DaaS Series: Getting Started
A series on thinking about, creating, and monetizing data assets within larger organizations
Piece 1 in an attempt to craft a playbook for how established companies can think about commercializing their data assets.
There’s a lot that’s been written on lessons for data startups and the modern, evolving data ecosystem. This series explores a specific niche: how can “non-data” companies (SaaS, marketplaces, etc) build out commercializable data businesses alongside their core offerings.
I’m starting this series after spending most of the last 3 years thinking through a pretty fascinating problem (to me at least): how can a SaaS company make money off its data assets? Like any great problem, this one has been a massive, tangled ball of yarn. What seemed easy at first — umm, just sell the underlying data?- has led to countless hours of discovery, considerations, reconsiderations, experiments, failures, and successes. Along the way I’ve pieced things together from established thought leadership (s/o World of DaaS podcast), cutting edge partners, and a lot of trial and error. And now that I’m eyeballs deep in it all, I figured it was time to start writing things down to a) help me make heads and tails of it all and b) maybe help others starting their journey do the same.
A quick disclaimer before we get started: unless otherwise cited, everything in here is my own thinking, my own opinions, and does not directly reflect the policies/opinions of any other organizations.
Part 0: What are we even talking about here?
First things first, let’s set some groundwork on what we’re NOT talking about here:
- There is a tremendous amount of literature that already exists on leveraging data in business decision making. This series is not intended to explore those depths.
- There is also a tremendous amount written, said, and invested around the world of SaaS and the values, benefits, best practices involved in running and distributed hosted software. I wouldn’t begin to suggest any level of expertise there, but I will leverage the world of SaaS as a comparison point.
And, one more detour, some definitions:
- DaaS — “Data as a Service”- refers here to the business of licensing data assets to external parties through a number of mechanisms that we’ll get into ranging from direct data feeds to APIs.
- Data Products — this will get a little muddy but I’ll try to make the distinction clear between internal data products (e.g. a data table on platform usage by client used by Customer Success) and external data products
- Data Assets — an owned set of facts, figures, or other knowledge points created/harvested and maintained by an organization that is has the rights a) use internally and/or b) distribute to 3rd parties.
Now onto this series:
Within the world of DaaS, there are a number of companies that are created and designed for the sole purpose of finding/creating data assets and then directly monetizing those data assets.
However, there are also a lot more companies who are sitting on data assets, either as inputs to their primary systems or even derivative works, who should be thinking about these assets as new revenue streams. Just as Reddit, Twitter, and most news sites are waking up to the fact that GenAI Companies been freely harvesting their valuable content for the last 4 years, so too should many companies be looking at what they’re sitting on and asking the fundamental question:
Do I have a proprietary, valuable data asset that I could be monetizing alongside my SaaS offering / marketplace / [insert XYZ other product]?
This series will explore that question — leaning on how I’ve thought about the problem within a SaaS business built on the foundations of an extremely rich data asset.
Series Contents