Top Venture Capital Funds Taking a Data-Driven Approach

The venture capital industry is extremely competitive, and it’s because there are only a finite number of top-returning investments in the best companies. Investors have to fight to get into those deals. Historically, these companies were sourced by building a strong network, referrals, reputation and track record to get access to the top founders. For an industry that invests in innovation, it’s ironic that the industry operates human capital intensive and software-light to find the best companies. But all of that is changing as the venture capital landscape is shifting and is adopting a more data-driven approach to investing. 

It’s hard to pinpoint exactly who pioneered the data-driven approach but if you’ve ever read “The Power Law Venture Capital and the Art of Disruption” by Sebastian Mallaby, he mentions Correlation Ventures attempting a data-driven approach to venture capital investing back in the mid 2000's. They attempted to leverage databases of venture outcomes to inform their investment decisions. However, this approach faced its hurdles primarily because it was ahead of its time and there was a lack of available data in the start-up sector, not to mention the technology that was available at that time. This was the same period as the rise of mobile phones, applications, social media networks, and cloud computing. 

Fast forward 20 years, and we’re in the data era where venture capitalists are looking to take a more data-driven approach to their investing. With the influx of data and technology tools at their disposal such as artificial intelligence and machine learning, it’s become evident that data-driven investing provides a clear advantage. Some of the advantages include:

1. Sourcing opportunities outside of your immediate network to get full market visibility, 

2. Supercharging pre-screening and due diligence

3. Monitoring and tracking companies & founders

4. Portfolio support from hiring to referring the right experts to guide them through company building.

Note to founders, start leaving your trails online about what you’re building, if you’re on the right path - they’ll come knocking on your door. 

Without further adieu, Landscape has researched some of the top Venture Capital Firms taking a data-driven approach (with no particular order). I've also created a database of venture firms taking a data-driven approach at the end blog. If you'd like to add your fund's name to the list below, please feel free to reach out to me.

1. EQT Ventures: €1.2BN investing in Seed to Series B and made investments into over 100 companies
   Launched: the Motherbrain in 2016 with the ability to track and source companies during its life cycle. There have been reports that the Motherbrain conducts market analysis and monitors competitors. It provides expert & talent sourcing, as well as metrics benchmark. It's sourced 15 investments totally over €250M such as AnyDesk, CodeSandbox, Handshake, Griffin, WarDucks, and Peakons. 
   Team: 30 person development team

2. SignalFire: $2.1BN AUM investing in enterprise and consumer at seed and early growth stages.
   Launched: Beacon AI - initiated in 2015. The whole vision behind Beacon AI is to build a Bloomberg terminal for the start-up industry. Beacon AI has been able to source companies that are outperforming through alternative data sources. It’s also been built to evaluate the competitive dynamics of the sector and broader markets through data insights. In addition, it's able to see the competitive dynamics of the sector and broader market
   Cost: Here's the kicker... there are claims that it costs about $10M per year and is paid through advisory fees + management fees.
   Team Size: 7 person dev team

3. Earlybird Venture Capital - $2B AUM investing in early-stage digital technology opportunities with separate funds focused on regions as well as healthcare & deep tech.
   Launched: EagleEye operational 2018. Proprietary machine-learning-based deal-sourcing platform. Screening and analysing early-stage opportunities. There have been reports that they were able to source Aleph Alpha
   Team size: 7 person dev team

4. ICONIQ Growth Capital  - $1.1Bn AUM focused on investing in growth tech companies.
   Launched:  Iconiq analytics & insights to support data-driven decision making. It's custom analytics for individual portfolio companies to address critical questions, including benchmarking on key topics across companies varying in scale, growth & product type. Cohesive business advisory in objective data driven work. Comprehensive topical reports featuring proprietary insights and thought leadership.
   Team Size: 57 person dev team

5. Social Capital LP - restructured from a venture firm to a family office structure run by Chamath Palihapitiya, one of the besties on the All-in Podcast. It operates about $1.89bn AUM and mission-driven focused on healthcare and education businesses.
   Launched: 2016 - an operating system for early-stage investing dubbed “Capital as a Service.” CAAS is a collection of quantitative diligence tools developed to help VCs evaluate investment opportunities and make better data-driven decisions. It reduces diligence time and offers investors insights that are otherwise a burden. Founders also use CAAS to improve their pitches and drive investor conviction using transparent and defendable data.
   Team Size: 6 person dev team

6. Tribe Capital: $1.6Bn AUM investing in sector and stage agonostic investing in seed to growth stage technology companies with the focus of finding companies that have the potential network effect of N-of-1. 
   Launched: 2018 launched Magic 8-Ball from Maidenberg, Sethi and Hsu who were responsible for the CAAS operating system at Social Capital before the restructure. The magic 8-ball provides data modeling to source investments. Finds and helps build a network of partnerships with investors Tribe wants to work
   Team: 3 person dev team

7. Akkadian Ventures - $700M AUM investing in direct secondary investment firms focused on providing liquidity to early employees and investors of venture-backed businesses.
   Launched: in 2011 and has been tracking 20,000+ private tech companies. It's developed a proprietary, data-driven methodology to identify which private technology companies are entering hyper-growth and uses this data to "pre-approve" companies.
   Team: 1 person dev team

8. Redstone - $540M AUM early stage investing in sectors including climate, fintech, health, industrial, quantum, social impact & venture debt. 
   Launched - Took a decade to build Sofia.AI. They've are building an in-house data platform to gain valuable insights into market opportunities and trends. Supporting sourcing and screening for investment analysis.
   Team Size: 4 person dev team

9. Quantum Light Capital - $200M AUM AI-Led Venture Capital Fund started from Revolut’s billionaire Nik Storonsky.
   Launched - 2022 using sources like LinkedIn, corporate filings and other databases to identify fast-growing startups. The team is building machine learning algorithm for decision-making
   Team: 17 person dev team.

10. AngelList Early Stage Quant Fund - $25M AUM broadly indexing the market via exposure to thousands of deals on the AngelList platform annually. 
    Launched in 2021, AngelList’s platform has access to more than 15,740 proprietary startups on their platform. In 2021 alone, the funds and spvs on the platform invested 56% of all top tier early stage US Deals as well as have 2M users apply to startups to AngelList talent (rebranded to Wellfound) each quarter. Their proprietary data to make systematic investment decisions positions them uniquely to high quality data and hiring activity.
    Team: 21 person dev team

If you are a venture fund looking to become data-driven in a cost-effective way to get a competitive advantage to get access to sourcing and screening. You should check out off-the-shelf products like Landscape or book a demo.

Additionally, if you don't see your fund on the list and want to get added? Please feel free to e-mail me at [email protected]. I'll be adding funds to the free database of VCs taking a data-driven approach.