TL;DR
4,094 startup ideas analyzed against 40+ live data sources. Median score: 55/100. Only 18.7% earned a "go" verdict. The #1 killer is not competition (13.1%). It is having no go-to-market plan (28.9%). Fewer than 1% of ideas scored above 90.
This is the second edition of my startup validation benchmarks report. The first edition covered 1,000 ideas. This one covers 4,094 completed analyses run through Preuve AI, where each idea was scored against 40+ live data sources including competitor databases, Google Trends, Reddit, and community forums.
Every number in this report comes from real founder submissions. No synthetic data. No ChatGPT-generated ideas. These are real people testing real business concepts they planned to build or were already building.
I am publishing this as a reference for anyone researching startup failure rates, validation benchmarks, or idea viability data. Cite freely.
Overall Viability Distribution
The average viability score across 4,094 startup ideas is 58.4 out of 100. The median is 55. The distribution is a right-skewed bell curve centered in the 50-59 range.
| Score range | Count | % of total |
|---|---|---|
| 0-9 | 3 | 0.1% |
| 10-19 | 5 | 0.1% |
| 20-29 | 33 | 0.8% |
| 30-39 | 110 | 2.7% |
| 40-49 | 890 | 21.7% |
| 50-59 (peak) | 1,292 | 31.6% |
| 60-69 | 912 | 22.3% |
| 70-79 | 730 | 17.8% |
| 80-89 | 113 | 2.8% |
| 90-99 | 6 | 0.1% |
75.6% of all ideas land between 40 and 69. This is the "caution zone," where the idea has a kernel of something real but is missing at least one critical ingredient: a distribution plan, a clear competitor picture, or enough demand evidence.
Only 6 ideas out of 4,094 scored above 90. A score above 90 means live market data shows strong demand, a clear gap in the competitive landscape, and multiple converging signals. It is exceptionally rare on a first pass.
Verdict Breakdown: Go, Caution, No-Go
Every analysis ends with one of three verdicts based on the composite viability score:
18.7%
Go
749 ideas
Avg score: 74.9
75.6%
Caution
3,022 ideas
Avg score: 56.0
5.6%
No-Go
225 ideas
Avg score: 36.1
The gap between a "go" idea and a "caution" idea is an average of 18.9 points. In most cases, that gap comes from 2-3 fixable issues: unclear positioning, no competitor awareness, or a missing distribution plan. The idea itself is rarely the problem.
What is the #1 risk that kills startup ideas?
Each analysis identifies the top risk factor from live market data. Here is the distribution across all 4,094 ideas:
| Top risk | % of ideas | Avg score | Count |
|---|---|---|---|
| Go-to-market | 28.9% | 58.0 | 1,156 |
| Early-stage risk | 21.6% | 51.4 | 864 |
| Competitive pressure | 13.1% | 65.9 | 524 |
| Funding requirements | 11.8% | 61.9 | 472 |
| Regulatory risk | 11.0% | 56.7 | 438 |
| Team execution | 6.5% | 61.4 | 259 |
| Production challenges | 4.4% | 59.5 | 177 |
Go-to-market risk is the #1 failure signal for the second year running, flagged in 28.9% of all analyses. This means nearly 1 in 3 startup ideas have no realistic path to their first customer. The founder has a product concept but no distribution plan, no channel strategy, and no evidence that the target buyer is reachable.
The second-biggest risk is early-stage immaturity at 21.6%. These are ideas that are too vague to properly evaluate: no defined buyer, no pricing reference, no competitive landscape. The average score for this group is 51.4, the lowest of any risk category.
The competition paradox
Competition ranks third as a risk factor (13.1%), but ideas flagged for competitive pressure have the highest average score at 65.9. That is counterintuitive until you realize: competition means there is a real market. Ideas with no competitors often have no customers either. A crowded market is not automatically a bad sign. An empty market often is.
Do founders who pay for deeper analysis have better ideas?
Preuve AI offers two tiers: a free quick scan and a paid deep analysis that unlocks competitor research, community signals, and investor-grade sections.
Free Scan
57.8
Average score, 3,887 analyses
Deep Analysis (paid)
69.5
Average score, 207 analyses
Paid users average 69.5 vs 57.8 for free users, a gap of 11.7 points. This is not because paying makes your idea better. It is selection bias: founders who invest $29 in validation tend to be more serious. They have already done some homework. They have a clearer concept and a more defined market.
The practical takeaway: if you are going to pay for validation, make sure you have done the basic homework first. Define your buyer. Name three competitors. Know what price range the market tolerates. That baseline preparation is worth more than any tool.
