In terms of deals over the past five years, artificial intelligence and big data was the largest VC-funded startup industry in 2022, accounting for close to 30 percent of the global deals. Meanwhile, fintech accounted for 16 percent of the deals, with life sciences and health care behind with 12 percent. Blue economy and digital media media were the smallest industries with only one percent each. However, the blue economy saw its funding deals almost doubling over the past five years.

Discover Startup Data for technology startups globally with Success.ai. Gain access to verified company data, including firmographic data, employee counts, and funding insights. Best price guaranteed.

Introduction

Startup Failure Rate Statistics: Launching a new business can be both exciting and promising, but it also comes with its share of ups and downs. Understanding the reasons behind startup failures can help aspiring entrepreneurs navigate challenges more effectively. By analyzing data on these failures, entrepreneurs can develop strategies to mitigate risks and create adaptable business plans that increase their chances of success.

This article presents statistics on startup failures, highlighting what potential new businesses may encounter and how to prepare for these challenges. Being informed, developing a clear strategy, and stepping out with confidence are essential for overcoming obstacles in the entrepreneurial journey.

We will create a customized startups dataset tailored to your specific requirements. Data points may include startup foundation dates, locations, industry sectors, funding rounds, investor profiles, financial health, market positions, technological assets, employee counts, and other relevant metrics.

Utilize our startups datasets for a variety of applications to boost strategic planning and innovation tracking. Analyzing these datasets can help organizations grasp market trends and growth opportunities within the startup ecosystem, allowing for more precise strategy adjustments and operations. You can choose to access the complete dataset or a customized subset based on your business needs.

Popular use cases include: enhancing competitive analysis, identifying emerging market trends, and finding high-potential investment opportunities.

According to the survey carried out among start-up owners, the main reasons why their businesses did not work out was a lack of financing, with nearly half percent of the start-ups giving this as the main reason for their business failure. Moreover, the COVID-19 pandemic played a role in one third of business failures. There is rarely one reason behind a company going bankrupt, it is rather a mixture of several issues, as reflected in the many reasons stated by the respondents.

This statistic shows the number of jobs that were created in the United States through businesses that were less than one year old from March 1994 to March 2023. In 2023, there were more than 3.7 million new jobs created through start-up businesses, more than the year prior.

Overview:

This dataset provides a comprehensive look into the financial expenditures and profits of 50 startups based in the United States. It is an invaluable resource for analysts, economists, and business strategists seeking to understand the correlation between different types of spending and profitability in startup ventures.

Attributes: 1. R&D Spend: - Description: The amount of money each company has invested in Research and Development activities. - Data Type: Numeric (US dollars) - Importance: Indicates the company's commitment to innovation and technological advancement. 2. Administration: - Description: Expenditure on administrative functions and operations. - Data Type: Numeric (US dollars) - Relevance: Reflects the overhead costs associated with managing the company. 3. Marketing Spend: - Description: Investment in marketing and promotional activities. - Data Type: Numeric (US dollars) - Significance: A key factor in revenue generation and market penetration. 4. State: - Description: The U.S. state where the company is operating. - Data Type: Categorical (California, New York, or Florida) - Purpose: Provides geographical context and allows for regional analysis. 5. Profit: - Description: The net profit earned by the company. - Data Type: Numeric (US dollars) - Utility: A direct measure of the company’s financial success.

Potential Uses: - Business Analysis: Understanding how different types of spending (R&D, administration, marketing) affect profitability. - Regional Studies: Examining the impact of geographical location on business success. - Startup Growth: Insights into the financial practices of successful startups. - Economic Research: Data-driven study of the startup ecosystem in the U.S.

Target Audience: - Business Analysts and Economists - Marketing Strategists - Startup Consultants - Data Science Enthusiasts - Academic Researchers

Conclusion: This dataset is a rich resource for anyone looking to delve into the financial dynamics of startups in the U.S. It offers a unique perspective on how different types of investments correlate with company success across various states.

Please note that the data is anonymized and does not include any confidential information about the companies listed. The dataset is intended for educational and research purposes.

The ************* was by far the best country for startups in 2024, according to data provided by StartupBlink. With a total score of ***, the U.S. had almost more than **** times as many points as the second ranked **************, with a score of *****. Israel followed in third.

Success.ai’s Startup Data for Technology Startups Worldwide provides a comprehensive dataset to help businesses, investors, and service providers connect with innovative tech startups across the globe. With access to over 170 million verified professional profiles and 30 million company profiles, this dataset includes detailed firmographic data, funding insights, and employee information. Whether you’re targeting early-stage ventures, scaling startups, or established unicorns, Success.ai ensures your outreach and strategic planning are informed by reliable, continuously updated, and AI-validated data. Backed by our Best Price Guarantee, this solution empowers you to engage meaningfully with the technology startup ecosystem.

