Why Startups Fail: What the 90% Statistic Really Means and the Root Causes Behind It
Quick answer: why startups fail
Most startups fail because they run out of money before they find something people will repeatedly pay for. US Bureau of Labor Statistics data shows about 20% of new private-sector establishments close in year one and roughly 65% within ten years. Among venture-backed companies, CB Insights found 70% of recent shutdowns ran out of capital and 43% never reached product-market fit. The famous 90% figure is not a measure of closed businesses at all.
The failure numbers founders repeat to each other are mostly true and mostly misunderstood. They come from different populations, measure different things, and get quoted without the definition that made them meaningful.
This guide sticks to sourced figures. It shows where the 90% claim comes from, what the government data actually says about failure rates by year and industry, why running out of cash is usually a symptom rather than a cause, and the warning signs that show up before the money does run out. So why do startups fail? In plain terms, they spend real money on demand they never confirmed.
Is It True That 90% of Startups Fail?
The claim that 90% of startups fail is repeated so often that it reads like a law of nature. It is closer to a definition problem. Failory's review of the research traces the 9-in-10 claim back to the Startup Genome project, whose own reports put success at only about 1 in 12 entrepreneurs. No US government agency publishes a 90% startup failure rate, and the number travels without the population or the definition that produced it.
Measured as closures instead, the picture changes completely. Of the US private-sector establishments born in March 2013, 79.6% survived one year, 50.6% reached five years, and 34.7% were still operating in March 2023, according to the Bureau of Labor Statistics. That is roughly 2 in 10 closing in year one and about 2 in 3 within a decade, not 9 in 10.
The definition changes the number
| Who is measured | What counts as failure | Reported rate | Source |
|---|---|---|---|
| All new US private-sector establishments | The business closes | About 20% in year 1, about 49% by year 5, about 65% by year 10 | BLS |
| Venture-backed companies | Never returns cash to investors | As many as 75% | Failory on Shikhar Ghosh (HBS) |
| Venture-backed companies, same analysis | Investors lose their initial investment | 30% to 40% of cases | Failory on Shikhar Ghosh (HBS) |
| Entrepreneurs tracked by Startup Genome | Never builds a business the data counts as a success | Only about 1 in 12 succeed | Failory on Startup Genome |
So the honest answer to "is it true that 90% of startups fail" is: not as a rate of businesses closing. It survives as a rough shorthand for venture outcomes, where success is judged on returning capital rather than on staying open. If you are running a services firm, an agency or a local business, the numbers that apply to you are the government survival rates, and they are a lot less bleak.
Startup Failure Rate by Year, Industry and Funding Stage
There is no single startup failure rate. There is a survival curve, and where you sit on it depends on how long you have been operating, what you sell, and whether outside investors set your spending pace.
Failure rate by year
These are US private-sector establishments born in March 2013, tracked by the Bureau of Labor Statistics through March 2023.
| Years in business | Still operating | Closed |
|---|---|---|
| 1 year | 79.6% | 20.4% |
| 5 years | 50.6% | 49.4% |
| 10 years | 34.7% | 65.3% |
The most recent cohort tells a similar story. Establishments that opened in the year ended March 2024 had a one-year survival rate of 77.9% as of March 2025, so about 22% closed within twelve months, per the BLS survival table. Notice the shape of the curve: the steepest losses are early. Businesses that clear year five are far likelier to reach year ten than new businesses are to reach year five.
Failure rate by industry
Ten-year survival for the same 2013 cohort, by sector. The information sector, where most software and media startups sit, is near the bottom.
| Industry | Still operating after 10 years | Note |
|---|---|---|
| Agriculture, forestry, fishing and hunting | 50.5% | Highest 10-year survival |
| Utilities | 45.7% | Capital heavy, slow moving |
| Manufacturing | 43.6% | Long contracts, high switching costs |
| Wholesale trade | 30.1% | Thin margins |
| Information (software, media, data) | 29.1% | Where most tech startups sit |
| Mining, quarrying, oil and gas extraction | 24.5% | Lowest 10-year survival |
Construction showed the sharpest first-year drop of any sector in that cohort, according to the same BLS analysis.
