Startup Failure Rates by Sector: A 10-Year Data Breakdown (2016–2026)

by Andy Jamerson  April  2026

Startup mortality data is frequently cited and rarely disaggregated. The headline figure — that approximately 90% of startups fail — has circulated in business media for over a decade without the sectoral nuance necessary to make it analytically useful. A decade of data from 2016 through 2026 reveals failure rates that vary dramatically by sector, funding stage, founding team characteristics, and macroeconomic conditions at time of launch. This analysis breaks those patterns down into actionable findings for investors, founders, and operators.

Key Takeaways

• Across all sectors, approximately 20% of startups fail within their first year and roughly 45% fail by year three
• SaaS startups demonstrate the highest five-year survival rate at approximately 32%, compared to 18% for consumer-facing apps and 14% for hardware startups
• Fintech failure rates accelerated sharply between 2022 and 2024 as rising interest rates eliminated unit economics for payment-forward business models
• Startups that raised Series A funding between 2021 and 2022 at peak valuations showed a 61% higher rate of closure or down-round distress by 2025 versus 2019 vintage cohorts
• Founding team composition is the single strongest predictor of five-year survival in pre-seed and seed-stage companies
• Climate tech startups show the lowest failure rate among 2020 to 2023 vintage cohorts, in part due to federal funding backstops
• Median runway at failure across all sectors was 4.2 months in 2024, down from 7.1 months in 2021

Failure Rate Patterns Across Sectors and Vintage Cohorts

The 2016 to 2026 window is analytically rich because it spans a full venture cycle: from the post-2016 recovery period, through the zero-interest-rate-driven peak of 2020 to 2021, into the 2022 to 2023 correction, and into the stabilization visible in 2025 data. Each phase produced distinct failure rate patterns.

SaaS startups consistently showed the best survival profiles of any sector across the decade. The category benefits from low cost-of-goods-sold structures, recurring revenue that provides planning visibility, and high investor familiarity that translates into relatively efficient capital access.

Consumer-facing app startups show the most volatile failure distribution. Successful outcomes in this category are highly concentrated among a small number of category-defining winners, while the remainder fails at rates approaching 85 to 90% at the five-year mark.

Hardware and deep tech startups have the highest absolute failure rates, driven by capital intensity, long development cycles, and manufacturing risk. The median hardware startup requires 2.4 times more capital to reach the same revenue milestone as a comparable SaaS startup.

Marketplace startups occupy a middle range. Their failure rates at the five-year mark average approximately 72 to 78%, with survival strongly correlated with achieving liquidity — sufficient transaction volume on both sides — within the first 18 months of operation.

Funding Stage, Valuation Vintage, and Failure Correlation

The 2021 vintage of venture-backed startups represents one of the most studied cohorts in recent history, precisely because the macroeconomic whipsaw that followed produced an unusually concentrated period of stress. Companies that raised at 2021 valuations — which averaged 40 to 60% above historical norms on a revenue-multiple basis — faced a structural mismatch when they attempted to raise again in 2022 or 2023.

Surveyed data from VC portfolio companies indicates that 61% of 2021 vintage Series A companies experienced either closure, asset sale at distressed valuations, or significant down-round financing by the end of 2024. The 2019 vintage equivalent rate was 38%.

Pre-seed and seed stage failure rates were less affected by valuation vintage because those companies had not yet committed to high-multiple raises. Earlier-stage companies that survived through 2023 often did so by dramatically extending runway — cutting burn rates aggressively in a way that later-stage companies with larger team structures could not replicate.

Startups that ultimately survived the 2022 to 2023 correction averaged 37% lower monthly burn rates in Q1 2022 compared to their peers who did not survive.

Cost Structure, Runway Dynamics, and Failure Triggers

Median runway at the point of failure declined significantly across the decade’s later years. In 2021, the median failed startup had approximately 7.1 months of runway remaining when founders made the decision to wind down. By 2024, that figure dropped to 4.2 months.

