Unit economics answers one honest question: does the business earn or burn money? We count the cost of one client (CAC), how much they bring over the whole lifetime (LTV) and check the 3xCAC rule. If LTV is lower - you scale loss, even when revenue grows.
In marketing and sales since 2008 · Worked at
The most common owner trap: revenue grows, the team grows, but profit does not appear. In such cases marketing reports good numbers - leads, conversions, CAC - but the owner does not see money in the till.
The reason is almost always one: the model does not add up at the level of one client. You acquire a client for $63, and over their whole life they bring $50 of profit. The more clients - the bigger the loss. And this is impossible to see in Metrica or lead reports - only by counting unit economics.
Unit economics is an honest answer to whether this business can be scaled at all. Without it, any decision to grow the budget is roulette.
| Metric | Formula | What it shows |
|---|---|---|
| CAC Customer Acquisition Cost | Acquisition spend / number of new clients | What one new client costs |
| ARPU Average Revenue Per User | Average check x purchase frequency per month | What a client pays on average per period |
| LTV Lifetime Value | ARPU x lifetime x margin | What profit a client brings over all time |
| ROMI Return On Marketing Investment | (Profit per client - CAC) / CAC x 100% | Return on acquisition investment |
The key ratio is LTV / CAC. If it is below 1, the business runs in the red. If 1-2, you are on the edge. If above 3 - you can scale. More on the 3xCAC rule below.
The four metrics above are the base. For management decisions three more are often needed. They show not "does the model add up" but "how fast it pays back and how stable it is".
| Metric | Formula | Why count it |
|---|---|---|
| Payback Period CAC payback term | CAC / (ARPU x margin) | After how many months a client starts bringing net profit |
| Churn Rate churn coefficient | Clients lost over period / clients at period start x 100% | How stable the base is; for LTV: lifetime = 1 / churn |
| MRR Monthly Recurring Revenue | Sum of recurring payments per month | Predictable revenue; for subscriptions and services - the key operational metric |
Payback Period is especially important for B2B and subscription models. If a client pays back in 18 months and you plan a one-year strategy - the model fails even with good LTV/CAC. Churn Rate shows how much clients "stick" to the product: at churn above 10% per month LTV is unstable and cannot be used for scaling.
Below are working LTV/CAC ratios I observe in projects. Numbers are averaged: in every niche there are companies at LTV/CAC 1x (not working) and 10x (working great). The reference is the average healthy value, not the "ideal". CAC ranges are approximate, converted to USD.
| Niche | Avg CAC (approx.) | Lifetime | Healthy LTV/CAC |
|---|---|---|---|
| SaaS and subscriptions B2B software, services | $60–600 | 12–36 mo | 4–8× |
| B2B services consulting, marketing, IT | $125–1,250 | 6–24 mo | 3–6× |
| B2B equipment machinery, parts, service | $400–1,900 | 3–7 years | 5–10× |
| Retail shops, cafes | $3–25 | 3–12 mo | 3–5× |
| Online education courses, schools | $20–190 | 1–6 mo | 3–7× |
How to use: if your LTV/CAC is below the niche average - that is a signal the model is not optimized (CAC too high, LTV too low, or both). If above average - there is scaling potential, if confirmed by end-to-end analytics per channel.
The 3xCAC rule came from SaaS but works in any business with repeat sales. Here is why exactly three:
The first "part" of LTV goes to paying back the ads themselves - the CAC you paid for the client.
The second part - for team salaries, rent, service, support. The client is served while bringing money.
The third part - for owner profit, reserves and growth investments. Without it the business does not develop.
If your LTV = 2xCAC - you run almost at zero, and any crisis, ad-cost rise or loss of a key client sends the business into the red. The 3x rule is a safety margin, not an arbitrary number.
Over 10 years working with unit economics I have seen the same calculation mistakes. They lead to the model "adding up" on paper while there is no money in the till.
Take a software subscription for small business. All numbers are simplified to show the logic.
| Parameter | Value |
|---|---|
| Monthly marketing spend | $6,250 |
| New paying clients per month | 100 |
| CAC (6,250 / 100) | $63 |
| Average check (subscription) | $38/mo |
| Average client lifetime | 14 months |
| Margin | 70% |
| LTV (38 × 14 × 0.7) | $372 |
| LTV / CAC | 5.9× |
| Payback Period (63 / (38 × 0.7)) | 2.4 months |
| Verdict | Model adds up. Can scale. |
LTV / CAC = 5.9× is a healthy model. Even if ad cost doubles (CAC ≈ $125), LTV / CAC stays around 2.9–3.0×, and the business still runs in profit. Payback Period 2.4 months is fast: the client starts bringing net profit already in the third month.
