Startkeel · Financial model

Example financial model

Real figures

martech · pre-seed · PLG · 36-month projection

Verdict

⚠️ Default alive — but one thing is holding you back

You reach break-even in month 1 without exhausting cash — but that only holds if you fix the problem below first.

The first thing to fix

⚠️Tight unit economics
Each customer is worth about 2.1× what it costs to win them (LTV:CAC) — healthy is 3 or more. To get there, bring the cost of winning one from $578 to ~$400, or charge more / keep them longer. Early on it's a rough guide, not a verdict.

Viability score

75/100

Viability score

On track

Solid foundation. Keep an eye on the amber items as you scale.

At risk

0–39

Fragile

40–59

On track

60–79

Strong

80–100

Survivali

Unit economicsi

Retentioni

Growthi

Efficiencyi

Orientative, not absolute — weighted from survival, unit economics, retention, growth and efficiency against early-stage SaaS ranges (§9). Read it by stage, not as a grade.

Does your business hold up?

RunwayiRunway at today's burn rate — a conservative floor (if nothing improves). If your growth plan plays out, cash can last longer, or never run out — see the projected cash-out. "36+" means you're not burning cash.

36+ months

Final MRRiProjected monthly recurring revenue at the end of the horizon.

$18,413

Avg MoM growthiAverage month-over-month MRR growth in the projection.

2.0%

Annual NRRiNet Revenue Retention: % of revenue you keep and expand from existing customers over a year, excluding new ones. >100% = you grow without selling.

61%

Cash over time

Cash isn't exhausted within the horizon (break-even in month 1).

MRR and active customers

MRR ($, left axis) · active customers (right axis)

Projection assumes your growth holds flat for 3 years; real growth usually slows, so later months read optimistic.

Team cost ramp

Loaded headcount cost per month ($).

Unit economics and burn

ARPAiAverage revenue per customer per month (MRR ÷ active customers).

$75

LTViCustomer lifetime value: ARPA × gross margin ÷ churn. What a customer leaves you on average while they stay.

$1,200

CACiCost to acquire a customer: sales/marketing spend ÷ new customers.

$578

LTV : CACiHow much a customer is worth vs what it costs to acquire them. Healthy ≥3 (mature SaaS reference).

2.1×

CAC paybackiMonths to recover CAC with the customer's margin. <12 strong; usually higher early-stage.

9.6 months

Monthly net burniWhat you burn per month = OpEx − gross profit. Negative = you make money.

$51

Burn multipleiHow much you burn per $ of new ARR. ≤1 excellent; at pre-seed 2.5-3.4x is normal.

0.2

Rule of 40iAnnual growth % + EBITDA margin %. ≥40 signals a healthy balance — but it is a scale-up metric, less meaningful before Series A.

Magic numberiSales efficiency: new ARR ÷ prior sales/marketing spend. >0.75 healthy.

2.23

Quick ratioi(New + expansion) ÷ (churn + contraction). >4 = you grow much faster than you lose.

1.7

Diagnosis vs benchmarks

Metric	Your value	Healthy range	Verdict
Monthly logo churniChurn = the % of customers who cancel each month. 5%/mo ≈ losing ~46% of customers a year.	5%/mo	2.5%–4%/mo	⚠️
NRR (annual)iNRR = net revenue retention: revenue kept from existing customers a year later, after churn and upgrades. Over 100% = you grow even with zero new customers.	61.3%	90%–110%	⚠️
Gross marginiGross margin = % of revenue left after the direct cost of serving customers (hosting, fees, support).	80%	75%–85%	✅
CAC paybackiCAC payback = how many months a customer takes to repay what it cost to acquire them.	9.6 m	≤ 18 m (pre-seed)	✅
LTV : CACiLTV:CAC = how much a customer is worth over their lifetime versus what it costs to win them. 3+ is healthy.	2.1×	≥ 3×	⚠️
Growth MoMiMoM growth = month-over-month growth: how much this number grows each month, compounding.	2.0%	≤ 40% (base 9K)	✅
Burn multipleiBurn multiple = cash burned for each unit of new annual revenue you add. Lower is better; under 2 is solid.	0.2	≤ 3.5 (pre-seed)	✅

Churn and retention are judged against your price band (ARPA $50-500/mo) — cheaper products churn more, and that is normal. ✅ healthy · ⚠️ watch · 🚩 flag · ℹ️ too optimistic · — N/A.

