As of 2020, the average startup failure rate in Africa stood at ** percent. However, the rate differed across countries. In Ethiopia and Rwanda, ** percent of the startups ceased operations, while Kenyan startups had a failure rate of ** percent in the same year.

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.

As of 2023, UK business enterprises founded in 2022 had a one-year survival rate of 92.3 percent, compared with 93.4 percent in the previous year. For businesses founded in 2018, just 39.4 percent were still operating in 2022.

Almost one in five new businesses in the European Union failed in their first year according to the one-year business survival rates in the European Union for 2018. In this year, the country with the highest business survival rate was Greece, which had a one-year survival rate of 96.7 percent, while Lithuania had the lowest at 63.57.

A comprehensive dataset covering small business statistics in 2025, including failure rates, growth data, average revenue, number of employees, and market insights.

Graph and download economic data for Number of Business Failures, All Commercial for United States (M0929CUSM474NNBR) from Jan 1939 to Jun 1965 about failures, commercial, business, and USA.

Only **** percent of businesses in the United States founded between March 2013 to March 2023 were still operating in March 2023. By 2018, around half of such U.S. businesses had still survived.

In 2020, approximately **** percent of newly established businesses in South Korea failed to continue operations after five years. This was highest among arts, sports and recreation-related services as well as accommodation and food services. The 5-year survival rate stood at **** percent, which was notably lower than the OECD average of **** percent.

** Startup Failure Prediction Dataset

This dataset helps understand why some startups succeed while others fail. It contains 5,000 startups from different industries and includes important details like funding, revenue, team size, and market conditions. **

** What’s Inside?**

This dataset has key information about startups, including:

Industry– Type of business (Tech, Healthcare, E-commerce, etc.)

Startup Age – How many years the startup has been running

Funding Amount – Total investment received

Number of Founders – How many people started the company

Founder Experience – Work experience of the founders

Employees Count – Number of employees in the startup

Revenue – How much money the startup makes

Burn Rate – How much money the startup spends per month

Market Size – Size of the industry (Small, Medium, Large)

Business Model – Does the startup sell to businesses (B2B) or customers (B2C)?

Product Uniqueness Score – How unique the startup’s product is (Scale: 1-10)

Customer Retention Rate – Percentage of customers who return

Marketing Expense – How much money is spent on marketing

Startup Status – 1 = Successful, 0 = Failed (Did the startup succeed or fail?)

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.

The following small business statistics broken down by industry to help you understand the small business landscape better.

Introduction

Small Business Statistics: Small businesses are often seen as the backbone of the economy, and rightly so. They bring fresh ideas to the market and create jobs for people who may not have opportunities in larger companies. From one-person businesses to significant job creators, small businesses are crucial to the economy.

However, with 82% failing because of cash flow problems and only 50% making it to the five-year mark, it’s clear that achieving success is not easy. Here are some Small Business Statistics that can help entrepreneurs understand the market better and position their products or services for success.

These small business statistics will tell you everything you need to know about the growth of business and where it’s going in the future.

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.

An in-depth dataset covering business plan statistics in 2025, including success rates, planning impact, and industry insights.

This statistic shows the results of a survey on attitudes towards starting a new business after a failure in selected countries in Latin America in 2017. That year, 18 percent of the entrepreneurs surveyed in Mexico stated they did not have any intention to start a new business after facing failure.

2 out of 3 business owners said their first year in business was the most difficult. 80% of small businesses are still in operation after 1 year.

In 2020, the average two-year fail rate was lower for Black and Latinx women-led startups than it was for startups overall in the United States. The national fail rate for startups in the U.S. sat at 40 percent in 2020, significantly higher than the 27 percent average fail rate for Black and Latinx female-led startups. The venture funding raised by Black and Latinx female-founded startups more than tripled between 2018 and 2020, but still only accounted for a fraction of all capital raised.

27% of the entire small business workforce had to be laid off or furloughed in 2020 due to the COVID-19 pandemic.

Analysis of ‘Startup Success Prediction’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/manishkc06/startup-success-prediction on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

A startup or start-up is a company or project begun by an entrepreneur to seek, develop, and validate a scalable economic model. While entrepreneurship refers to all new businesses, including self-employment and businesses that never intend to become registered, startups refer to new businesses that intend to grow large beyond the solo founder. Startups face high uncertainty and have high rates of failure, but a minority of them do go on to be successful and influential. Some startups become unicorns: privately held startup companies valued at over US$1 billion. [Source of information: Wikipedia] https://images.unsplash.com/photo-1556761175-5973dc0f32e7?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=500&q=60" alt="startup image"> Startups play a major role in economic growth. They bring new ideas, spur innovation, create employment thereby moving the economy. There has been an exponential growth in startups over the past few years. Predicting the success of a startup allows investors to find companies that have the potential for rapid growth, thereby allowing them to be one step ahead of the competition.

Objective

The objective is to predict whether a startup which is currently operating turns into a success or a failure. The success of a company is defined as the event that gives the company's founders a large sum of money through the process of M&A (Merger and Acquisition) or an IPO (Initial Public Offering). A company would be considered as failed if it had to be shut down.

About the Data

The data contains industry trends, investment insights and individual company information. There are 48 columns/features. Some of the features are:

• age_first_funding_year – quantitative
• age_last_funding_year – quantitative
• relationships – quantitative
• funding_rounds – quantitative
• funding_total_usd – quantitative
• milestones – quantitative
• age_first_milestone_year – quantitative
• age_last_milestone_year – quantitative
• state – categorical
• industry_type – categorical
• has_VC – categorical
• has_angel – categorical
• has_roundA – categorical
• has_roundB – categorical
• has_roundC – categorical
• has_roundD – categorical
• avg_participants – quantitative
• is_top500 – categorical
• status(acquired/closed) – categorical (the target variable, if a startup is ‘acquired’ by some other organization, means the startup succeed)

Acknowledgements

• I would like to thank Ramkishan Panthena, for providing us this dataset. He is a Machine Learning Engineer at GMO.
• This dataset was used in data sprint #5 at DPhi.

Inspiration

Predicting the success of a startup allows investors to find companies that have the potential for rapid growth, thereby allowing them to be one step ahead of the competition.

--- Original source retains full ownership of the source dataset ---