Why Choose Success.ai’s Technology Startup Data?

1. Comprehensive Startup Insights

   • Access verified data on company size, founding dates, technology focus areas, geographic locations, and funding stages.
   • AI-driven validation ensures 99% accuracy, minimizing wasted outreach and guiding confident engagement.

2. Global Coverage of Technology Startups

   • Includes profiles of tech startups specializing in SaaS, AI, FinTech, e-commerce, HealthTech, IoT, cybersecurity, and more.
   • Covers key innovation hubs such as Silicon Valley, Bangalore, London, Berlin, Singapore, and emerging markets worldwide.

3. Continuously Updated Datasets

   • Real-time updates reflect new funding rounds, product launches, leadership changes, and expansion activities.
   • Stay aligned with the fast-paced startup ecosystem to identify opportunities and build relationships at the right time.

4. Ethical and Compliant

   • Adheres to GDPR, CCPA, and other global privacy regulations, ensuring responsible data usage and compliance with legal standards.

Data Highlights:

• 170M+ Verified Professional Profiles: Engage with founders, co-founders, CEOs, CTOs, and decision-makers in technology startups worldwide.
• 30M Company Profiles: Gain insights into startup firmographics, including size, industry focus, and operational footprint.
• Funding Insights: Access data on seed, Series A, Series B, and other funding rounds, along with investor details.
• Employee and Organizational Data: Understand team compositions, growth trajectories, and hiring trends for better engagement.

Key Features of the Dataset:

1. Startup Decision-Maker Profiles

   • Identify and connect with founders, product leads, technology architects, and business development managers driving growth in tech startups.
   • Engage with professionals making critical decisions about partnerships, procurement, and market expansion.

2. Funding and Investment Data

   • Access insights into recent funding rounds, investor portfolios, and funding sources (venture capital, angel investors, private equity).
   • Tailor outreach based on funding stage, ensuring relevance for services like advisory, recruitment, or technology solutions.

3. Advanced Filters for Precision Targeting

   • Filter startups by industry vertical, funding stage, geographic location, company size, or growth metrics.
   • Align campaigns with unique startup challenges, such as scaling operations, building MVPs, or achieving market fit.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data allow you to craft personalized messaging, showcase relevant value propositions, and enhance engagement with startup leaders.

Strategic Use Cases:

1. Investor Relations and Funding Opportunities

   • Connect with founders and executives preparing for fundraising rounds or seeking strategic investment partnerships.
   • Identify high-growth startups for venture capital, angel investing, or co-investment opportunities.

2. Sales and Lead Generation

   • Present SaaS solutions, infrastructure tools, or marketing services tailored to startup challenges, such as scaling, market entry, or user acquisition.
   • Build relationships with startups that align with your product offerings and service capabilities.

3. Strategic Partnerships and Ecosystem Building

   • Engage startups developing complementary technologies or exploring strategic alliances in innovation ecosystems.
   • Identify early-stage companies to co-develop products, expand market reach, or enhance technology stacks.

4. Recruitment and Talent Solutions

   • Offer staffing services, recruitment platforms, or HR solutions to fast-growing startups scaling their teams.
   • Engage with hiring managers or founders seeking skilled professionals to support product development or market expansion.

Why Choose Success.ai?

1. Best Price Guarantee

   • Gain access to premium-quality verified data at competitive prices, ensuring optimal ROI for outreach and strategic initiatives targeting startups.

2. Seamless Integration

   • Integrate verified startup data into your CRM or marketing platforms via APIs or d...

Introduction

CRISPR Statistics: CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) technologies have transformed the genetic modification landscape since their invention. Making allows for precise editing of deoxyribonucleic acid and transformative use in health care, farming, and research.

Since its discovery, CRISPR has enabled precise editing of DNA in a wide range of organisms—from bacteria and archaea to plants, animals, and human cells. Approximately 50 percent of sequenced bacterial genomes and nearly 90 percent of sequenced archaeal genomes carry CRISPR loci. Field trials using CRISPR to knock out the KRN2 gene in maize and OsKRN2 in rice yielded grain yield increases of around 10 percent and 8 percent, respectively.

The global CRISPR gene‑editing sector is projected to rise from USD 3.58 billion in 2023 to USD 4.01 billion in 2024, and further to USD 4.77 billion in 2025, with an estimated CAGR ranging from 14.7 percent to 14.8 percent into the early 2030s. Its agricultural offshoot—the CRISPR‑Cas genes market—generated USD 461.9 million in 2024 and is expected to exceed USD 1.02 billion by 2030, growing at around 14.4 percent CAGR. In parallel, CRISPR genomic‑cure initiatives are estimated at USD 4.62 billion in 2025, expanding to USD 17.04 billion by 2032 at a 20.5 percent CAGR.

