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Data Driven VC Report 2024
The current state of global data driven vcs, trends, and market expectations explaining why venture capital funds need to become more data driven. 35% of data driven venture capitalists claim that their data-driven tools are responsible for half of the deals sourced today.
This Data Driven VC Landscape Report was created by Andre Retterath, Partner at Earlybird VC, and is based on several external sources and a survey conducted by 300+ VC Firms across the globe. The data on usage and coverage of tech stacks and vc value chain are based on 190 data-driven vc funds.
The VC Investment Process is Evolving
Traditionally, the venture capital sector has operated in a highly manual and inefficient manner, with limited technological innovation for investors to leverage and utilise. Access to data was constrained, and the high costs of computing made it difficult to support the workflows of investors effectively. The ability to make sound investment decisions was predominately gained through experience, hours of manual research and conversations, and quantitive analysis provided by the technologies companies.
With current inefficiencies in how the venture capital industry operates, we conduct a deep dive into the data-driven VC landscape report to highlight key findings from some of the leading data driven venture capital firms leading the frontier in venture capital investing.
This shift to a data driven approach is fundamentally reshaping the landscape of venture capital, making the industry more agile and insightful. The VC funds are not only improving how they allocate resources but also enhancing their ability to identify and capitalize on investment opportunities.
By 2025, more than 75% of venture capital and early-stage investor executive reviews will be informed by artificial intelligence and data analytics.
Why do venture capital funds want to become more data driven?
The primary reason venture capital funds want to become more data-driven is to enhance efficiencies. The shift towards data driven approach allows venture capital firms to manage their diverse and demanding roles where investors are often stretched thin, juggling numerous tasks from - engaging with founders and evaluating new deals to fundraising and managing existing investments. Ruthless prioritization is essential in this field.
Data-driven tools offer significant advantages by enabling investors to streamline their processes. These tools help venture capital firms gather insights from diverse alternative data sources, automate mundane repetitive tasks, and incorporate valuable analytics into their investment decision-making processes.
ChatGPT has accelerated data-driven venture capital adoption
The combination of technological advancements such as algorithms, data, and computing has helped shift the venture capital industry forward to become more data driven.
The launch of Chatgpt has been wildly adopted and has already seen 40% efficiency gains for investors who are using the tool. Junior investors are armed with information and insights to help them perform at an expert level and save hours of manual research.
35% of data driven venture capitalists claim that their data-driven tools are responsible for half of the deals sourced today.
Most Data Driven Venture Capitalists already use Large Language Models (LLMs) extensively
Large Language Models (LLMs) have revolutionized various industries including venture capital with their capabilities to generate text, process vast amounts of data, and deliver actionable insights. This is evident with a survey response of 66% of venture capitalists leveraging LLMs into their modern investment workflows. LLMs are particularly valuable in automating the qualitative tasks involved in sourcing and screening potential investments. Its popularity among venture capitalists stems from their ability to efficiently synthesize information, which accelerates decision-making processes and enhances the accuracy of investment evaluations. This technological advancement not only saves time but also significantly boosts the productivity and effectiveness of investment strategies.
Shifting from inbound to outbound sourcing
Venture capital returns often adhere to the power law, emphasizing the importance of investing in outlier companies to achieve substantial returns. Missing the chance to back these standout ventures can result in significant financial losses for VCs. Utilizing data-driven tools can expand a VC's capacity to source potential investments, thereby improving their ability to select promising opportunities and build a robust deal pipeline.
As the use of data driven approach becomes more prevalent, traditional VCs without these tools may find themselves at a severe disadvantage, potentially missing out on lucrative opportunities. In an increasingly competitive market to fund top-tier companies, data driven VCs will gain a competitive advantage and be better positioned to seize emerging opportunities.
The shift towards outbound sourcing strategies is gaining traction over traditional inbound methods. Outbound sourcing involves actively seeking out and engaging with potential investment opportunities, rather than passively waiting for opportunities to approach the VC. This proactive approach is becoming increasingly popular because it allows VCs to build a connection with the founders early on, before they become widely known and sought after in the investment community. This early engagement is critical in a market where timing can significantly influence the success of an investment.
While a fifth of data driven venture capitalists are still ramping up their initiatives, about a third already source more than half of their investments via modern tools.
Most firms struggle to cut through the noise and find the best tool & data providers
Venture capital firms face specific challenges when navigating data providers and tools available, largely due to their unique needs for rapid, accurate and comprehensive data to make informed investment decisions. Additionally, there’s a large volume of data ranging from the market, which can be overwhelming and difficult to manage without the right tools. Sifting through irrelevant data to find actionable insights is time-consuming and costly.
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