Enter your numbers - the calculator counts CAC, LTV and the ratio. Data stays in the browser, nothing is sent anywhere.
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So you do not set up formulas from scratch, here is the ready table structure I use in projects. Copy into Excel or Google Sheets and fill your data.
| Cell | Content | Formula |
|---|---|---|
| A1 | Marketing spend (quarter) | number |
| B1 | New clients (quarter) | number |
| C1 | CAC | =A1/B1 |
| A2 | Average check | number |
| B2 | Purchase frequency per month | number |
| C2 | ARPU | =A2*B2 |
| A3 | Lifetime (months) | number |
| B3 | Margin | 0.7 |
| C3 | LTV | =C2*A3*B3 |
| A4 | LTV / CAC | =C3/C1 |
| B4 | Payback Period | =C1/(C2*B3) |
For advanced calculation add tabs by segments (by channels, by products, by cohorts) and compare LTV/CAC between them. A 2-3x difference between segments is common, and it is exactly what shows where the business earns and where it loses.
The store grew in revenue but net profit stood still. We counted unit economics by product categories: some categories ran in the red - low margin and high churn (clients bought once and left). The solution was not advertising but assortment: we removed unprofitable items and focused on those with LTV/CAC > 3. Over a quarter profit grew 18% at the same revenue.
The company thought leads were too expensive (CAC $1,060) and wanted to cut the budget. We counted LTV including repeat orders over 5 years - it turned out to be $8,000. LTV/CAC = 7.5×. Decision: not cut, but scale the most profitable channels. Budget doubled, revenue grew 2.3x.
After counting unit economics the question arises: what to do with it? Below are typical decisions for each scenario.
| LTV / CAC | Diagnosis | What to do |
|---|---|---|
| < 1× | Business in the red: a client brings less than it costs to acquire | Fix the model urgently: raise prices, cut CAC, grow LTV. Do not scale ads. |
| 1–2× | Business on the edge: runs almost at zero, vulnerable to crises | Optimize: find the most expensive and cheapest channels, turn off draining ones, focus on retention. |
| 2–3× | Healthy business but no safety margin | Scale carefully: grow budget on best channels, watch churn. |
| 3–5× | Good model with a margin | Scale aggressively: grow budget, enter new channels and regions. |
| > 5× | Excellent model, possibly underinvestment in growth | Invest in growth: grow budget until LTV/CAC drops to 3×. |
Unit economics answers "does the business model add up?". End-to-end analytics answers "which channel gives clients with the best LTV/CAC?"
The right order is: first count units and understand the model adds up. Then connect end-to-end analytics and scale only the channels where LTV/CAC > 3. Without unit economics, end-to-end analytics shows where leads are cheaper - but not whether those leads bring profit.
Together these two tools close 90% of marketing management decisions.
So there are no expectations of "I thought this was included too" - I fix the project boundaries upfront.
| Element | Included | Not included |
|---|---|---|
| CAC, LTV, ROMI calculation by cohorts | ✓ | |
| Segmentation by channels and products | ✓ | |
| Finding unprofitable segments | ✓ | |
| Excel/Google Sheets template for your business | ✓ | |
| Action plan with numbers and priorities | ✓ | |
| Setting up end-to-end analytics | separate project | |
| CRM and call-tracking implementation | separate project | |
| Ad-campaign optimization | included in lead generation |
10+ years in B2B marketing. Worked as marketing director in companies with revenue from $1M to $25M, now a fractional CMO for B2B companies in Russia, UAE, Thailand, Kazakhstan and Turkey. Specialization - unit economics, end-to-end analytics, building lead-gen systems with predictable CAC. I run marketing and trade-show-preparation audits and speak at industry conferences.
Unit economics is the tool I use in every project as the first step. Without understanding whether the model adds up, any budget decision is guessing. If you feel that "revenue grows but there is no money" - most likely the reason is in unit economics, not in marketing.
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