Where do startup ideas come from? (by country)
The dataset skews heavily toward India and the US, but there are interesting patterns in the average scores by region.
| Country | Ideas tested | Avg score |
|---|---|---|
| India | 1,005 | 61.1 |
| United States | 76 | 53.3 |
| Pakistan | 34 | 60.6 |
| Nigeria | 30 | 53.6 |
| United Kingdom | 23 | 52.9 |
| Canada | 17 | 57.5 |
| Australia | 16 | 54.2 |
| Germany | 14 | 56.9 |
| Sri Lanka | 14 | 63.4 |
| Saudi Arabia | 13 | 53.5 |
Indian founders score 7.8 points higher on average than US founders. One possible explanation: India's startup ecosystem has matured rapidly, and founders submitting ideas tend to be building in markets they know well, where local competition is mapped more clearly. US founders more often target saturated global markets (AI tools, productivity SaaS) where the competitive density is brutal.
What separates a 50 from a 75?
After reviewing thousands of analyses, the gap between a mid-range score and a high score almost always comes down to three things:
1. Named competitors with pricing
Ideas that can name 3+ real competitors and reference their pricing score significantly higher. Not because competition is good, but because it proves the market exists and the founder has done the work. "No competitors" almost always means "I have not looked."
2. Demand evidence from outside the founder's network
Reddit threads, review complaints, Google Trends upticks, community forum posts. External demand signals show that strangers already care about the problem. Without them, the analysis can only score what the founder claims.
3. A specific buyer, not "everyone"
"Small business owners" is not a target market. "Solo accountants in the US who still use spreadsheets for client onboarding" is. Narrow targeting makes every other validation signal sharper: competitors are more relevant, demand is more measurable, pricing is more grounded.
The difference between a 50 and a 75 is not a better idea. It is better homework. Most ideas that score in the 40-60 range have a real kernel of value. They just have not been pressure-tested against the market yet.
Key takeaways for founders
- 1.Most ideas are not terrible, they are unfinished. 75.6% land in the caution zone, not the no-go zone. The median score is 55, not 30.
- 2.Distribution kills more ideas than competition. Go-to-market risk (28.9%) is 2x more common than competitive pressure (13.1%). Stop worrying about who else is building this. Start worrying about how your first customer finds you.
- 3.Competition is a positive signal. Ideas flagged for competitive pressure average 65.9, the highest of any risk category. A crowded market means proven demand.
- 4.Scoring above 90 is extremely rare. 6 out of 4,094 ideas (0.15%). If your idea scores 70+, you are already in the top 21%.
- 5.Preparation matters more than the idea. Paid users score 11.7 points higher on average, not because paying helps, but because serious founders do their homework first.
Methodology
This report is based on 4,094 completed analyses processed by Preuve AI as of April 2026. Each analysis scans 40+ live data sources including competitor databases, Google Trends, Reddit, Crunchbase, patent databases, and community forums.
The viability score (0-100) is a composite of market size signals, competitive density, demand evidence, timing indicators, and risk factors. The verdict (go/caution/no-go) is derived from the score. Every data point is linked to its original source within each report.
This dataset includes both free scans and paid deep analyses. It does not include agency scans or investor packages. All data is anonymized. No individual ideas, founder names, or company names are disclosed.
For the full validation methodology, read how Preuve AI validates startup ideas. For the scoring formula, see how viability scores work.
Where does your idea land?
Preuve AI scores your idea against 40+ live data sources. See how it compares to 4,000+ other startup ideas, and get a sourced report you can act on.
Get my free viability scoreFrequently Asked Questions
What percentage of startup ideas pass validation?
Based on 4,094 startup ideas analyzed by Preuve AI against 40+ live data sources, only 18.7% received a go verdict (score 70+). 75.6% received a caution verdict, meaning the idea has potential but needs significant work. 5.6% received a no-go verdict with a score below 40.
What is the most common reason startup ideas fail validation?
The number one failure signal is go-to-market risk, flagged in 28.9% of all analyses. Founders build products without a distribution plan. The second most common risk is early-stage immaturity at 21.6%. Competition, which founders fear most, ranks third at 13.1%.
What is a good startup viability score?
The median viability score across 4,094 analyzed ideas is 55 out of 100. Ideas scoring 70 or above (20.7% of all ideas) are considered high-viability. The average score is 58.4. Fewer than 1% of ideas score above 90.
What is the startup failure rate in 2026?
Preuve AI's 2026 dataset shows that 5.6% of startup ideas receive a no-go verdict based on live market data. Another 75.6% land in the caution zone, meaning they need iteration before launch. Only 18.7% of ideas pass validation on their first attempt.
How does Preuve AI calculate startup benchmarks?
Preuve AI scores startup ideas from 0 to 100 using 40+ live data sources including competitor databases, Google Trends, Reddit, Crunchbase, and community forums. The score reflects market size, competitive density, demand signals, timing, and risk factors. Every data point links to its original source.
