A Deep Dive: The Data as a Service Business Model
How to build, scale, and monetize vertical data companies
DaaS (Data as a Service) isn’t just SaaS with a CSV upload. It’s the marriage of deep domain expertise, obsessive data hygiene, and tech-savvy packaging.
We’re pulling back the curtain on what it really takes to build and scale a vertical data business.
🔓 What’s inside this post (8-part breakdown):
📦 DaaS ≠ SaaS
Why Data-as-a-Service isn’t just software with a CSV upload—and how the monetization model flips when you sell answers, not features.
🛠 The Challenges of Starting a DaaS Business
Why it’s brutally hard to get off the ground, even with AI—and how Masterworks, FINTRX, and others built proprietary datasets from scratch.
🔭 Going Broad vs. Narrow
ZoomInfo vs. FINTRX: The tradeoff between horizontal reach and vertical depth—and why obsession always wins.
🔄 Building into Workflows
How DaaS companies become mission-critical by showing up in CRMs, slide decks, Slack alerts, and GTM plans.
🧬 Rolling Your Own Data
Why licensing other people’s data kills your margins—and how control over freshness, structure, and provenance becomes your moat.
🎯 Figuring Out Your Ideal Customer Profile
Segmentation beyond logos: how to sell by job-to-be-done, not just title or industry.
👥 Hiring for a DaaS Model
Why data businesses need product-minded analysts, ambiguity-tolerant engineers, and sellers who speak the customer's language.
🧾 Summary + Key Takeaways
The full cheat sheet: how to build, defend, and scale a vertical DaaS company from first row to last click.
Yeessh!..This clocks in at the longest piece I’ve ever written. My fingers hurt.
👉 Read on for the full breakdown (paid subscribers only)