This is our first “Steeped Dive” article where we explore open-source studies and datasets using the Steeped AI platform. We used the platform's findings to draft and refine the content. We then auto-generated this full article, including charts and visuals, based solely on information from a spreadsheet. Steeped Dives are where real data meets curiosity to uncover diverse, meaningful insights. More Steeped Dive articles to come!

For this Steeped Dive, we analyzed CB Insights' "Startup Failure Post Mortem" dataset, which includes over 400 startups across six industry sectors from 1992 to 2024. As a startup ourselves, we saw value in learning from the challenges others have faced and gaining insight into the hurdles we might encounter. This dive also highlights how the Steeped AI platform can uncover statistically-backed findings even from smaller datasets.

Competition was by far the most common reason startups failed. 71% struggled to keep up with direct industry rivals, and an even greater 75% cited competition from tech giants. On average, these startups lasted 8 years and raised $145 million in funding. Among those that failed due to competitive pressures, the top contributing factors were low demand, overly niche products, and depleted resources. The peak years for these failures were 2020 and 2013.

While underfunding wasn’t the top reason for failure overall, 19% of failed startups cited it as a key factor. However, its impact varied widely across sectors—as did the average funding amounts. In Manufacturing, over half (52%) of failed startups pointed to underfunding, despite an average funding of $402 million. Healthcare followed with 38%, then Hospitality at 23% ($73M average funding), Retail at 19% ($128M), Tech & Information at 8% ($113M), and Financial Services also at 8% ($103M). These differences highlight how the supply and demand of funds for survival can vary significantly by industry.

Low market demand was cited by 20% of failed startups as a key reason for their downfall. Each company in the dataset included a “Lessons Learned” statement, many pointing to demand-related insights like “Solve a real pain” or “Stand out or drown.” The industries most affected by low demand were Healthcare (47%), Manufacturing (23%), Financial Services (23%), and Retail (22%). Interestingly, 96% of startups that exited via acquisition (23% of all failures) did not cite low demand as a factor. Similarly, 94% of Tech & Information startups (which made up 38% of failures) also didn’t attribute their downfall to lack of demand.

The "Lessons Learned" quotes included in the failed startup dataset add depth to the previously discussed reasons for failure. For instance, in the context of competition, one company remarked, “Giants gobble niches,” echoing the top-cited reason for failure: losing out to tech giants, particularly among niche startups.

Additional quotes related to competition include: “Small gets scooped,” “Giants own ads,” “Differentiate or die,” and “Giants rewrite rules.” Many companies also voiced concerns about limited funding, with quotes like: “Free eats paid,” “Passion doesn't pay,” and “Budget for long runways.” Several statements highlighted issues with low demand as well, such as: “Supply needs demand” and “Niche needs traffic.”

This is just the beginning of the insights we'll be sharing through Steeped Dives. Over the next two weeks, we'll be adding a new dataset focused on mental health headlines from news and events, which will be featured in an upcoming Steeped Dive.

If you're looking to uncover compelling insights in your own business or research data, feel free to schedule a demo here. At Steeped AI, we're driven by curiosity and precision. One side of our team is passionate about finding meaning in complex data, while the other is dedicated to building and refining powerful tools that tackle real-world challenges. This balance enables us to turn raw information into clear, actionable insights.