The Ultimate Startup Failure Rate Report [2019]

Are you afraid of startup failure? You should be! It is estimated that 90% of startups fail, but you don't necessarily have to be part of that club. Continue reading to learn more about startup failure rates and how to avoid it 👇

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As you were reading the title and summary of this article, 40 new startups were created (and probably even more).

137,000 businesses give birth every day or 5 million per year, as established in this research.

But 90% of them fail... If we do maths, 123,300 fail every day and, in the time you were reading up to here, 85 businesses were probably shut down.

Okay, I know this is quite depressing and doesn't inspire you to start a business yourself. But by reading this article and learning why startups fail, you will be one step ahead than the rest of entrepreneurs.

Failory started as a website where we interviewed failed startup founders (and we still do it every week!). We have been doing this for 2 years now, so we feel confident to claim we are the experts of failure.

You might be thinking this isn't a title we should be proud of, but you need to understand that success is not achieved without stumbling with a few rocks on the road.

You need to get that title too... and this is a great place to start.

This article is divided into two parts:

  1. The first section will show you "The Startup Failure Rate Infographic": a long and detailed infographic on startup failure, common mistakes and how to avoid them.
  2. The second section has a deep analysis of the data of 100 startups that failed in the past 15 years. You will be able to play with charts and look for the data that's interest for you.

Let’s dive right in.

#1: The Startup Failure Rate Infographic

TL;DR of the following infographic:

  • 90% of startups fail... yeah, it's hard to accept it.
  • Information startups are the ones that tend to fail the most.
  • Construction and manufacturing have both really little success rates.
  • Many startups fail due to incompetence, lack of experience in terms of goods and industry, little experience from the team and personal problems.
  • Successful startups have a well-defined market, have disruptive ideas and the founders are persistent and take advantage of mentors.

Startup Failure Rate

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#2: Analyzing Why 100 Startups Have Failed

As shown in the infographic, multiple sources have analyzed startup failure data, and found failure rates as high as 90%.

Now, why do so many startups fail?

And more importantly, how can you overcome failure as a startup founder?

In this section, we’ll equip you with an action plan to avoid failure. We’ll show you how you can efficiently analyze startup failure data, and grow your business thanks to these new data insights.

An interactive dashboard to analyze startup failure data

If you want to learn from previous failures, the first thing you need is accurate data on the subject. In this article, we’ll rely on the Startup Cemetery, which assembles startup failure data from more than 100 startups, containing:

  • Company data: #employees, #founders, industry, location,...
  • Funding information: #investment rounds, #investors, total amount of funding,...
  • Startup failure data: cause of failure, year of failure, type of outcome,...

In order to properly analyze all that startup failure data, we loaded it into a visual Cumul.io dashboard. In that way, you can explore the data interactively & spot correlations or trends in the blink of an eye.

Below, we’ll further deep-dive into the dashboard and how to use it. However, if you’re eager to start exploring yourself: play around with the embedded dashboard below!


<div id="startup-cemetery"><script type="text/javascript">(function(d, a, s, h, b, oa, rd){if (!d[b]){oa=a.createElement(s), oa.async=1; oa.src=h; rd=a.getElementsByTagName(s)[0]; rd.parentNode.insertBefore(oa, rd);}d[b]=d[b]||{}; d[b].addDashboard=d[b].addDashboard||function(v){(d[b].list=d[b].list || []).push(v)};})(window, document, 'script', 'https://cdn-a.cumul.io/js/cumulio.min.js', 'Cumulio'); Cumulio.addDashboard({dashboardId: '863021f9-d4b7-4340-8b11-df93c316d8e1', container: '#startup-cemetery',});</script></div>

How to read this startup failure data?

As a founder, how can you derive useful insights from all that startup failure data? A global view on why startups fail is interesting, but how do you take action on such a dashboard?

This startup failure data becomes truly valuable if you start filtering them on characteristics that apply to your own business.

Here are 3 simple steps to help you use the dashboard above efficiently:

1) Assess the status quo of your business

  • Which stage of business, industry, market are you operating in? e.g. an e-commerce business with 25 employees, 2 funding rounds, 3 investors,...
  • Identify key challenges: what are your biggest struggles at the moment? e.g. struggling with marketing, product development,...

