Data monetization is quite simply turning your data into money. Your business collects a lot of data every day and you are gathering all these data to ensure that you stay competitive and relevant as a business.
The opportunities you find in big data are limitless. It has been used to improve marketing and sales performance, as well as to get business intelligence and get to know your customers. Big data, when properly analyzed, can also help you discover new product lines and get more revenues. But what do you do with all that data after getting all of these insights? Do you just let it all rot in storage and wait for a time when you would need it?
You do not have to. You can monetize data by:
- Identifying the available data sources that you have. This includes the information that you already have and ready for monetization, plus other data sources that would make your current data even more valuable.
- Converting the data into revenue generating insights, products or services.
- Pricing the data-based product, as well as specifying how the data is to be vetted, stored and accessed.
- Analytics and research. Transforming your data into insights that help you reduce risk, focus on improving customer experience, or develop new or better products.
- Leveraging your data. Aside from coming up with a data-based product, you can also come up with alternative products and services, such as real-time notifications.
There are three main types that you will need to become familiar with when dealing with data monetization: contributory databases, data processing platforms and data creation platforms.
Contributory databases collect customer data that the customer voluntarily provides in exchange for a service or information. This helps you get a robust set of customer data that makes it a very valuable data source and asset. For instance, Markit has a credit index business that surveys dealers for the prices of fixed income instruments. They then aggregate this data and index it, so that it could be used along with established indices that are used in the industry.
Data processing platforms, on the other hand, make use of complicated data architectures, complex algorithms that are most likely proprietary, and analytics. These types of businesses allow users to consume data in any way they want, easily and quickly. Bloomberg, for one, gets data from different sources then integrates all of these data into one stream. Bloomberg users can make use of an API or a dashboard to get analytics for whatever purpose they might need.
Data creation platforms collect a large volume of data from customers allowing them to customize the products, services and features that they offer their customers. These data assets are so valuable that companies seek it out.
For quite some time, big data has been touted as a way to help you understand your market, your products, your customers and your operations so that you could make better decisions that help you grow your business and make it even more competitive and profitable. When you have a large set of data, you can turn it into a new business or launch it as a new product. Four Cornerstone can help you monetize your data. Call us today!
Photo by Gerd Leonhard.