These are a reference for your stage, not a verdict: many "healthy" ranges were set for mature SaaS. At pre-seed/seed a high burn multiple (≈2.5-3.4x) or long CAC payback is normal while you find traction. Use them to orient yourself, not to punish yourself.

Scenarios & sensitivity

	Pessimistic	Base	Optimistic
Verdict	🔴	✅	✅
Cash-out month	22 mo	> 36 mo	> 36 mo
Break-even	—	1 mo	1 mo
Final MRR	8,432	18,413	40,350
Final cash	-57,905	38,399	194,212

Your survival depends on things going roughly to plan — the pessimistic case runs out of cash. Build a buffer. Each adjusts growth, churn, OpEx and price together — a realistic range, not a promise.

What moves your runway most

These are the levers you can change, ranked by how much each moves your cash. Start at the top - that's where your effort pays off most. Each lever is moved on its own, with the rest held fixed; in reality they interact.

Each lever moved ±10% on its own — green helps your final cash, amber hurts it.

Higher price-34,305 · +34,305

Lower OpEx-20,716 · +20,716

Lower churn-17,593 · +19,205

Faster growth+3,310 · -3,887

P&L — monthly year 1, annual thereafter

$	M1	M2	M3	M4	M5	M6	M7	M8	M9	M10	M11	M12	Year 2	Year 3
Revenue	8,978	8,969	8,976	8,996	9,031	9,081	9,144	9,223	9,316	9,424	9,546	9,684	132,779	185,672
Gross profitiRevenue minus the direct cost of delivering your service (hosting, payment fees, support). What's left to cover everything else.	7,182	7,176	7,181	7,197	7,225	7,265	7,316	7,378	7,453	7,539	7,637	7,747	106,223	148,537
OpExiOperating expenses: everything you spend to run the business — team, sales & marketing, tools, admin, R&D.	-7,125	-7,229	-7,337	-7,450	-7,567	-7,688	-7,815	-7,946	-8,083	-8,226	-8,374	-8,528	-116,848	-154,441
Team	-4,375	-4,375	-4,375	-4,375	-4,375	-4,375	-4,375	-4,375	-4,375	-4,375	-4,375	-4,375	-52,500	-52,500
S&M	-2,600	-2,704	-2,812	-2,925	-3,042	-3,163	-3,290	-3,421	-3,558	-3,701	-3,849	-4,003	-62,548	-100,141
G&A	-50	-50	-50	-50	-50	-50	-50	-50	-50	-50	-50	-50	-600	-600
Infra	-100	-100	-100	-100	-100	-100	-100	-100	-100	-100	-100	-100	-1,200	-1,200
EBITDAiOperating-profit proxy (earnings before interest, taxes, depreciation and amortization). Negative = you're burning cash; positive = profitable.	57	-53	-157	-253	-342	-424	-499	-568	-631	-687	-737	-780	-10,624	-5,904

Diagnosis

On track on cash — but you’re leaking customers. Retention is your #1 fix.

What this means

Will you survive?
In short: the cash math works — you reach break-even around month 1 before running low on cash. But that projection only holds if the problem below gets fixed first.
What's your biggest problem?
Your biggest problem is retention. You're losing about 5% of your customers every month — over a year that's most of your base walking out the door, which is why only 61% of this year's revenue would still be here next year. Until you fix this, every new customer partly replaces one you lost: you're filling a leaky bucket.
Do you make money on each customer?
On the per-customer maths: it costs about $578 to win a customer, and each is worth roughly $1,200 over their lifetime — about 2.1 to 1 (healthy is 3 to 1+). The good news: most of that gap is the churn problem. Keep customers longer and each one is worth more automatically, lifting this ratio on its own.
What do you fix first?
What to focus on first: find out why customers leave and fix it. Getting the % of customers who leave (churn) down toward 2.5% a month is the single lever that improves your retention, your customer value and your growth ceiling at the same time.

What to look at first

⚠️Net revenue retention is low
Your existing customers bring in 61% of last year's revenue (NRR) — low even for your price band. Cheap self-serve rarely clears 100%, so that alone is not the problem; being below what similar-priced products retain is. Win it back with upsells/expansion or by lowering churn.

Second opinion from your AI

Analyze this model in your own AI

Copy a ready-made prompt with your numbers, paste it into ChatGPT, Claude or any AI, and get a skeptical second opinion — red flags, what's strong, and what to fix next.

Runs in YOUR AI — we don't see it or store it. AI can make mistakes; treat it as a second opinion, not gospel. The prompt tells it not to invent numbers, but always sanity-check.