Unit Economics

Also known as: Unit EconomicsPer-Unit ProfitabilityCustomer EconomicsContribution EconomicsMarginal Economics

Unit Profit = (LTV × Gross Margin) − CAC

💡The Concept

Unit economics is the direct revenue and costs associated with a single 'unit' of your business model (usually one customer). If your unit economics are positive, every new customer generates profit. If negative, every new customer accelerates your death. The core calculation: Unit Profit = (LTV × Gross Margin) − CAC. If LTV is $2,000, gross margin is 80%, and CAC is $1,200, unit profit is ($2,000 × 0.80) − $1,200 = $400 per customer. This means each customer eventually contributes $400 toward covering fixed costs and generating profit.

⚠️The Trap

Founders often achieve 'positive unit economics' by excluding fixed costs entirely or misclassifying variable costs. True unit economics must include a fair allocation of all variable costs. The second trap: assuming unit economics stay constant as you scale. They can improve (economies of scale in hosting, support) or worsen (higher CAC from market saturation, more support tickets from less-sophisticated users). Track unit economics by cohort and by scale.

🎯The Action

Calculate profit per unit: (LTV × Gross Margin) − CAC. If this number is negative, do NOT scale. Fix your pricing, reduce CAC, or improve retention first. Scaling negative unit economics is like pouring gasoline on a fire — you burn faster. Once positive, track the 'contribution margin ratio': Unit Profit ÷ Revenue per Customer. This tells you what percentage of each revenue dollar covers fixed costs.

⚡Pro Tips

The most dangerous startups have unit economics that are 'barely positive.' A $50 unit profit per customer means you need 10,000 customers just to cover a 5-person team's salary. The margin of error is zero — one churn spike or CAC increase makes you unprofitable overnight.

Unit economics should improve with scale in SaaS. If they're DECLINING as you grow, something structural is wrong: CAC is rising faster than LTV (market saturation), COGS is scaling linearly (infrastructure inefficiency), or you're attracting lower-quality customers.

VCs will reject companies with negative unit economics unless there's a clear path to positive — with specific milestones and a realistic timeline. 'Unit economics will improve at scale' is not a plan; 'Unit economics turn positive at 1,000 customers because hosting COGS drops from $8/user to $3/user' IS a plan.

🚫Common Myths

✗Myth: “Negative unit economics are acceptable if you're 'investing in growth'”

✓Reality: This logic killed Pets.com, MoviePass, WeWork, and hundreds of other companies. Negative unit economics mean every customer you acquire destroys value. Scaling faster just destroys value faster. Amazon's 'losing money to grow' strategy worked because their unit economics were POSITIVE (they were profitable per transaction) — they were just reinvesting total profits into new business lines.

✗Myth: “Unit economics only matter for startups”

✓Reality: Every business at every stage must have positive unit economics. Uber ran negative unit economics for years (subsidizing rides below cost) and has still barely achieved profitability. They essentially paid users to use the product hoping network effects would eventually allow price increases. It took 14 years and $25B+ in losses.

📊Real-World Case Studies

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MoviePass

2017-2019

failure

MoviePass offered unlimited movie tickets for $9.95/month. A single ticket costs $10-15 at the theater. If a customer saw just ONE movie per month, MoviePass lost $0.05-$5.05 per customer per month. Heavy users ($30-50/month in ticket costs) destroyed unit economics completely. At peak, MoviePass was losing $20-40 per customer per month. They bled $150M+ in cash trying to 'grow their way to profitability' through advertising revenue and data sales that never materialized.

Monthly Subscription

$9.95

Avg Ticket Cost to MoviePass

$12-15

Unit Loss per Customer/month

$20-40

Total Losses Before Shutdown

$150M+

💡 Lesson: MoviePass is the textbook case of negative unit economics at scale. No amount of growth, ad revenue, or 'data monetization' could overcome the fundamental truth: they paid more per customer than they received. The lesson: if your unit cost exceeds your unit revenue, scaling makes the problem worse, not better.

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