What is data monetization?
Data monetization is the act of measuring the economic benefit of corporate data. The benefits can be in the form of actual dollars, but they can also pave the way to new products, services and even process improvements.
The term data monetization rose in lockstep with trends such as big data, a precursor to the latest wave of artificial intelligence platforms and tools, and the internet of things, a network of sensors embedded into physical objects that helped propel the edge computing architecture. As C-level executives continue to recognize the value of data, and as the world continues to be instrumented with sensors and an expectation for real-time analytics, data will continue to be a booming business.
Data monetization in practice
Experts describe data monetization strategies as being either direct or indirect. Former Gartner analyst Doug Laney, who coined the term infonomics, a portmanteau of economics and information, and author of Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage, described direct data monetization methods as data that's sold or traded. Early examples include Walmart's Retail Link System, a data portal for sellers, and Alibaba's targeted personal finance services. Indirect methods, on the other hand, use data to improve business processes such as identifying waste or improving safety, which companies should strive to measure to show a monetary benefit.
Barbara H. Wixom, principal research scientist at the MIT Sloan Center for Information Systems Research, also differentiates between direct or indirect methods for monetizing data.
In her 2019 research briefing "Building data monetization capabilities that pay off," Wixom listed three data monetization strategies: selling data, wrapping analytics around products and services or improving business processes.
Selling data outright, something retailers have been doing for years with point-of-sale or customer loyalty data, introduces new revenue streams to a company. When wrapping analytics around an offering, companies are introducing new products based on data such as dashboards that provide metrics on customer sentiment or product use. Both are described as direct data monetization methods.
Wixom also highlighted improving business processes as an indirect strategy, which she described in her 2017 article "How to Monetize Your Data" as a perhaps unglamorous but immediate path to data monetization. She pointed to Microsoft's sales team and its push starting in 2014 to makes processes more efficient and decisions more data-driven as an example of an indirect data monetization success.
Data monetization challenges
Along with its potential, data monetization introduces challenges businesses won't be able to ignore. Businesses will need to comply with legal and regulatory constraints when selling or trading data.
They'll also have to consider the tricky area of data privacy, which can attract or deter customers, depending on the company policy.