Rate

Step 5: Break-Even Analysis

Break-Even Point (customers):
  = Fixed Costs ÷ (ARPU - Variable Cost per Customer)

Break-Even Point (revenue):
  = Fixed Costs ÷ Gross Margin%

Example:
  Fixed costs: $10,000/month
  ARPU: $50/month
  Variable cost per customer: $10/month
  Break-even: $10,000 ÷ ($50 - $10) = 250 customers

Monthly P&L projection:

| | Mo 1 | Mo 3 | Mo 6 | Mo 12 | |---|---|---|---|---| | Revenue | $[X] | $[X] | $[X] | $[X] | | COGS / variable costs | ($[X]) | ($[X]) | ($[X]) | ($[X]) | | Gross profit | $[X] | $[X] | $[X] | $[X] | | Gross margin % | [X]% | [X]% | [X]% | [X]% | | Operating expenses | ($[X]) | ($[X]) | ($[X]) | ($[X]) | | Net income | ($[X]) | ($[X]) | $[X] | $[X] | | Cumulative cash | $[X] | $[X] | $[X] | $[X] |

Step 6: Scenario Modeling

Three scenarios:

| Assumption | Worst Case | Base Case | Best Case | |-----------|-----------|----------|----------| | Monthly new customers | [X] | [X] | [X] | | Monthly churn rate | [X]% | [X]% | [X]% | | ARPU | $[X] | $[X] | $[X] | | Marketing spend | $[X] | $[X] | $[X] | | Hiring timeline | Delayed | On time | Accelerated |

12-month outcome by scenario:

| Metric | Worst | Base | Best | |--------|-------|------|------| | Customers (Mo 12) | [X] | [X] | [X] | | MRR (Mo 12) | $[X] | $[X] | $[X] | | ARR (Mo 12) | $[X] | $[X] | $[X] | | Monthly burn (avg) | $[X] | $[X] | $[X] | | Break-even month | Mo [X] | Mo [X] | Mo [X] | | Runway remaining | [X] months | [X] months | [X] months | | Cash needed | $[X] | $[X] | $0 |

Step 7: Cash Flow Summary

Monthly cash flow:

| Month | Revenue | Expenses | Net | Cumulative | |-------|---------|----------|-----|------------| | 1 | $[X] | $[X] | ($[X]) | $[X] | | 2 | $[X] | $[X] | ($[X]) | $[X] | | 3 | $[X] | $[X] | ($[X]) | $[X] | | ... | | | | | | 12 | $[X] | $[X] | $[X] | $[X] |

Key dates:

• Cash-flow positive: Month [X] (when monthly net turns positive)
• Break-even (cumulative): Month [X] (when cumulative losses are recovered)
• Runway exhausted: Month [X] at current burn (worst case)

Output Format

# Financial Model — [Business Name]

## Revenue Model
[From Step 2 — monthly revenue projections]

## Unit Economics
[From Step 3 — CAC, LTV, payback, margins]

## Expense Forecast
[From Step 4 — fixed + variable costs]

## Break-Even Analysis
[From Step 5 — break-even point + P&L]

## Scenario Analysis
[From Step 6 — worst/base/best]

## Cash Flow
[From Step 7 — monthly cash flow + key dates]

## Key Assumptions
[List every assumption with the value used]

Completion

Financial Model — Complete!

Business model: [Type]
12-month ARR (base case): $[X]
Break-even: Month [X]
LTV:CAC ratio: [X]:1
Runway: [X] months
Scenarios modeled: 3 (worst/base/best)

Next steps:
1. Validate assumptions with real data (update monthly)
2. Track actual vs projected monthly
3. If LTV:CAC < 3:1, reduce CAC or increase ARPU before scaling
4. If runway < 6 months, raise capital or cut burn
5. Update the model quarterly with actuals

Level History

• Lv.1 — Base: Revenue models (SaaS, e-commerce, service), unit economics (CAC, LTV, payback, LTV:CAC, gross margin), expense forecast (fixed + variable), break-even analysis with P&L projection, 3-scenario modeling (worst/base/best), cash flow timeline with key dates (cash-positive, break-even, runway). (Origin: MemStack Pro v3.2, Mar 2026)