Failure rate by funding stage
Venture funding changes the failure profile rather than removing it. Harvard Business School lecturer Shikhar Ghosh told the Wall Street Journal that 75% of venture-backed companies never return cash to investors, and that in 30% to 40% of cases investors lose their initial investment, figures summarized by Failory.
More recently, in a report published in March 2026, CB Insights analyzed 431 venture-backed companies that shut down from 2023 onward. Together they had raised $17.5 billion, with a median raise of $11 million, and the median time from last fundraise to failure was 22 months. Funding buys time, and the clock still runs.
Bootstrapped businesses fail differently. They rarely die from a missed Series A. They stall, revenue plateaus, the founder takes on client work to cover costs, and the company quietly stops being a startup. That outcome does not appear in venture failure datasets at all.
Why Startups Fail: Root Causes vs Final Causes
"Ran out of money" is the cause of death written on most startup certificates, and it explains almost nothing. In the CB Insights dataset it tops the list at 70%, and CB Insights itself describes it as the final cause rather than the root problem.
Every company that closes runs out of money. The question that matters is what consumed the money. In practice it is one of three things: the product never found buyers who would pay repeatedly, the economics of each sale never worked, or the business scaled costs ahead of proven demand. The percentages in the same study line up with that: poor product-market fit at 43%, bad timing at 29%, unsustainable unit economics at 19%. Those shares cover the 385 companies CB Insights could assign a reason to, and many companies cited more than one, so the figures add to more than 100%.
Final cause: the bank balance hits zero and payroll cannot clear.
Root cause: demand was assumed rather than tested, so revenue never compounded.
Root cause: each sale cost more to deliver than it brought in, so volume made it worse.
Root cause: headcount and spend were sized for a growth rate that had not been earned yet.
This distinction matters because founders respond to the final cause. They cut costs, extend runway and go back out to raise. If the root cause is unaddressed, a longer runway only buys a later version of the same ending.
The 8 Most Common Reasons Startups Fail
Each of these reasons startups fail is drawn from a named study rather than folklore. The fixes live in a companion guide: see common startup mistakes and how to fix them for the detailed corrections.
No Product-Market Fit
Of the 385 venture-backed shutdowns CB Insights could assign a cause to, 43% had poor product-market fit. In the Wilbur Labs survey, 54% of founders said the biggest lesson from failure was understanding product-market fit better.
Root cause: The team validated interest, not willingness to pay. Enthusiasm in discovery calls is not the same as a signed order or a renewed subscription.
The fix belongs upstream, in validation and research.
Running Out of Capital
70% of those 385 shutdowns ran out of capital, making it the single most reported cause in the CB Insights dataset.
Root cause: This is almost always the final cause, not the root one. Cash runs out because the business could not convert spend into repeatable revenue fast enough.
Treat runway as a symptom monitor rather than the disease itself.
Bad Timing and Macro Conditions
29% of that same group were attributed to bad timing or macro conditions, and CB Insights found the effect concentrated in climate and energy, food and agriculture, and blockchain, sectors that drew heavy capital in 2021 and 2022.
Root cause: Some companies build the right product for a market that arrives three years later, or raise into a hype cycle that reverses before the product matures.
Timing risk is managed with smaller bets and shorter funding horizons, not with optimism.
Unsustainable Unit Economics
19% of that group were tied to unit economics that never worked.
Root cause: Every sale loses money and growth makes the hole deeper. Discounts, subsidized delivery and heavy service costs hide it until volume exposes it.
Know your contribution margin per order before you scale acquisition.
Premature Scaling
Startup Genome's analysis of more than 3,200 high-growth technology startups found that 70% of the dataset scaled prematurely, and 93% of those never passed $100,000 in monthly revenue. The report dates from 2011, so treat it as a pattern rather than a current rate.
Root cause: Hiring, ad spend and infrastructure grow ahead of proven demand, which converts a solvable product problem into a fatal cash problem.
Scale a channel only after it repeats without you pushing it.
Team and Hiring Missteps
In the Wilbur Labs survey, 49% of founders wished they had hired key team members sooner and 35% wished they had removed underperforming employees earlier. Failory's breakdown of interviews with more than 80 failed founders puts team problems at 18% of failures.
Root cause: Senior hires arrive before the role is defined, co-founder equity and decision rights stay vague, and nobody corrects a bad fit in time.
Role clarity and hiring sequence matter more than headcount.
