MBA Mondays: Revenue Models – Data
The Internet is a data generating machine. According to Eric Schmidt, every two days now we create as much information as we did from the dawn of civilization up until 2003. It's also incredibly good at presenting that data, both to humans and machines.
So it makes sense that collecting and publishing data is one of the primary business models on the Internet. Here are some of the examples that you all created on the revenue model hackpad:
I like to think of data businesses in two categories; businesses that aggregate and then publish data and businesses that generate their own proprietary data by virtue of the service they provide on the internet.
Most of the companies listed in the data section of the revenue model hackpad are businesses that aggregate data from others and sell it. These can be good businesses but they are rarely great businesses.
Google is an example of a business that generates its own proprietary data by virtue of the service they provide. Google doesn't monetize with a data revenue model, they monetize with advertising that is targeted based on the data they generate. But in many ways, Google is a data business. Data is the secret sauce of their business and they have invested heavily in data science to maximize the value of their data.
Facebook and Twitter are rapidly becoming data businesses like Google. They collect a ton of data about users and what they think about and care about by virtue of providing a free and valuable service on the Internet. And that allows them to improve their services, make them smarter, and to target advertising to their users.
Going back to the aggregation model, if you are going to pursue this approach, try to figure out how to make your data as proprietary as possible. Anyone can aggregate so you run the risk of commodification in the aggregation game. If you can create some sort of proprietary advantage, either through exclusive access to the data or through some sort of refinement of the data using your own insights and analytics, that leads to a better aggregation type business.
Most data businesses are subscription based, but data can also be sold on a transactional basis. Transactional models are easy to sell when you are just getting going, but subscription models work better over the long run.
Many data businesses use APIs to make it easy for their customers to get data into their own systems. This is a good idea because it makes it harder for customers to leave if your data is part of their systems. If you can make your data part of a broad ecosystem, that is a good thing.
Selling data is a good way to build a business on the Internet but if you can figure out how to leverage proprietary data produced by your service to make your service even better, that often turns out to be an even better "data business".