From memstack
Builds monthly financial projections including revenue forecasts, expense modeling, unit economics (CAC, LTV, payback), break-even analysis, cash flow tracking, and best/base/worst scenarios for SaaS and other businesses.
npx claudepluginhub cwinvestments/memstack --plugin memstackThis skill uses the workspace's default tool permissions.
*Builds monthly revenue projections, expense forecasts, unit economics (CAC, LTV, payback), break-even analysis, cash flow tracking, and scenario modeling (best/base/worst).*
Builds 3-5 year financial models for startups with cohort-based revenue projections, operating expense breakdowns, cash flow analysis, burn rate, runway, and headcount planning.
Models unit economics (LTV/CAC, payback), calculates burn rate and runway, forecasts revenue bottom-up, analyzes pricing, and builds 24-month financial projections for startups.
Builds 3-5 year financial models for startups with cohort revenue projections, cost structures, cash flow, headcount plans, burn rate, runway, and scenario analysis.
Share bugs, ideas, or general feedback.
Builds monthly revenue projections, expense forecasts, unit economics (CAC, LTV, payback), break-even analysis, cash flow tracking, and scenario modeling (best/base/worst).
When this skill activates, output:
Financial Model — Building financial projections...
Then execute the protocol below.
| 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 |
| 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. |
If the user hasn't provided details, ask:
- Business model — SaaS, e-commerce, service, marketplace, or other?
- Revenue streams — subscriptions, one-time sales, services, ads?
- Current numbers — existing revenue, customers, growth rate?
- Pricing — price points, tiers, average revenue per user?
- Costs — known fixed and variable costs?
- Funding — bootstrapped or funded? Current cash balance?
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)
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] |
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
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] |
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 |
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:
# 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]
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