📈How Career Predicts Startup Success

A preliminary research article is tailored for VCs, offering data-driven insights into the relationship between a founder's career and startup success.

TL/DR

Most Successful Founders Background:

Cybersecurity
Serial Founders, Entrepreneurs, CEOs
Strategy
Product
Operations
Venture Investors
Design
Engineering/Developer-related roles
Digital and Innovations
Marketing
Sales and Business Development
SMM, Social Media, Content, Communities, Editors
Finance and Accountant
Researchers, Analyst
Academic Titles (Professor, PhD)
PR
Project managers
Account, Client and Customer-related roles
Legal
HR, Talent and Recruitment

The story

I wanted to discuss a topic with idea-stage founders, but how can I find these people if they don't call themselves founders at this stage?

I assumed it would likely be C-levels, multipreneurs, entrepreneurs post-exit (after rest), and tech guys. I asked myself with whom should I start? And then it hit me: LinkedIn could be a goldmine, allowing me to trace career paths that often lead to founding a startup, and, moreover, to a successful startup. If so, I could build a scoring model for VC deal flows.

Initially, I defined a startup as successful if it was VC-funded, indicating that an investor trusted its market fit. Next, I had to match the startup names from LinkedIn to Crunchbase data. However, matching two datasets seemed too complex for a rapid approach. Let's assume that a company operating for at least 3 to 5 years is sustainable in the market, whether it was funded or not. It could be a tech product or a marketing agency; it doesn't matter—the founder found the market and how to sell.

Long story short, there are no ways to quickly and freely acquire the data I need for trustworthy research. For example, I found one data provider that charges $0.28 per person with job experience, so researching 100K people would cost $28K. Some sources don't have or provide career experience or can’t filter by founded year. Despite such limitations, I've found alternative methods that provide an overview and meaningful insights following rapid research.

Sourcing data

Where to get founders

Initially, I explored various free data sources to assess their filtering capabilities. I recorded the overall number of profiles and attempted to determine the count of successful startup founders. This approach is crucial for gauging the market size and comparing data sources.

LinkedIn Search indicates ~1 billion profiles, of which 5,160,000 are founders. This represents a 0.5% founding rate, although it needs to be clarified how many of these startups are successful.

I also explored Apollo.io and Lusha, sales intelligence platforms for lead generation and managing contact databases. These platforms offer extensive filtering options such as industry, location, job title, and company size. They provide access to data on specific user segments on their free plans.

Apollo has 269M profiles, with 3.4M listed as founders, a 1.3% rate. Lusha shows a 2% rate with 2.3M founders. These figures include founders at all stages—successful, seed stage, or failed.

There is no filter by founding year In Apollo, so I used the Employees count filter 11+. It gives 1.4M founders, making up 40% of all founders. Lusha shows 47% in this category but has a 'year founded' filter. Using <=2020 as a benchmark for minimal success, 35% of founders meet this criteria.

Crunchbase with trial access provides a filter feature for the list of persons. It has a total of 1.8M profiles, with 845K listed as founders (47%). 493K founders have companies with 11+ employees (58% of all founders), and 391K have companies with 11+ employees founded before 2020 (46%). This success rate is similar to what I found on Apollo and Lusha, though the founding rate is notably higher.

So, what are the conclusions here? While Apollo and Lusha are sales tools, their databases primarily consist of business people or decision-makers. This could explain the difference in founder rates compared to LinkedIn. We can assume that LinkedIn includes up to 35% of successful founders, translating to approximately 1.8 million founders in its database.

While Crunchbase is a startup-focused tool, it has a 47% founding rate. It also has the smallest number of founders compared to other sources. This could be because Crunchbase focuses mainly on tech product startups. Although I believe business skills are universal, I've also observed numerous failures among successful offline entrepreneurs attempting modern tech, often due to a gap in the mindset essential for tech.

Tracing the Career Experience of Successful Founders

I used Crunchbase's query tool to find 265K founders with at least one investor. I then filtered by 'Past Jobs' to identify their prior roles, querying around 150 titles and whole job segments like 'Marketing.' This also let me gauge the prevalence of C-level positions. While useful for spotting patterns, this method has limitations—founders' careers can evolve, leading to multiple counts in the query.

Career insights within Crunchbase data

36% of founders having previously been founders or CEOs

Isn't surprising. It underscores the concept of the serial entrepreneur. Success or failure in prior ventures offers invaluable experience that often leads to subsequent entrepreneurial activities. The percentage may also be elevated because founders or CEOs might need to enter their full career paths into Crunchbase.

11% of founders with tech backgrounds

With half being CTOs, corroborates Crunchbase's tech-centric database. Any tech startup needs to have a CTO among its shareholders. The skew toward Data Science, Front-end, and Full-stack roles among engineers may signal that these skill sets are increasingly crucial for startup success. However, given the current hype around AI, Data Science emerging as the leader here is expected.

