Case study · full TrustMRR database

What actually makes a SaaS money

A data-scientist's read of every one of the 7,992 startups with payment-verified revenue on TrustMRR — not just the winners. Revenue in USD; "30-day" = trailing 30 days, "all-time" = lifetime verified.

Jump to: Baseline· Time to money· Best ideas· Pricing & model· Margins· Audience· Traffic· Momentum & M&A· Cohorts· Payments/geo· Stack & channels· The boom· Playbook

1. The honest baseline: most make almost nothing

Survivorship bias is the enemy of good startup decisions. Across the entire database — winners and ghosts alike — here's where lifetime revenue actually lands.

All-time revenue distribution (all 7,992)

lifetime verified revenue per startup

68% never cross $1,000 in total revenue. The median startup has earned essentially nothing. This is the base rate every founder fights.

~17% reach $1k–$10k, ~10% reach $10k–$100k, only ~5% pass $100k lifetime. Just 77 (1%) have cleared $1M.

Clearing your first $1k already beats two-thirds of everyone who tried. Treat it as the first real milestone.

Revenue is brutally concentrated

Lorenz curve — cumulative share of all 30-day revenue vs. cumulative share of startups (ranked low → high)

The top 10 startups capture 54% of all current revenue; the top 1% take 77%, the top 10% take 97%, and the bottom half earns ~0%. Gini = 0.97 — near-total inequality.

Lifetime it's starker still: Gumroad alone is 59% of all revenue ever recorded here, and the top 10 are 80%. This is a power-law game — a few winners, a long tail of near-zero.

2. How long until the money comes

Using each startup's founding date and lifetime revenue, the median age of companies at each revenue level — a realistic "time to get there."

Median months to reach each revenue milestone

all-time revenue tier · median company age (months)

~11–12 months is the typical age of startups in the $1k–$10k band. The first thousand dollars usually takes the better part of a year.

~19 months for $10k–$100k, ~33 months for $100k–$1M, ~5+ years for $1M+. Revenue compounds slowly.

Founded-date is a proxy and survivors skew these down — read as "fast lane" timings.

3. Which ideas actually make money

Two honest lenses: % of a category that ever reaches $1k (your odds) and median revenue among those who do earn (the payoff). Plain averages mislead because most startups earn $0.

categories with 20+ startups

Category scoreboard

earners = making >$0 · reachers = lifetime ≥ $1k

AI is the crowd, not the cushion. 1,780 startups (22%) — but only 35% reach $1k and median earners make ~$200/mo.

Best odds of $1k: E-commerce (52%), Marketplace & Sales (40%), Education (39%), Security (38%), Marketing (36%).

Biggest payoff: Marketplace (~$1.5k/mo median earner), Sales (~$840), Security & E-commerce (~$450).

4. Pricing & business model

What do these startups actually charge — and does a subscription beat one-time sales? Price point = median monthly revenue per active subscription.

Monthly price-point distribution

revenue per active subscription · median is just /mo

Indie SaaS is cheap and high-volume: ~64% of priced startups charge under $30/mo. B2B charges 3× B2C (median $28 vs $9). Highest price points: Sales ($81), Customer Support ($49), Marketing ($31).

Recurring vs one-time — and price by category

left: median $/mo among earners by model · right table: median price by category

Subscriptions win: recurring businesses earn a median $215/mo vs $99/mo for one-time/usage — more than double — and they compound. Default to a subscription if the problem is recurring.

How many customers to hit each MRR milestone

median active subscriptions by MRR tier (subscription startups)

At a ~$13 price point it adds up fast: ~18 paying customers for the first few hundred a month, ~90 for $1k–$5k MRR, ~290 for $5k–$20k, and ~770 for $20k+.

The median earning subscription business has just 8 active subscribers — most are tiny. A few hundred true fans is already a real business.

5. Profit margins: software is cheap to run

Of the 3,178 startups reporting it, the median 30-day profit margin is 80%. This is software's superpower — once built, each new customer is almost pure profit.

Profit-margin distribution

last-30-day profit margin

Median margin by category

categories with 20+ reporting

The most automatable categories run near-pure margin: Mobile Apps, Utilities, Developer Tools, Games and No-Code all median ~90%. Even the "lowest" categories sit at 80%+. Low overhead is the norm, not the exception.

6. Do you need a big audience?

Short answer: no. A following helps you get started, but it's a surprisingly weak predictor of how much you'll actually make.

Followers vs. odds and size of revenue

enriched sample · bars = median $/mo (earners), line = % that earn

A following mainly lifts your odds of earning — 49% → 60% → 90% as followers grow from <1k to 10k–100k — but barely predicts how much: median revenue among earners stays modest (~$190 → ~$780). The overall link is weak (r = 0.21, n = 666). Reach gets you in the game; it doesn't size the prize.

...but you can win quiet

top earners in the sample with < 1,000 followers

Plenty of $40k–$480k/mo products run on well under 1,000 followers — some on just 11–88. Audience is a tailwind, not a gate.

7. Traffic & conversion efficiency

For the 1,320 startups with traffic data: how much website traffic translates into money, and who monetizes it best. Median revenue per visitor is .