In the year 2024, the globalization of the CRISPR statistics value chain is on the rise owing to the ongoing development of gene-editing ailments and increased R&D activities.

Post getting recognition a Startup may apply for Tax exemption under section 80 IAC of the Income Tax Act. Post getting clearance for Tax exemption, the Startup can avail tax holiday for 3 consecutive financial years out of its first ten years since incorporation.

Eligibility Criteria for applying to Income Tax exemption (80IAC):

1. The entity should be a recognised Startup
2. Only Private limited or a Limited Liability Partnership is eligible for Tax exemption under Section 80IAC
3. The Startup should have been incorporated after 1st April, 2016

From 2013 to 2023, the number of startups in Brazil has increased year after year. In 2023, there will be approximately ****** registered startups in Brazil. This number has grown by *** percent compared to 2013, when the number of Brazilian startups was less than *****.

The Business Dynamics Statistics (BDS) includes measures of establishment openings and closings, firm startups, job creation and destruction by firm size, age, and industrial sector, and several other statistics on business dynamics. The U.S. economy is comprised of over 6 million establishments with paid employees. The population of these businesses is constantly churning -- some businesses grow, others decline and yet others close. New businesses are constantly replenishing this pool. The BDS series provide annual statistics on gross job gains and losses for the entire economy and by industrial sector, state, and MSA. These data track changes in employment at the establishment level, and thus provide a picture of the dynamics underlying aggregate net employment growth.

There is a longstanding interest in the contribution of small businesses to job and productivity growth in the U.S. Some recent research suggests that it is business age rather than size that is the critical factor. The BDS permits exploring the respective contributions of both firm age and size.

BDS is based on data going back through 1976. This allows business dynamics to be tracked, measured and analyzed for young firms in their first critical years as well as for more mature firms including those that are in the process of reinventing themselves in an ever changing economic environment.

If you need help understanding the terms used, check out these definitions.

Data Dictionary

Key	List of...	Comment	Example Value
State	String	The state that this report was made for (full name, not the two letter abbreviation).	"Alabama"
Year	Integer	The year that this report was made for.	1978
Data.DHS Denominator	Integer	The Davis-Haltiwanger-Schuh (DHS) denominator is the two-period trailing moving average of employment, intended to prevent transitory shocks from distorting net growth. In other words, this value roughly represents the employment for the area, but is resistant to sudden, spiking growth.	972627
Data.Number of Firms	Integer	The number of firms in this state during this year.	54597
Data.Calculated.Net Job Creation	Integer	The sum of the Job Creation Rate minus the Job Destruction Rate.	74178
Data.Calculated.Net Job Creation Rate	Float	The sum of the Job Creation Rate and the Job Destruction Rate, minus the Net Job Creation Rate.	7.627
Data.Calculated.Reallocation Rate	Float	The sum of the Job Creation Rate and the Job Destruction Rate, minus the absolute Net Job Creation Rate.	29.183
Data.Establishments.Entered	Integer	The number of establishments that entered during this time. Entering occurs when an establishment did not exist in the previous year.	10457
Data.Establishments.Entered Rate	Float	The number of establishments that entered during this time divided by the number of establishments. Entering occurs when an establishment did not exist in the previous year.	16.375
Data.Establishments.Exited	Integer	The number of establishments that exited during this time. Exiting occurs when an establishment has positive employment in the previous year and zero this year.	7749
Data.Establishments.Exited Rate	Float	The number of establishments that exited during this time divided by the number of establishments. Exiting occurs when an establishment has positive employment in the previous year and zero this year.	12.135
Data.Establishments.Physical Locations	Integer	The number of establishments in this region during this time.	65213
Data.Firm Exits.Count	Integer	The number of firms that exited this year.	5248
Data.Firm Exits.Establishment Exit	Integer	The number of establishments exited because of firm deaths.	5329
Data...

The paper deals with the potential relationship between higher education and entrepreneurial activities. Universities and other higher education institutions could be seen as boosting entrepreneurship in the region. University graduates could be more often involved in starting up a new business and the university itself could commercialize their innovations by creating academic spin-off companies. The paper aims to examine the potential effect of higher education on the probability of starting a business as well as its further success. Based on the data for 40 EU and non-EU countries, retrieved from a Eurobarometer survey, we conducted probit and IV probit regressions. These have tested the assumed relationship between higher education and entrepreneurial activities. Our results strongly suggest that higher education can often be very beneficial for starting up a new business and this seems to be one of the factors determining the success of new businesses. Furthermore, those respondents who attended courses related to entrepreneurship appear to be more active in starting-up a business and this seems to be also positively correlated with the company's future success. Interestingly, university graduates from Brazil, Portugal and India in particular, tend to appreciate the role that their universities have played in acquiring the skills to enable them to run a business.

