Over the last 3 months, there has been a common set of questions about the design of the underlying business model for a data platform. If you have a data set that you think is valuable, how should you “sell” it?
- Data as a product.
This is the simplest model and in essence you sell all or part of that data for a defined value. This is a one off payment as for a product and the purchaser has unrestricted use of that data. This is typically useful for static data e..g clinical trials, survey results, insights from analytics.
- Subscription model
The purchaser is able to access defined portions of the data, through an API. Restrictions are often applied on quality of data, frequency of access, usage etc.
- Analysis or Model as a Service
Here the data provider will create a model where the purchaser is able to add their own data to create unique insights. As an example, retail sales data gathers for areas of a city can be provided as a model to allow real estate companies assess the value of developing a shopping mall at a particular location.
- Insight as a Service
Consultants or experts are made available by the data platform provider to provide insights or answers to specific questions required by the purchaser. This is essentially a consulting service, where the consultants are data scientists that have access to unique data stores and analysis tools. Benchmarking services are a good example here.
These seem to be the four generic models I have come across so far. What other models have you come across?