Demystifying Data Monetization

Companies have figured out that data can be used in day-to-day operations to reduce costs and grow revenue.

Reading Time: 9 min 


Every company operating today is a data company. Most have access to an array of data on their supply chains, operations, strategic partners, customers, and competitors. Yet most companies are leaving money on the table, with only one in 12 monetizing data to its fullest extent. Data on its own has value, but insights derived from data substantially increase that value. These insights can be used to direct activities as varied as customer segmentation, demand and churn prediction, pricing optimization, retention marketing, and cost management — and they can also command even greater margins when sold externally.

There are two primary paths to data monetization. The first is internal and focuses on leveraging data to improve a company’s operations, productivity, and products and services, and also enable ongoing, personalized dialogs with customers. The second path is external and involves creating new revenue streams by making data available to customers and partners.

These paths are not mutually exclusive, and some companies accomplish both, as is the case with telecommunications companies such as Verizon, Deutsche Telekom, and Telefónica. They’ve achieved internal monetization by using data to optimize operations and client services, and they also leveraged that data, anonymized and aggregated, across various use cases for their B2B clients and partners by offering:

  • Geotargeting and geofencing for retailers and tourism.
  • Traffic flow and density planning for ad agencies, government agencies, public transportation companies, city planners, and health care organizations.
  • Fraud detection for financial institutions and credit card companies.
  • Smart targeting and click-stream insights for brands and digital advertisers.
  • Location, layout, and staff planning for retail stores.
  • Internet of things (IoT) applications for a variety of companies.

Successful data monetization requires a careful approach that focuses on the highest-value opportunities that are consistent with a company’s overall business strategy.

Preparing for Data Monetization

John Deere is one company that has created a new source of revenue for itself and value for its farmer customers through data. They did this through a partnership with Cornell University, using Ag-Analytics, Cornell’s data platform that syncs with John Deere’s operation center to access and analyze farm data. Farmers can access analytics tools such as estimators for crop insurance and forecasts for yield and risk management. The platform integrates public data sources, including soil type and weather.



The authors would like to acknowledge and thank Eric Stettler, Chris Hagen, and Sally Quan for their valuable contributions.

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