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The Economics of Data Businesses

When you think of tech, you would think of SaaS, marketplaces, e-commerce, social media etc. Most of these business models have been studied extensively but not data businesses. 

Abraham Thomas wrote a great piece on the ins and outs of data businesses. Let's dig in!

What is a data business?

• A company is a data business if, and only if, data is its core product
• Data is central to the activity of the company; without the data, there is no company
• Google and Bloomberg are all data businesses. They acquire their data in different ways and generate revenue from that data in different ways

It's all about the data 

• Succesful data businesses are all built around a unique or proprietary data asset
• There are a few ways to build it: brute force, aggregate and harmonize, license and transform, affiliate collection, core business output, payment in kind, inbound network effects, give to get etc.
• For example, Google uses brute force to build their data asset. They allocate resources for the task of data collection and crawl every website on the internet

The Economics 

• Data businesses have slow beginnings. Building a valuable data asset and infrastructure takes time
• They start slow but accelerate over time
• A data business has an accelerated route through the middle of the S-curve. Over time, the cost of acquiring data begins to decline, sales cycle begins to shorten
• You can now offer your data for more effective targeting and as your data becomes widely used, it goes from optional to essential
• You can start to charge more and unlock new channels of data acquisition
• After all of these scale and network effects combine such that you become the lowest-cost acquirer of your data inputs while still offering your data outputs at the lowest price, you'll become unstoppable
• Data businesses are also super sticky. In order for customers to switch, you need to either offer a dramatically lower price or dramatically higher quality 
• The economics of data acquisition makes it hard to offer cheaper prices and increasing speed or accuracy doesn't really increase the utility of the data so it's hard to envision what an improved version can do that is 10x better than the existing data product

Successful data businesses are rare because valuable data is rare. There's a lot of data in the world, but most of it is junk.

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Before you go...

• Check out issue #63 where we talked about the economics of buy now pay later (BNPL) 💳
  
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