2) Filter the dashboard on this key information about your business
e.g. Look at the most common reasons of failure for an e-commerce business, in which stage they typically fail,... Or act the other way around: filter on your struggles as a reason for failure and get insights into the businesses that failed before due to that same reason

3) Identify threats and possible actions to take
e.g. Let’s say your key challenge is cash flow, and you see that many similar businesses failing because of a bad business model. Together, this might indicate that your business model needs improvement, which could help improve the cash flow and avoid business failure.

Following this path, you can learn from your predecessors and avoid the same mistakes they made. Practice what you preach? Let’s put these 3 steps into practice!


An example: how can an e-commerce startup use the dashboard?

Let’s illustrate this with a fictional example. Imagine you are running JustDress.com, an e-commerce business that’s selling their own brand of women's clothing online. How can JustDress.com make use of our startup failure dashboard?


Step 1: Getting to know JustDress.com & its challenges

First, you’ll want to get a solid understanding of this e-commerce business. Let’s have a look first at what we know about the company:

  • The company was founded in San Francisco, USA in 2016
  • Active in the e-commerce sector
  • Grew from 2 founders to 20 employees in 3 years
  • They raised $500K in 1 funding round with 3 different investors

Looking back over the past 3 years of activity, their biggest challenge has been the highly competitive landscape. They lose a lot of customers to competing clothing retailers, both online & offline.


Step 2: Replicate the JustDress.com case & challenges in the dashboard

Now, to find useful insights for JustDress.com in the dashboard, you’ll want to filter on characteristics they have in common with previously failed businesses.

Let’s start with JustDress.com’s main challenge: competition. What do they have in common with businesses that failed due to high competition? If you filter the dashboard on competition as the reason for failure, you’ll spot the following insights:

  • Only 1 out of 15 startups that failed due to competition is active in e-commerce. This could indicate that failure because of competition is not so common for e-commerce.
Failed eCommerce due to Competition
  • Failure because of competition is the highest for startups that have been active 3 to 5 years.

Next, you can filter the dashboard specifically on e-commerce startups, as they ran their business in the same category as JustDress.com. What can we learn from other startups that failed in e-commerce?

  • In terms of funding, failure rates were highest for e-commerce startups that had only 1 funding round, as is the case for JustDress.com.
  • E-commerce businesses in the past have failed mostly due to a combination of reasons, or lack of experience.

You can do the same for other parameters. For example, you can filter the dashboard on startups with 11-50 employees or on startups that were active for 3 years when failed.


Step 3: Define actions to take for JustDress.com

So, we found some interesting insights when looking at failed companies that have similar business characteristics as JustDress.com. The next step is: how can they take meaningful actions on these insights? We listed 4 insights, so here are 4 possible actions for JustDress.com.

  1. Talk to other e-commerce companies to understand how they managed to deal with a competitive market. Since it’s not a common reason for failure, they can still learn from others’ success.
  2. Research similar businesses to yours that are active longer than 5 years. Learn how they were able to overcome their challenges at earlier stages of business.
  3. Failure rates are high for e-commerce startups with lower amounts of funding. So deep-dive into your cash flow, and see if you’re managing your funds well enough to move forward.
  4. Assess your startup for multiple bottlenecks. Apart from competition, are there other challenges you’re dealing with? Is your team experienced enough? Make sure that you are aware of any possible threat: a combination of smaller issues adds up to the bigger picture.

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4 general trends we identified from startup failure data

Now that we’ve looked at a specific use case, it’s also interesting to look at wider trends that might be insightful across all sectors and sizes. We identified a number of general trends in this set of startup failure data.


1. Company size

The chart below looks complex at first sight, so let’s illustrate how to read it properly. By hovering over a specific value, you can see how the data flows for that specific category.

For example, hover over productivity. You’ll see that failed productivity startups had a different number of founders, but no clear pattern. However, after that, you can see the data converging again: most of the failed productivity tools were companies of 11-50 employees.