Competition and Market Shifts
45% of the founders Wilbur Labs surveyed named competition and shifting market dynamics when asked why their company failed or had to pivot, 44% named technology or product issues, and 50% said technological disruption, including AI, is now the top threat to their company.
Root cause: A defensible wedge erodes when a larger platform ships the same feature for free or a new technology resets customer expectations.
Watch the substitutes your customers actually consider, not only direct rivals.
Founder Burnout
90% of the founders Wilbur Labs surveyed said they experienced stress or burnout severe enough to make them consider quitting, and close to half reported anxiety, depression or panic attacks.
Root cause: Burnout does not show up in a metrics dashboard, but it slows decisions, delays hard conversations and eventually ends companies that were still viable.
Founder capacity is an operating constraint, not a personal failing.
Sources for the figures above: CB Insights (431 venture-backed shutdowns, published March 2026), Wilbur Labs (survey of 200 startup founders, fielded with Wakefield Research in February 2026, margin of error 6.9 percentage points), Failory (interviews with more than 80 failed founders) and Startup Genome (2011 analysis of more than 3,200 high-growth startups).
Startup Failure Examples and the Lesson From Each
Percentages are easier to argue with than names. These five companies raised more money than most founders will ever see, and they still closed.
Quibi
The short-form streaming app raised $1.75 billion in venture capital, launched on April 6, 2020, and announced on October 21, 2020 that it was winding down, roughly six months later.
Sources: TechCrunch, Yahoo Finance
The lesson: Capital and celebrity distribution deals do not create demand. The product asked people to change a viewing habit that was already served for free.
Zume
Raised $446 million, pivoted from robot-made pizza to sustainable packaging, and shut down after the new market did not materialize.
Source: CB Insights
The lesson: A pivot only works if it lands on a market that is already buying. Pivoting late, with a burn rate set by the old plan, rarely leaves enough runway.
Convoy
A digital freight brokerage that raised more than $1 billion in total, including a $260 million round in 2022 at a $3.8 billion valuation, then sent its shutdown memo on October 19, 2023, about 18 months later. CEO Dan Lewis blamed a massive freight recession and said market forces were too strong for the company to withstand on its own.
Source: Supply Chain Digest
The lesson: Scale does not fix economics. When the margin on each transaction is thin, a downturn in the underlying market removes the cushion quickly.
Olive
A healthcare AI automation company that raised hundreds of millions of dollars, including a $400 million round, was once valued at $4 billion, and announced at the end of October 2023 that it was shutting down, selling its clearinghouse and patient access businesses to Waystar and Humata Health.
Source: Healthcare Dive
The lesson: Selling into slow, highly regulated buyers takes longer than venture timelines assume. Raising at a pace the sales cycle cannot support creates a gap nothing closes.
New Age Meats
Raised $32 million during the peak of the alternative-protein funding wave and shut down when the market did not materialize.
Source: CB Insights
The lesson: Raising into a hype cycle sets expectations you have to grow into. When the wave passes, the next round is priced against results you never had time to produce.
The pattern across all five is the same one the aggregate data shows. None of them failed because the founders were not working hard enough. They failed because the market they were building for was smaller, slower or later than the spending plan assumed.
Startups vs Small Businesses: Different Failure Rates
Most of the alarming numbers in circulation describe venture capital outcomes, but most US businesses never raise a round. A marketing agency, a dental practice or a plumbing company is judged on whether it stays open and profitable, not on whether it returned an outside investor's money several times over.
That is why the BLS survival curve is the right reference for small business owners: roughly 20% close in year one, about half are gone by year five, and about a third are still running after ten years. Steep, but nothing like 90%. It also explains why the two groups fail for different reasons. Small businesses are more often undone by cash flow timing, key-person dependency and local demand shifts. Venture-scale startups are more often undone by building a market that does not exist yet.
The practical implication is about pace. If you are not chasing venture returns, you do not need a venture spending pattern, and copying one is a reliable way to import failure modes you had no reason to face.
5 Warning Signs Your Startup Is Failing
These signs show up months before the bank balance does. Use them as a self-check: score each one honestly, and treat two or more as a signal to stop adding features and re-examine demand.
