The single reason startups win, and the many reasons they don't
Today we analyse two large data sets encompassing 638 startups in total to decipher why they succeed or why the fail, and the results are surprising...
CB Insights released a list of 438 startups and the reasons they failed.
I have read each end every summary (which took quite a long time) and I really wish I could hear some of those stories direct from the Founders.
To make up some time, I then used ChatGPT4o to analyse them and help me categorise the reasons for failure, and the proportional percentage.
I did this because I wanted to cross reference the learnings from CB Insights’s list of 438 failures with the insights from a great Ted Talk by Bill Gross “The single biggest reason why startups succeed”.
Bill Gross makes a convincing case (using real life data from his analysis of 200 startups) and tells us that the number one reasons startups succeed is… Timing.
Bill Gross has been an entrepreneur since he was 12 years old, founded IdeaLab, and started 100 companies. Through his direct experience, and his analysis of 100 other startups, he realised that timing was the single most important factor for startup success.
“The startup organisation is one of the greatest forms to make the world a better place. If you take a group of people, with the right equity incentives, and organise them in a startup you can unlock human potential in a way never before possible.“ - Bill Gross
Amen to that Bill!
Let’s compare these main reasons for success from Bill Gross analysis of 200 startups to the CB Insights analysis of the reasons why 438 startups failed.
Reasons for Failure - ChatGPT4o Analysis of CB Insights report
No Market Need (42%)
Many startups fail because there is no real demand for their product or service. They develop solutions that don't solve a significant problem or address a market need.
Ran Out of Cash (29%)
Insufficient funding is a common issue. Startups often underestimate the amount of capital required to reach profitability, leading to financial exhaustion.
Not the Right Team (23%)
Having a well-rounded, skilled team is crucial. Many startups fail because they lack the right mix of expertise or face internal conflicts.
Got Outcompeted (19%)
The competitive landscape is tough, and startups often get outmaneuvered by better-funded or more agile competitors.
Pricing/Cost Issues (18%)
Incorrect pricing strategies or high costs can prevent startups from achieving sustainable profitability.
Poor Product (17%)
Failure to develop a product that meets customer expectations can lead to high churn rates and low customer acquisition.
Need/Lack Business Model (17%)
A viable business model is essential for long-term success. Many startups fail to develop a sustainable model, leading to collapse.
Poor Marketing (14%)
Even great products can fail without effective marketing. Startups often underestimate the importance of marketing in acquiring and retaining customers.
Ignore Customers (14%)
Neglecting customer feedback and failing to adapt to their needs can lead to product-market misalignment.
Product Mis-Timed (10%)
Timing is crucial. Some startups launch too early or too late, missing the optimal market window.
These percentages indicate the proportion of startups that cited each reason as a primary factor in their failure. The cumulative total exceeds 100% as many startups fail for multiple reasons simultaneously.
…… end ChatGPT4o……
I found the above from ChatGPT4o very helpful. It took around 2 seconds (and 4.32g of CO2, which is a lot) to have ChatGPT4o deliver this for me, but I really dislike the summary statement it always puts at the end:
“This comprehensive categorization and percentage split provide valuable insights into the common pitfalls faced by startups, helping future entrepreneurs to avoid similar mistakes.” - ChatGPT4o
Thanks for stating the bleedingly obvious ChatGPT.
Now then, how do we reconcile these two data sets:
Bill Gross 200 startups
key reason for success = Timing
Vs.
CB Insights 438 startups
key reason for failure = No market need
It’s fascinating that “timing” is not included in any of the CB Insights reasons for failure.. (despite “product mis-timing” being the lowest factor indicated at 10%) but surely timing is a reason for failure as well as a reason for success?
I suppose that “no market need” speaks to timing in some ways, as the needs of the market can change… quickly. For example:
Airbnb's success can be attributed to the timing of its launch during the 2008 financial crisis which capitalised on people seeking extra income and affordable travel options, giving a strong market need.
Whereas the failure of Quibi can be attributed to Covid-19. Quibi was an American short-form streaming platform that generated content for viewing on mobile devices, launched in 2019 and by late 2019, announced it had sold out its first-year advertising inventory, which amounted to $150 million! However, the COVID-19 pandemic in 2020 caused a misalignment with market needs, as people preferred long-form content during lockdowns, not the short-form content designed for on-the-go consumption. This unfortunate timing and consequential destruction of “market need” directly led to Quibi’s failure.
The top two reasons for failure are No Market Need 42% and Ran Out of Cash 29%.
This makes me think that the barrier to entry for startups is actually quite low, so almost anyone with an idea can make the attempt. But it also speaks to many of these ideas being a “solution looking for a problem”.
I was recently involved in a failed startup and have been deliberating deeply on if it was a “solution looking for a problem” (ie no market need) from the outset or if it’s failure was due to unfortunate timing (which it was), or hiring the wrong people, who failed in their roles burning time and money (which they did), or simply running out of cash before they could get the traction required to raise more capital (which was the nail in the coffin). Three Strikes? Yup.
Here are some excerpts from the final shareholders report:
Since I’m on the Board of a range of companies I have a unique and diverse set of “Windows” into their journeys.
One mining tech startup raised the funds required to build their MVP and market themselves properly in their angel round ($3M, out of which around half was spent on product and half on marketing) which enabled them to pay for the advertising to buy the user growth to make the traction trend lines attractive to investors.. despite this, most VCs said “come back when you’ve hit $1M ARR”. Luckily, they managed to raise an additional $1.5M based on their user growth and engagement, largely from their existing angel investor base.
This was more or less the plan with Routinr but they only ever managed to raise enough money to build the MVP platform.. and then failed to raise the funds required to market it, leaving them stuck in the no-mans land of “come back when you have some traction”. Despite much hustle, grit and equity-for-service deals to drive growth nothing achieved the traction required to attract investor interest and during this time the market tanked, AI launched and the world moved on.
In summation, timing is crucial.
Successful startups often find the sweet spot where market demand, technology, and culture intersect (through great strategy and timing) while getting lucky with investors, staff and execution. When I say lucky, I mean it.. if your investors and new hires do what they say they are going to do - instead of the opposite - then your startup is on track and growing, which is very lucky… and you put your startup “in lucks way”.
I previously wrote about the great success story of a startup and have pondered the impact of timing. In the case of Aldi Mobile timing was absolutely crucial, given the transition from 3G to 4G which enabled them to access and monetise remnant 3G inventory… but the timing would have amounted to nothing had the strategy not been in place.
In the case of the trillion dollar company I wrote about it was outstanding long term strategy (and good luck during the interceding period) that enabled the interplay of three strokes to deliver a great success as they became the world’s most valuable company.
What both of these companies did was form a view of the future, base their strategy on it, get the timing right, and get lucky along the way.
I wrote about the future because I feel strongly that if we can predict it to some degree (as the two examples above have, and won because of it) then we can put ourselves and our companies in good lucks way as that future unfolds.
What do you think?