Context A startup or start-up is a company or project undertaken by an entrepreneur to seek, develop, and validate a scalable business model. While entrepreneurship includes all new businesses, including self-employment and businesses that do not intend to go public, startups are new businesses that intend to grow large beyond the solo founder. In the beginning, startups face high uncertainty and have high rates of failure, but a minority of them do go on to be successful and influential.

Content The following dataset has data about the Top 300 startups in India. Details about the columns are as follows:

Company - Name of the Startup. City - The City in which the startup is started. Starting Year - The Year in which the startup was started. Founders - Name of the founders of the startup. Industries - Industrial domain in which the startup falls. No. of Employees - Number of employees in the startup. Funding Amount in USD - Total funding amount funded to the startup. Funding Rounds - Funding rounds are the number of times a startup goes back to the market to raise more capital. The goal of every round is for founders to trade equity in their business for the capital they can utilize to advance their companies to the next level. No. of Investors - Number of investors in the startup.

Original Data Source: Indian startups

According to data from the Global Entrepreneurship Monitor, the start-up rate in the United States was 10.7 percent in 2020. In the United Kingdom the start-up rate amounted to 5.2 percent in the same year.

PredictLeads Connections Dataset maps global business relationships using advanced web scraping and logo recognition to detect key partnerships, investments, and integrations. This dataset helps venture capital firms, B2B sales teams, and competitive intelligence professionals analyze market dynamics, track partnerships, and uncover strategic opportunities.

Use Cases for Venture Capital & B2B Strategies: ✅ Identify Emerging Startups – Track early-stage companies forming new partnerships, vendor relationships, and integrations. ✅ Assess Startup Traction – Analyze a company’s key customers and strategic alliances before investing. ✅ Market Demand Analysis – Track which startups are securing major clients, vendors, and partners to assess competitiveness. ✅ M&A & Acquisition Targeting – Identify startups with strong B2B relationships, making them ideal acquisition candidates. ✅ Competitive & Market Intelligence – Track partnership trends, vendor reliance, and ecosystem expansions within target sectors.

Primary Attributes from the API:

Business Connection Details:

• id (UUID) – Unique identifier for the business connection.
• type (string, constant: "connection") – Object type.
• category (string) – Type of relationship (vendor, partner, investor).
• source_category (string) – Website section where the connection was detected.
• source_url (URL) – Main website where the connection is found.
• individual_source_url (URL) – Direct page link mentioning the connection.
• context (string) – Description of the business relationship between two companies.
• first_seen_at (ISO 8601 date-time) – Timestamp when the connection was first detected.
• last_seen_at (ISO 8601 date-time) – Timestamp when the connection was last observed.

Company Details:

• company1 (object) – First company in the relationship.
• - id (UUID) – Unique identifier.
• - type (constant: "company") – Object type.
• company2 (object) – Second company in the relationship.
• - id (UUID) – Unique identifier.
• - type (constant: "company") – Object type.

Included Company Metadata:

• id (UUID) – Unique company identifier.
• domain (string) – Company’s website domain.
• company_name (string) – Official company name.
• ticker (string, nullable) – Stock ticker symbol (if applicable).

📌 PredictLeads Business Connections Data is trusted by enterprises, VC firms, and analysts for accurate, structured intelligence on global partnerships and business networks.

PredictLeads Documentation: https://docs.predictleads.com/v3/guide/connections_dataset

Startup Indicators: Founders: Education: High School data was reported at 5.600 % in 2023. This records an increase from the previous number of 5.400 % for 2022. Startup Indicators: Founders: Education: High School data is updated yearly, averaging 5.600 % from Dec 2021 (Median) to 2023, with 3 observations. The data reached an all-time high of 5.600 % in 2023 and a record low of 5.400 % in 2022. Startup Indicators: Founders: Education: High School data remains active status in CEIC and is reported by Brazilian Association of Startups. The data is categorized under Brazil Premium Database’s Investment – Table BR.OH004: Startups: Profile of Startup Founders.

Brazil Startup Indicators: Fundation: 4 Years data was reported at 13.400 % in 2023. This records an increase from the previous number of 10.800 % for 2022. Brazil Startup Indicators: Fundation: 4 Years data is updated yearly, averaging 10.800 % from Dec 2021 (Median) to 2023, with 3 observations. The data reached an all-time high of 13.400 % in 2023 and a record low of 8.700 % in 2021. Brazil Startup Indicators: Fundation: 4 Years data remains active status in CEIC and is reported by Brazilian Association of Startups. The data is categorized under Brazil Premium Database’s Investment – Table BR.OH004: Startups: Profile of Startup Founders.

In the first quarter of 2024, 322,000 new businesses were formed in the United States. This is a slight decrease from the previous quarter, when 327,000 new businesses were formed. In the second quarter of 2020, new business starts experienced a dip to 227,000, but have picked up quickly in subsequent quarters.