No paying customer after months of building
How to check: Count signed orders or paid subscriptions, not waitlist signups or demo requests. If the number is zero after a full build cycle, you have a demand problem, not a marketing problem.
Burn rate is set by the plan, not by revenue
How to check: Divide cash on hand by average monthly net burn. If runway is under six months and monthly revenue has not moved for two quarters, the shortfall is structural.
You cannot state your contribution margin per sale
How to check: Take the revenue on one order and subtract every variable cost that order triggers. If the answer is negative or unknown, growth is making things worse.
The team disagrees on what matters this quarter
How to check: Ask three people, separately, to name the single most important metric. Three different answers usually predict scattered effort and missed deadlines.
Launch keeps moving because the product is not ready
How to check: Look at how many times the launch date has shifted and why. Repeated polish-driven delays are usually avoidance of the market's verdict.
None of these five signs is fatal on its own. Together they describe a company that is spending real money on assumptions it has not tested. In the CB Insights dataset, the median company had 22 months between its last fundraise and its shutdown, so there is usually time to act on these signals.
Where to Go Next
This post is deliberately about diagnosis, not treatment. If you recognized your company in the root causes above, the corrections are laid out elsewhere on this site: common startup mistakes and how to fix them covers the founder-controllable errors one by one, go-to-market strategy for startups deals with the demand side, the startup roadmap for founders sequences the stages, and how to start a business in 30 days is the week-by-week version for anyone still at the beginning. For team-related failure modes, see startup hiring strategy.
If the constraint is simply that nothing is live yet, you can launch an MVP website the same day and start collecting real demand signals this week instead of next quarter.
FAQ: Why Startups Fail
Direct answers to the questions people ask most often about startup failure rates.
Is it true that 90% of startups fail?
Not as a closure rate. The 9-in-10 figure comes from startup ecosystem research rather than official records, and the nearest verified venture number is Shikhar Ghosh's finding that as many as 75% of venture-backed companies never return cash to investors. Measured as businesses that actually shut down, US government data shows about 20% of new establishments close in year one and roughly 65% within ten years.
Where does the 90% startup failure statistic come from?
There is no single official source. Failory traces the 9-in-10 claim back to the Startup Genome project, whose own reports put success at only about 1 in 12 entrepreneurs. The figure then spread through startup media without the population or definition that produced it, so it now gets repeated as though it described every new business.
Source: Failory
What percentage of startups fail in the first year?
About one in five. Bureau of Labor Statistics data shows 79.6% of US private-sector establishments born in March 2013 survived their first year, so 20.4% closed. Establishments that opened in the year ended March 2024 did slightly worse: 77.9% were still open a year later, meaning roughly 22% closed within twelve months.
Source: BLS
What is the number one reason startups fail?
Running out of money is the most reported reason, cited in 70% of the 385 venture-backed shutdowns CB Insights could assign a cause to. CB Insights calls it the final cause of death rather than the root problem. The underlying issue is usually weak product-market fit, which appeared in 43% of the same group.
Source: CB Insights
How many startups fail within 5 years?
Roughly half. Of the US private-sector establishments born in March 2013, 50.6% were still operating five years later, so about 49% had closed. Survival improves after that point: the businesses that reach year five are far more likely to reach year ten than brand-new businesses are to reach year five.
Source: BLS
Which industries have the highest startup failure rate?
Over ten years, mining, quarrying and oil and gas extraction had the lowest survival rate at 24.5%, followed by information at 29.1% and wholesale trade at 30.1%. Agriculture, utilities and manufacturing survived best, at 50.5%, 45.7% and 43.6%. Construction showed the steepest single drop in year one.
Source: BLS
Get a Second Opinion Before the Runway Runs Out
Understanding why startups fail is only useful if it changes what you do next. The failure data points to the same three questions: does anyone pay repeatedly, does each sale make money, and is spending sized to proven demand. Those are answerable long before the cash runs out.
BizTech's startup advisory services cover business model development, go-to-market strategy, competitive analysis and investor readiness review for early-stage founders. You can see the startup advisory pricing before you get in touch.
Ruhan Rafiq Bhaleshah
Chief Technology Officer
Ruhan Rafiq Bhaleshah leads the technical vision at BizTech, overseeing full-stack development, AI-powered workflows, and ensuring engineering teams collaborate with design and SEO specialists.