Personnel costs represent the single largest driver of startup burn across all sectors. Payroll and benefits averaged 58 to 67% of total operating expenses in the 12 months prior to failure. The decision to scale hiring ahead of revenue metrics proved particularly damaging when revenue projections failed to materialize.

Customer acquisition cost (CAC) elevation contributed significantly to consumer-facing startup failures in 2022 and 2023. Digital advertising costs rose substantially as major platforms tightened ad signal quality, increasing median CAC in consumer categories by 31 to 44% between 2021 and 2023.

Approximately 42% of startup founders surveyed after closure cited “no market need” or “insufficient product-market fit” as a primary failure cause — making it the most common answer ahead of funding shortfall, competitive pressure, or operational execution failures.

Leading Platforms in This Space

CB Insights provides comprehensive startup tracking, funding data, and failure analysis, serving as a primary data source for investors monitoring sector-level failure and survival trends.

Crunchbase offers global startup and funding database coverage, with research tools that allow investors and analysts to track cohort survival rates and acquisition outcomes by vertical.

PitchBook delivers detailed venture capital and private equity data, including portfolio company performance tracking and sector-specific failure and exit data.

AngelList serves as both a funding platform and a data source for early-stage startup activity, with particular depth in pre-seed and seed-stage company formation.

Carta manages equity and cap table data for a large portion of venture-backed companies, giving it visibility into funding round timing, dilution events, and company dissolution patterns.

Y Combinator functions as both an accelerator and a longitudinal data source, with over 5,000 alumni companies providing sector-level survival and outcome data.

Startupblink tracks global startup ecosystem health, providing geographic and sector-level analysis of startup formation and mortality rates across over 100 countries.

NVCA (National Venture Capital Association) publishes industry-standard data on venture investment volumes, exit rates, and sector-specific trends.

Platform Comparisons and Alternatives

Academic research on startup failure rates and practitioner-sourced analysis differ in meaningful ways. Academic studies tend to use legally-defined business closure as the failure event, which understates failure because many functionally failed companies remain legally active for years.

Sector-specific failure data from industry associations provides more granular context but varies significantly in methodology — making cross-sector comparisons imprecise when definitions are not aligned.

Government-sourced data from the Bureau of Labor Statistics and SBA Office of Advocacy covers business survival broadly but lacks the sector and stage granularity needed for venture-relevant analysis. BLS data consistently shows slightly higher five-year survival rates than venture-focused databases because it includes industries with lower capital intensity and lower growth ambitions.

What the Data Signals for 2027 and Beyond

Sector concentration among survivors will continue. The 2022 to 2026 correction period functionally culled the weakest cohorts. Companies that survived are, on average, better capitalized, more capital-efficient, and operating in categories with more durable demand.

Fintech startup formation will remain subdued through 2026 as the sector digests the failure rate spike of 2022 to 2024. Regulatory scrutiny has increased, unit economics require higher interest rate floors than many models assumed, and investor appetite for unproven fintech models has narrowed.

Climate tech will be the most resilient formation sector through 2027. Federal funding backstops, corporate sustainability commitments, and improving unit economics across solar, battery, and efficiency categories are providing demand visibility and non-dilutive capital rare in any other sector.

Methodology

This analysis draws on aggregated data from venture capital databases, academic research on business survival rates, SBA Office of Advocacy business lifecycle data, and industry association reports covering specific sectors including fintech, SaaS, and climate technology. Funding vintage analysis is informed by publicly available round data and secondary market research on portfolio company outcomes.

Conclusion

Startup failure rates are not uniform, and treating them as such produces misleading conclusions for founders, investors, and policy-makers alike. The decade from 2016 through 2026 reveals a clear sectoral hierarchy of survival, with SaaS and climate tech at the top and hardware and consumer apps at the bottom — and a funding vintage effect that shaped outcomes across every sector during the 2022 to 2025 correction. Capital efficiency, product-market fit discipline, and sector selection are the variables that most consistently differentiate survivors from failures, regardless of economic conditions.