Eagle Alpha’s Alternative Data Conference in New York on February 12, 2025, brought together industry leaders, investors, and data providers for a day of in-depth discussions on the evolving alternative data landscape. Recognizing the growing reliance on data in private markets, we dedicated an entire Private Equity Track to exploring how PE professionals are leveraging data to make better investment decisions, gain a competitive edge, and unlock new revenue streams. From deal sourcing to portfolio management, private equity firms are increasingly integrating a Private Equity Data Strategy by adding AI, alternative data, and advanced analytics into their workflows. The conference also tackled broader industry themes, including regulatory scrutiny on AI and alternative data usage, as well as insights into hedge fund technology. A summary of key private equity panels is presented below.
How Investors and Lenders in Private Companies are Using Technology & Analytics as a Competitive Weapon
David Teten, a seasoned investor in the VC and private equity space, shared his insights on how the industry is evolving to embrace data-driven decision-making. He emphasized the necessity of adopting modern tools and technology to streamline what is inherently a complex end-to-end investment process.
David outlined his comprehensive eleven-step approach to investing, covering everything from managing deal flow and due diligence to fundraising and executing successful exits. A key takeaway from his presentation was that data and technology should be leveraged at every stage of the investment cycle. While foundational tools like CB Insights, Preqin, and BizQualify have become industry staples, newer solutions are emerging to enhance efficiency and decision-making. For instance, Otto, a GenAI-powered deal sourcing tool, is revolutionizing how investors identify opportunities. In the tech sector, platforms like G2 and Peerspot provide invaluable hard data, while due diligence tools such as AskWonder offer deeper insights.
Beyond the initial deal process, David highlighted the importance of continuous post-deal monitoring. Vendors like GF Data offer key intelligence on deal valuations, helping investors stay informed and optimize their portfolios. His overarching message was clear: to remain competitive, investors must integrate cutting-edge data solutions into their workflows and move away from outdated, manual processes.
The Fund of the Future: Embracing Technology and Private Equity Data Strategy
Brad Haller of West Monroe opened his session with insights gathered from over 50 client meetings, where firms of all sizes shared their current challenges and future plans for data strategy, large language models (LLMs), and AI agents. A consistent theme emerged: data sourcing remains suboptimal, firms are not building their own LLMs but see promise in tools like Microsoft Co-Pilot, and post-deal monitoring suffers from limited data availability.
For firms looking to evolve into the “fund of the future,” Brad outlined the need for a structured, multi-tiered approach to data and AI adoption. At its core, building a robust data platform is essential to unlocking alpha generation opportunities. West Monroe’s recommendation includes forming an influential working group to champion the initiative, investing in data maturity and proprietary datasets, and securing early wins to demonstrate tangible success.
The key takeaway? Firms that prioritize a strong data foundation today will be best positioned to leverage AI and advanced analytics in the years ahead, turning strategic investments in data into lasting competitive advantages.
Alternative Data and Private Equity – Use Cases and Applications [Private Equity Data Strategy Track]
With Claire McCarthy, G2, Wayne Norris, Dodge Construction Data and Shameel Abdulla, Clootrack.
The session opened with the panelists detailing how they work with PE and VC clients compared to public markets. The major difference here is how data delivery to PE and VC clients can be ad hoc, or project driven, while public market clients are on annual subscriptions. Shameel Abdulla from Clootrack noted that most of the business they see is for due diligence which is driven by one-off project work. Wayne from Dodge Construction said that they see business across sourcing, due diligence and post deal monitoring. They see annual subscription sales as well as project level business. Claire noted that G2 only does annual subscriptions but they also have a credit system in place to allocate costs to various projects.
The panel then elaborated on use case examples for their data. Clootrack highlighted how online media, social media and review data could be used for the analyses of any consumer facing brand but highlighted up and coming athleisure and sneaker brands compared to Nike and Addidas. Wayne from Dodge highlighted how their data could be used to do a deep-dive on data centers built across the US, from green field to build and completion. Other similar industrial scale projects are also another great use case. Claire focused on emerging tech and SaaS companies and also highlighted that G2 has a new B2B spend data offering that offers greater insight into the tech space.
The session closed out with data delivery to end clients. There was a range of options here with raw data, curated CSV and even reports. The panelists also emphasized their collaboration with consultants, who help analyze the data for PE and VC clients looking for high-level insights without taking on the analytical workload themselves.
Value Creation in Private Equity: Talent, Revenue, Operations – with Tom Liu, Managing Partner and Founder of Ideate
Talent: Finding the Right People Before They Even Know They’re the Right People
Identifying top-tier talent has always been a mix of art and science, but AI is increasingly making it more science than art. By systematically knitting together data points—performance metrics, network connections, even competitor reviews — it’s possible to identify not just the best hires but also those who will thrive in a company’s culture.
But does this work for senior hires? Jury’s still out. The higher up the ladder, the more human intuition still plays a role. One thing that is undeniable, however, is that AI can flag key person risk. If someone is about to jump ship, the right data signals can predict it. So, take note: if you’re a high-flyer making subtle LinkedIn updates, someone somewhere is watching.
Revenue: The Holy Grail of PE Management Teams
Sure, talent matters, but if there’s one thing that keeps PE partners up at night, it’s revenue. Boards don’t just want to know who’s running the ship; they want to know where the next wave of growth is coming from.
This is where AI goes beyond just fancy dashboards. Companies like Ideate have cracked the code on identifying the perfect buyers and, just as crucially, the perfect influencers who can help close deals. The magic formula?
• Lead enrichment: No more cold outreach into the abyss—AI finds buyers with a genuine need.
• Mass personalization: Because “Dear Valued Customer” emails belong in 2010.
• Predictive analytics: Knowing which prospects will actually convert (before even they do).
In a world where speed and precision win, these tools help firms not just grow revenue, but do so efficiently — meaning better margins, better returns, and, of course, happier LPs.
The Takeaway
Private equity has always been about optimizing returns, but with AI and data, the game has changed. Finding top talent isn’t just about gut instinct anymore — it’s about deep analytics. Revenue growth isn’t just about sales strategies — it’s about predictive insights and automation. Final piece of advice? Keep an eye on your LinkedIn activity. Big Brother—or at least, Big Data—is watching.