<div id="alluvial-startup-failure-data"><script type="text/javascript">(function(d, a, s, h, b, oa, rd){if (!d[b]){oa=a.createElement(s), oa.async=1; oa.src=h; rd=a.getElementsByTagName(s)[0]; rd.parentNode.insertBefore(oa, rd);}d[b]=d[b]||{}; d[b].addDashboard=d[b].addDashboard||function(v){(d[b].list=d[b].list || []).push(v)};})(window, document, 'script', 'https://cdn-a.cumul.io/js/cumulio.min.js', 'Cumulio'); Cumulio.addDashboard({dashboardId: '863021f9-d4b7-4340-8b11-df93c316d8e1', container: '#alluvial-startup-failure-data', chartId: '9082193c-9b56-4be4-a506-b746b5ee87cd', chartDimensions:{width: 'auto', height: '400px'}});</script></div>

Now, if you just look at the distribution of the right column, you can already see a trend emerging. The largest chunk is that of 11-50 employees, followed by 1-10 employees. This indicates that failure was more common among smaller companies below 50 employees.


2. Failure outcome

When a startup fails, there can be multiple outcomes: it can be acquired by another firm, the founders can decide to shut it down, or the company can go bankrupt.

Looking at the funnel chart below, you can see that a shut-down is the most common option. Acquisition is second in line, so let’s filter on acquisition to see if there are any similarities among acquired companies.

Startups per outcome
Acquisition filtering

Looking at the alluvial diagram, you can see that there are quite some acquired startups that had a high number of investors. Let’s dive into that a little deeper: what if we filter outcome only on startups that had more than 20 investors?

Number of Investors

The chart above shows that, in case of a very high number of investors, the company is more likely to be acquired than to shut down.


3. Time

Are there certain patterns to the timing when companies fail? Are failures more common in the beginning phase of a startup, or does it also happen to more mature companies?

<div id="time-startup-failure-data"><script type="text/javascript">(function(d, a, s, h, b, oa, rd){if (!d[b]){oa=a.createElement(s), oa.async=1; oa.src=h; rd=a.getElementsByTagName(s)[0]; rd.parentNode.insertBefore(oa, rd);}d[b]=d[b]||{}; d[b].addDashboard=d[b].addDashboard||function(v){(d[b].list=d[b].list || []).push(v)};})(window, document, 'script', 'https://cdn-a.cumul.io/js/cumulio.min.js', 'Cumulio'); Cumulio.addDashboard({dashboardId: '863021f9-d4b7-4340-8b11-df93c316d8e1', container: '#time-startup-failure-data', chartId: '5d0d9a20-4b24-4895-bf47-b56cb7d94721', chartDimensions:{width: 'auto', height: '400px'}});</script></div>

The chart above shows that only 10% of startups in this dataset have failed during their first year. Failure is most common for companies that have been in business between 2 and 5 years: a striking 70% of the total.


4. Cause of failure

There’s a whole array of reasons why businesses fail. But can we see patterns among the companies that failed for the same reason?

Why 100 startups failed?

The chart above shows you the main causes for startup failure. In the full dashboard, you can click on a specific cause to filter only on startups that failed due to this specific cause. A few learnings we spotted while filtering:

  • Companies that failed due to mismanagement of funds typically have many investors involved, and passed several investment rounds.
  • The same goes for startups that failed due to legal challenges. If you drill down, you’ll see that many of these companies also had a higher number of investors involved.
  • Larger companies have a hard time coping with competition: of all failures due to competition, 60% were companies that have more than 50 employees.
  • A bad business model typically strikes a business before it scales: 64% of startups that failed due to a bad business model had less than 50 employees.

Similar to the examples above, you can filter the startup failure data in the dashboard on your current company size, funding situation and sector. In that way, you can see what the most common reasons were for failure of companies similar to yours.

Final Notes

Each company fails for its own reasons. The startup failure dashboard shows that there are a lot of circumstances and variables that can have an impact on why a business fails. But as shown above, there are always larger trends that possibly coincide for multiple businesses.

As a founder, there’s nothing more valuable than knowing the common pitfalls beforehand. You can learn from other businesses’ failures and apply these learnings to your own startup. There will always be challenges to overcome, but being ahead of the game will make your chances of survival much more likely!

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