Recently, I led research at UpYouth on analyzing the batch data of Y Combinator in Southeast Asia from 2013 to 2023. This includes the analysis of 217 founders and 111 startups enlisted to YC in the region.
The facts were interesting: 60% founders went to elite universities; 70% founders have prior work experience in product development or growth; only less than 30% were first-time founders.
Many more interesting insights can be found in the research. I recommend reading the research first before moving forward with the article.
In this article, I will address the methodology of the research that the team didn’t include in the public version released by UpYouth. This includes:
What are the data sources used in the research and how did we process them?
What variables were used in the research?
How are the variables calculated and what’s the rationale behind them? (e.g. what is an elite university)
Methodology of the research
The goal of this analysis is to uncover the key factors behind the success of founders enlisted in YC in Southeast Asia.
To achieve this goal, the research employs both a quantitative and qualitative approach. However, in the public release of the UpYouth’s Founder Roadmap research, the qualitative approach is not mentioned.
Quantitative Approach
Raw data regarding YC startups in SEA is scraped from the official YC Startup Directory using Beautiful Soup 4.
This data includes:
Startup Name
Startup Batch
Startup Industry
Startup Description
Social media including Crunchbase and LinkedIn
LinkedIn and Facebook of Startup’s Founders
Psst… you can refer a friend to get a list of 111 YC startups and 217 YC founders above. This is an exclusive offer for my subscribers.
From the Crunchbase of each startup, the research scraped funding data including:
Last Funding Amount
Total Funding Amount
Funding Stage
From the LinkedIn of each founder, the research scraped their personal data including their work experience and education history. This is done using ProxyCurl.
From this data, critical work and education variables regarding a founder’s success can be retrieved and calculated. The variables with description can be found below:
Frequently Asked Questions
What is an elite university?
In the research, universities are not only categorized based on their rankings, but also:
Startup Ecosystem within their area of establishment
Their entrepreneurship program
Proximity with other elite universities based on previous criteria.
As academic rankings such as QS cannot convey the entrepreneurial support that founders receive, the addition of other factors is necessary.
To automate the calculation process, these metrics are calculated using a LLM model (gpt-4-turbo) with relevant agents with access to Internet. Each university is given a score of 1 to 5 based on these metrics.
Afterwards, the data is then filtered by a team member to ensure correctness.
Examples of elite universities include:
Havard University and its schools.
The University of Hong Kong
Nanyang Technological University
Singapore Institute of Management [based on Proximity]
What are the implications of the research?
The research is not a guide for founders to base their life decisions on. It is merely a statistical way of looking at founders and guessing their success.
Founding a successful companies take much more than your educational and work background. It takes courage, grit and more.
These are personal characteristics that are shaped by your environment, especially work and education, however, can be shaped elsewhere as well. So keep believing and keep fighting, regardless of your odds and environment.
“All our dreams can come true, if we have the courage to pursue them.” - Walt Disney
Fundamentally, the question of which characteristics a successful founder must have is a rather interesting one. This is addressed with the qualitative side of this research, which will be released in the future.
Bro I love this. Keep this stuff coming.
Btw, could you help change The university of Hong Kong to The University of Hong Kong?