I’m a builder turned backer. I spent the first half of my career building and growing products that help companies use data to engage with their customers. Over the last 25 years, I’ve helped grow 5 startups and 4 industry leaders focused on that goal, most recently as Chief Product Officer for the $9B Service Cloud at Salesforce. Now I’m joining DYDX to back entrepreneurs solving hard problems with data. Why? Because I’ve seen the emerging opportunity of the Data Supercycle first hand.
I joined my first startup after 3 years as an analyst for McKinsey & Company. We delivered predictive analytics software to retailers, including Disney, the Body Shop, and Walmart. I saw even these very sophisticated retailers make decisions about pricing and inventory using merchandiser instinct instead of cold, hard data.
Why not make data-based decisions? I’ve heard the same answers to this question throughout my career: Data is complex and messy, especially for retailers where sales and inventory vary by SKU by store by day. Data is difficult to process, requiring specialized tools and techniques. And data can actually be misleading until put into context– for retailers this means difficult corrections for seasonality and out-of-stocks.
When we solved those problems, the impact on retailers was incredible. Over my career, so was using data from your files to improve project collaboration. So was using data in your email to improve customer engagement. So was using data latent on the public web to improve prospecting. I led product or marketing teams at 5 different startups using data to solve these problems, including a Salesforce Ventures-backed startup of my own. Those startups exited to Wipro, Citrix, and Demandbase– there was real power in using data to solve problems for the enterprise.
But nothing prepared me for what I saw when I finally joined Salesforce in 2021, after orbiting in the ecosystem since my first Dreamforce in 2005. As Chief Product Officer for Salesforce Service Cloud, I was entrusted with the roadmap for the system of record for some of a company’s most precious data– conversations with customers when things weren’t going so well. But solving problems using that data was easier said than done.
This became clear as we led enterprises into the era of Agentic AI over the course of 2023-2024. I met with company after company at the top of Salesforce Tower in San Francisco. Even when Karl obscured the view, it was always crystal clear that AI Agents needed to be grounded on enterprise-specific data in order to be trusted to take action. But customer data was fragmented. Knowledge was inconsistent. Workflow data wasn’t structured. Roles and permissions weren’t documented. The metadata describing how different systems worked together wasn’t captured.
I knew that each one of these barriers represented a billion dollar startup opportunity. I thought to myself: If only I knew someone running a fund investing in startups focused on these problems!
It ends up that I did– one of my oldest friends. Spencer Maughan and I were in high school together, where we talked each other into joining the swim team, mostly because there were no try-outs to test our scrawny frames. Years later we reconnected at the Stanford GSB, and I’d been cheering Spencer on through his incredible career in venture ever since.
We realized we needed to work together when Spencer observed that his best investments were always fundamentally entrepreneurs doing incredible things with data. That’s exactly how I’d come to describe my best products… and the products that I now see the enterprise software market desperately needing.
I’m passionate about DYDX Capital’s focus on the data supercycle, and know the impact on the enterprise will be profound. This is a generational opportunity to back exceptional people using data to solve problems for the world’s organizations, and improve the human condition while we’re at it. If that’s you, let’s talk!