Matt Ober is a general partner at Social Leverage. Matt was most recently the Chief Data Scientist at Third Point, where he built the data analytics and technology platform used to enhance the firm’s investment capabilities in equity, structured credit, venture capital, and cryptocurrency. Prior to joining Third Point, Matt was the Head of Data Strategy at WorldQuant and part of the WorldQuant Ventures founding team, focused on private investments in fintech, data, and technology companies.

In the data & information services space, it seems like the key to success is acquisitions. You have to find your wedge, your revenue, your product-market fit, but once you find it, you have to start acquiring, or “rolling up.” If you are in a position of strength, you need to use it. That is if you want to build a big business.

This is my opinion, but I have seen very few—if any—companies get to scale with the potential for billion-dollar exits or IPOs without acquiring. Tegus acquired Canalyst and BamSec and they are well on their way to building a big business.

Alphasense acquired Sentieo and Mosaic. IHS acquired a ton of companies before they were acquired by Markit, which was then acquired by S&P Global. There are other companies (like Exchange Data International) that have been the data vendor for data vendors for many years, and have quietly been acquiring small data and information services companies.

Even in the crypto data space, we have seen the strong team at Amberdata making acquisitions, such as Genesis Volatility.

Pitchbook, which arguably leads in private market data, was acquired by Morningstar. Granted the public companies can acquire easily, but this is just a good example of them taking advantage of their strength and seeing opportunity.

PE has looked at and dabbled in the data world, but we are still early. We saw MackeyRMS acquired by PE, which then bought Insider Score before rebranding to Verity. The RMS (Research Management Systems) opportunity and value, I think is pretty interesting in this AI-focused world. They arguably have the best access at integrating AI and making it available to hedge funds and the buy side. They are already trusted with the most secretive of information- models, notes, research, etc. What better way to train AI and integrate than building on top of an RMS?

Overall acquisitions, in my mind, are how you get scale velocity in the data & information services space. Growing organically, having a core product, and the right team are all necessary, but without having that acquisition muscle, I find it hard to believe that many companies can make it to the public markets or the unicorn status.

If we are going to see a Factset, S&P, Verisk, Morningstar-type competitor in the public markets in the next 10 years, then we are going to need to see a team that can execute on acquiring a lot of these smaller data and product companies. There are endless opportunities to do this right now and I look forward to seeing this play out in the coming years.