With 3.2% coming from operations

And two-thirds at the COO level, the implication is that a strong operations background prepares one well for founding roles. In cases where a tech-focused individual becomes CEO, or a strong leader takes the helm, a significant role arises for handling manual tasks and back-office work. This becomes even more crucial when the startup receives funding, requiring hiring and management. The question of who initially takes on the COO role merits further investigation.

Product, Sales and Marketing roles

Ta-da, a key insight I was looking for in this research is the breakdown of these roles:

2.7% are in product, with half of them in CPO roles
2.6% are in sales and business development, with half in C-level roles
2.1% are in marketing, with two-thirds in C-level roles

Product roles are multidisciplinary. A good product requires a blend of marketing, sales, and tech skills. I often see that jobs under 'marketing' involve just social media posting and managing ad expenses rather than a deep focus on market penetration, such as segmentation and hypothesis testing. This is crucial for product development, so I suspect many senior marketers hold product titles. That could explain why marketing ranks third in this group.

0.9% are researchers and analysts

While can come from various fields, they have a mindset that's essential for new ventures, especially during the big research and experiments leading up to Series A. Maybe great product managers are rising from analysts.

0.7% of finance roles

Are tending due to the strong presence of FinTech startups.

If considered separately, they would be at the bottom of the list. However, I bet on these roles because they interact directly with users. Understanding user needs and how to attract their attention could be especially valuable for B2C startups.

While other segments are also interesting, I leave room for your thoughts and comments.

How popular are these professions

The initial findings were absolute and didn't account for their proportionality in the job market. This perspective may not provide the most accurate view of job title distribution. For instance, if many people work in sales, it is unsurprising to see them among the top 10 roles for successful startup founders. To address this, I turned to LinkedIn to count how many people have experience in each profession segment.

I cross-referenced the initial data with LinkedIn's Search by Person for a fuller picture. I used the search's main and titleFreeText keywords to get more accurate results. However, these numbers could be better, too. For example, there's the potential for double-counting individuals who've held multiple roles throughout their careers.

At first glance, the distribution of professions differs. It's important to remember that this distribution is influenced by LinkedIn's user base, which may not accurately reflect the global profession market. However, given LinkedIn's popularity in the tech industry, these results are still informative. It should be compared with the initial table to make sense of this data.

Weighted results: Startup Founder Likelihood

To get weighted results, I used the 'Startup Founder Likelihood' (SFL) formula:

This formula considers the number of founders in each job title segment and its prevalence in the professional world.

The high SFL Quartile (SFL > 6.91) includes the expected serial founders, entrepreneurs, CEOs, product, strategy, and operations roles, and the unexpected inclusion of cybersecurity. Does this imply that cybersecurity folks, possibly natural white-hat hackers, have skills crucial for startup success? Or are they natural for managing risks?

The Upper-Middle SFL Quartile (1.73 < SFL <= 6.91) shows marketing and sales at the lower end, likely because there are so many salespersons and marketers globally. However, if we focus on the C-level rate on Crunchbase in these segments, they perform much better. Interestingly, design has made it into the top 10. Tech professions dropped due to the sheer volume of developers worldwide.

The Lower-Middle SFL Quartile (0.65 < SFL <= 1.73) features finance, primarily due to the many accountants included, but researchers and analysts are also present. It appears these professions are less directly linked to entrepreneurship.

The Low SFL Quartile (SFL <= 0.65) resembles the Crunchbase ranking closely. Given their importance in understanding client needs, I'm curious why customer-related roles fail to fare well. Is the low-level support roles skewing the data?

Conclusions

While I only spent a few hours acquiring and analyzing this data, it provided many insights that warrant further reflection. I'll take a closer look at individuals in cybersecurity to better understand the metrics I observed. I'm also curious about who typically steps into COO roles, which often come with co-founder status.

In summary, finding idea-stage founders is more nuanced than it appears, yet critical for venture capital deal flows. Leveraging platforms like LinkedIn offers a rich data source to build a predictive scoring model, enabling VCs to sift through the noise and identify true potential. This isn't just a hypothesis; it's an actionable strategy to revolutionize the early-stage investment game. The future of VC isn't about gut feeling; it's about data-driven decisions, honed by years of experience and augmented by the tools of tomorrow.

What insights have you gained from this preliminary research? Do you think a startup's deal flow can be effectively evaluated using career path metrics?

Calling VCs

I'm eager to refine this research with robust data, including segmentation by variables like country of origin and educational background. There are also lingering questions about career paths that I'm keen to explore. If you're a VC interested in more in-depth research and building scoring models for deal flows, let's collaborate to create a more data-driven venture funding landscape.

Last updated 8 months ago