DDVC Landscape 2024

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Key takeaway

For entrepreneurs: Data-driven VCs are becoming more prevalent, potentially offering more efficient and effective funding opportunities, but also increasing competition for attention.
For investors: Adopting data-driven approaches is becoming crucial for staying competitive in VC, with potential to improve deal sourcing, screening, and portfolio management.

Summary

The Data-Driven VC Landscape 2024 report highlights the growing trend of venture capital firms adopting data-driven approaches to improve efficiency, effectiveness, and inclusiveness in their investment processes. The report provides insights into the current state of data-driven VC, including market benchmarks, tools used, and future outlook. It emphasizes the importance of leveraging AI, modern tools, and data analytics to gain a competitive edge in deal sourcing, due diligence, and portfolio management.

Insights

75% of surveyed VCs believe the "Augmented VC" model (human-in-the-loop with AI) will dominate the future of venture capital.
35% of data-driven VCs claim their tools are responsible for half of their deal sourcing.
The median data-driven VC firm has $450M AUM, 40 employees, 2 engineers, and 10 investors.
Most data-driven VCs use a combination of internal and external tools, with a focus on developing proprietary solutions.
LLMs are widely used across the VC value chain, particularly in screening, due diligence, and reporting.
The top challenges in becoming data-driven include finding the right tools, data sources, and making data actionable.

Implications

VCs not adopting data-driven approaches may fall behind in deal sourcing and evaluation capabilities.
Entrepreneurs may need to adapt their pitching strategies to appeal to both human investors and AI-powered screening tools.
The VC industry may see increased efficiency and potentially reduced team sizes due to AI and automation.