đ Hi, Iâm Andre and welcome to my weekly newsletter, Data-driven VC. Every Tuesday, I publish âInsightsâ to digest the most relevant startup research & reports, and every Thursday, I publish âEssaysâ that cover hands-on insights about data-driven innovation & AI in VC. Follow along to understand how startup investing becomes more data-driven, why it matters, and what it means for you.
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Welcome to our monthly wrap-up episode where weâll cover Aprilâs most relevant content at the intersection of VC, startups, data, AI & productivity. I read it all so you donât need to - here we gođ
INTERESTING RESEARCH & REPORTSđ
Is Founder Response Time Predictive of Future Success?
Adam Shuaib from Episode 1 ran the numbers:
They identified every startup in their CRM that they had exchanged 3+ emails with. This number was large enough to capture the median response time for each founder, but small enough not to bias the dataset.
Total of ~1500 startups from 2012-2020 raising a seed round. They didnât analyse companies/emails after 2020 to ensure everyone in the analysis had enough time to raise further funding.
For each company, they identified the median founder response time (in hours) to the first three emails they had exchanged with them.
The metric for success is always difficult to pin down, but they opted for companies that went on to raise a future Series-A funding round (approx. 10% of dataset).
âď¸ KEY TAKEAWAY
Founders that went on to raise future Series-A rounds responded TWICE as fast to emails as those that didnât end up raising a Series-A.
SaaS Playbook From 0 to 30M ARR
The inaugural edition of the ChartMogul SaaS Growth Report has arrived, offering a treasure trove of insights into the growth trajectories of over 2,200 SaaS businesses. From zero to $30M in annual recurring revenue (ARR) and beyond, here are the key findings from the deep-dive analysis:
Stabilized Growth Rates: SaaS growth rates have shown stabilization in the last three quarters, with best-in-class startups accelerating and new business activity increasing.
Fast Track to $1M ARR: The elite SaaS startups hit $1M ARR within 9 months, a stark contrast to the median timeframe of approximately 2 years and 9 months. Moreover, the journey to $10M ARR averages just over 5 years.
Subscriber Base Growth: The bulk of SaaS startups expand from $1M to $10M ARR primarily by enlarging their customer base, with less than 5% relying on increasing their average revenue per account (ARPA).
âď¸ KEY TAKEAWAY
The report illuminates the path for emerging SaaS businesses, highlighting the importance of rapid ARR milestones achievement, subscriber base expansion, and retention. As the landscape continues to evolve, these insights offer valuable benchmarks for startups navigating their growth strategies.
Decoding the Science of Product-Market Fit
In our last episode, we identified bad product-market fit as one of the top reasons why startups fail. Luckily, First Round Capital published a comprehensive report helping founders transform PMF from art to science. The report focuses on sales-led B2B startups but many of the very actionable findings transfer to other verticals as well.
Four Concrete Levels: First Round identifies four levels of PMFâNascent, Developing, Strong, and Extremeâeach requiring different strategies and outcomes. This methodological segmentation helps founders identify their current position and strategize for progression.
Three Critical Dimensions: Their framework expands PMF assessment beyond mere customer satisfaction to include demand and efficiency. This ensures the product not only meets needs but is also scalable and market-ready.Â
Leveraging Tactical Levers: The framework introduces four leversâPersona, Problem, Promise, Productâthat founders can adjust to streamline their path to PMF, drawing from real-world applications by companies like Looker and Ironclad.
âď¸ KEY TAKEAWAY
First Round's PMF Method provides a more navigable path to finding product-market fit, potentially reducing the role of luck and emphasizing strategic effort. With peer benchmarking and practical exercises, it offers founders a detailed roadmap to reach and sustain PMF.
INSPIRING TECH IN VC CONTENTđĄ
âHow to Model a Venture Capital Fundâ deep dive by Taylor Davidson via OpenVC here, exploring what it means to create a financial model for a venture capital fund, the various ways you can create a portfolio construction and operating cash flow model, and providing you with templates and examples that you can use for modeling your own fund
âEnhancing Knowledge Graphs with LLMs: A novel approach to keyword extraction and synonym mergingâ by Valentin Buchner from EQT here, sharing their experiment of using GPT-4 to extract keywords with relevant frameworks, using OpenAIâs ADA embedding model to embed the extracted keywords, and applying the simple but novel PAIRWISE methodology to detect and merge potential synonyms
EVENTSđ
đĽFew days left until our virtual Data-driven VC Summit 2024 on May 5-8. Weâll have the Champions League of thought leaders at the intersection of data-driven innovation and AI in VC, hailing from top organizations like BLACKROCK, EQT, INDEX, ICONIQ, LIGHTSPEED, STANFORD, and more - details heređĽ
âTECH IN VCâ JOBSđŠâđť
đĽSenior Software Engineer @Earlybird VC in Munich or Berlin heređĽ
đĽSoftware Engineer Intern @Earlybird VC in Munich or Berlin heređĽ
Tech Lead @All Iron Ventures in Bilbao here
AI/ML & Data Intern @Cathey Innovation in Paris here
Research Manager @Endeavor in NYC here
Analytics Engineer @Dawn Capital in London here
Data Engineer @Ethereal Ventures remote here
Senior Data Engineer @Growth Equity Firm in the Bay Area here
Analytics Engineer @Tidemark Capital in San Francisco Bay Area here
THIS MONTHâS DATA-DRIVEN VC EPISODESâŽď¸
Essays
Insights
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If you have any suggestions, want me to feature an article, research, your tech stack or list a job, hit me up! I would love to include it in my next editionđ.
Thanks Andre good summary for the early morning