The Economics of Data Businesses

Adding to the problem is the fact that almost all data products have a ‘minimum viable corpus’ — a size below which the data simply isn't useful. This parallels the concept of a minimum viable product in software, but an MVC is usually much harder to build than an MVP.

The effort required to go from zero-to-one in data businesses is one reason they are so formidably defensible. It's also why ‘brute force’ remains one of the most popular strategies used by players in this game. A data product that can be built easily is a data product that can be replicated easily.

Everything starts slower on the data side. Building a valuable data asset takes time. Building the supporting infrastructure to actually deliver that data takes time. Sales cycles take time...  The classic mistake people make is to see this and jump to the conclusion that early-stage data businesses don't work and will never work. But that's a... See more

Google, Bloomberg, Yelp, and ZoomInfo are all data businesses. They acquire their data in different ways, and they generate revenue from that data in different ways. But for all these companies, data is the fundamental unit of value creation.

Everything starts slower on the data side. Building a valuable data asset takes time. Building the supporting infrastructure to actually deliver that data takes time. Sales cycles take time.

In fact, typically, a successful new data product is not a variation on the existing data; it’s a brand new data asset from a completely different source, exploiting a completely different set of loops.

You should also try to add proprietary value of your own, lest either your suppliers or your customers encroach and disintermediate you. A sufficiently large transformation of your source data is tantamount to creating a new data product of your own.

Successful data businesses are all built around a unique or proprietary data asset. There are a few ways to build such an asset:- Brute force License and transformCore business outputPayment in kindInbound network effectsGive to get Data exhaust

A common failure mode is to build a business on top of somebody else’s data. If you depend on a single upstream source for your data inputs, they can simply raise prices until they capture all of the economics of your product. That’s a losing proposition.