Revenue vs. monthly traffic

median $/mo among earners, by monthly visitors

More traffic, more money — predictably: <1k visitors → ~$67/mo, 10k–100k → ~$2.4k, 100k+ → ~$5k. But traffic isn't destiny — see the efficiency leaders.

Most efficient monetizers

highest revenue per visitor (with real revenue & traffic)

The best squeeze $15–$66 per visitor — high-intent niches (fintech, B2B, paid tools) where a few hundred visitors fund a real business. Quality of traffic > quantity.

8. Momentum & the acquisition market

Fastest-growing recurring revenue

highest 30-day MRR growth (with MRR ≥ $500) — stickier than one-time spikes

MRR momentum is more meaningful than raw revenue spikes — it's recurring. Still, big % jumps often ride small bases.

The buy-vs-build market

1,808 startups are listed for sale (23% of the database)

listed for sale

median asking price

median revenue multiple

0.07×

cheapest deal multiple

What acquirers pay: multiples by size & category

median price ÷ annualized-revenue multiple among the 996 priced listings

Tiny startups over-ask. Sub-$1k businesses list at a median 4.3× (hope-priced), while real revenue ($1k–$100k/mo) clusters at a sane ~2.1–2.5×. By category, Analytics, Productivity & Fintech command the richest multiples; commodity tools the lowest.

9. Cohorts: time is the cheat code

Group every startup by founding year. Older cohorts have had time to compound — and it shows dramatically.

Success by founding year

bars = % that reached $1k lifetime, line = median $/mo among earners

2020–2021 cohorts: ~84% reached $1k; the 2026 cohort sits at 14% — not because they're worse, but because they're months old. Median earner revenue climbs steadily with age too. The lesson from sections 2 and 9 is the same: survival and time do most of the work.

10. Payments, audience & geography

Payment provider

share of all 7,992

Stripe leads (60%); RevenueCat (14%) + Dodo, Polar & Superwall reveal a big mobile & creator cohort. Whop & Superwall show the highest medians.

B2B vs B2C

median $/mo among earners

B2B earners out-earn B2C ($212 vs $132) and "Both" sells at the richest multiple (4.6×).

Top countries

by number of startups

US leads count & revenue (~$19.7M of ~$31M). India: big volume, low revenue. Poland earns big from few.

11. Tech stack & marketing channels

From the ~1,000-startup enriched sample. Bars = median monthly revenue among earners; (n) = how many use it. Popularity and payoff differ.

Tech stack — median revenue (earners)

(n) = startups in sample using it

Next.js is the runaway default (258 of the sample). But median revenue barely moves across stacks (~$100–$300) — tooling is table stakes, not a differentiator. Stripe- and OpenAI-using builds skew only slightly higher.

Marketing channels — median revenue (earners)

(n) = startups in sample using it

SEO is the most common channel; Facebook, YouTube & Instagram show the highest medians. X/Twitter and Reddit are widely used but low-yield.

12. The gold rush is right now

When all 7,992 startups were founded

89% were founded in 2024 or later

2025 and 2026 alone account for ~5,360 of the 7,992. The cost and time to launch a money-making SaaS have collapsed; the database is overwhelmingly young.

13. The starter's playbook

What 7,992 verified startups would tell someone opening a blank editor tomorrow.

Beat the 68%

Two-thirds never reach $1k. Make crossing your first $1,000 (usually ~6–12 months) the explicit goal; if you stall, change the offer fast.

Pick for odds, not hype

E-commerce tools, marketplaces, sales, education, security give the best shot at $1k and fattest payoff. AI is the most crowded, thinnest median.

Charge recurring, lean B2B

Subscriptions earn ~2× one-time; B2B charges ~3× B2C and sells at higher multiples. Default to a subscription priced for businesses.

An audience helps — isn't a gate

10k+ followers raises your odds of earning to ~90%, but barely changes how much (weak link, r=0.21). Reach helps you start; the product makes the money. No following? Lean on product + SEO — people still hit six figures quiet.

Chase high-intent traffic

The best monetizers earn $15–$69 per visitor. A few hundred high-intent visitors beats floods of cheap traffic. Tooling barely moves revenue — ship on any proven stack and market on 2–3 high-yield channels.

Time is the cheat code

Margins are ~80% and revenue compounds — but slowly. Only ~1% clear $1M. Build for profit and longevity; survival does most of the work.

Methodology. Data pulled live from the TrustMRR API (/api/v1/startups) on 2026-06-30: the complete database of 7,992 startups with payment-verified revenue. Follower, tech-stack and channel figures come from a stratified enriched sample of 1,000 (followers known for 666). Pricing = median revenue per active subscription (startups with subscriptions & MRR > 0); margins from 3,178 reporting startups; traffic/efficiency from 1,320 with visitor data. "% reach $1k" = share with ≥$1k lifetime; "median among earners" uses startups currently making >$0 to avoid zero-inflation. "Time to milestone" and cohort figures use company age and reflect survivors. The 68%-under-$1k figure matches TrustMRR's own published statistic. Descriptive analysis, not investment advice. Source: trustmrr.com · database by Marc Lou · case study by SaaS Araby.

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