How to Monetize Your Data—With Examples

So you’re ready to turn your ocean of data into a pile of money. Given British mathematician Clive Humby’s analogy, “Data is the new oil,” it’s a wise business decision to monetize your data. So how does it work? Let’s explore data monetization and the different ways companies monetize their data. Hopefully, it will spark ideas for monetizing data in your business.

What is data monetization?

Data monetization is the process of turning your data into revenue. Data can be monetized in a few ways. It can be internally leveraged to inform business decisions and drive new product features or lines of business. Data can also be sold to other organizations that need the type of data you sell. 

Here are some examples of data monetization among the most significant players: 

• Google: Targeted advertising, using customer data to deliver highly relevant ads to users
• Facebook: Targeted advertising and sponsored content
• Uber: Optimize its driver supply and demand, resulting in more efficient and cost-effective operations
• Amazon: Personalized product recommendations, offering customers relevant products, and driving increased sales
• LinkedIn: Premium subscription services, providing users with access to enhanced features and analytics tools
• Fitbit: Partnering with insurance companies, providing them with access to user data to inform insurance policies and premiums
• IBM: Data analytics and consulting services to other organizations, helping them extract insights from their data
• Mastercard: Offering data to banks and merchants, helping them identify fraud, improve marketing strategies, and optimize operations
• Royal Dutch Shell: Licensing oil and gas exploration data to other companies in the industry, helping them make more informed exploration and drilling decisions
• American Express: Offering it to merchants and business partners, enabling them to analyze customer spending patterns and improve their marketing strategies

Productizing and Monetizing Data

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What kind of data can be monetized?

Data ripe for monetization includes demographic information, historical data, future projections, customer or business contact information, geographical location information, user data, internal metrics, weather patterns, transportation routes, and market research—nearly anything you can measure. 

As you can see in the above examples, data can be used to present value to consumers, partners, brokers, competitors, and more. It’s all about understanding the business problem needing to be solved by whoever buys or uses the data.

Demystifying data monetization

Any data you share must be packaged in a consumable, easy-to-use way. Before monetizing, data must be productized from raw data into a curated product that:

• Solves a specific problem
• Has a precise product market fit
• Is usable and consumable
• Is packaged and marketed effectively

There are two types of data monetization:

• Sharing curated and uncurated data internally (internal data monetization)
• Selling curated and uncurated data externally (external data monetization)

Let’s look at specific use cases of internal and external data monetization and examine real-world data monetization case studies.

Internal data monetization examples

Internal data monetization is when an organization shares its data internally (across the organization and/or across its business partner ecosystem) to improve business intelligence, efficiency, and decision-making. And a lot of valuable information is hiding in your user data.

Here are a few data monetization use cases and examples that enable internal teams to make data-driven improvements.

Monetize data analytics for business optimization

When considering monetizing data insights, don’t forget that internal optimization can be a money maker—or, a money saver. 

Data analytics can identify areas of inefficiency or underperformance in your business. Analyzing KPIs such as revenue, cost, and customer satisfaction can reveal areas to improve and change operations. Using these insights, teams can assess where processes might improve, leading to cost savings, increased efficiency, and improved customer satisfaction.

Enhance the customer experience

Customer data can provide a deep understanding into customers’ needs, preferences, and experiences. For example, Starbucks harnesses the data from its loyalty card program and app to assess customer behavior and predict purchases. By sending individualized offers to customers, they can increase sales, suggest new products, and re-engage customers who haven’t been by in a while. 

Their in-app games and stars program also keeps customers engaged and gameifies their coffee run, which makes Starbucks more than just a coffee—it’s an experience.

Improve your product and engagement

Any online product will yield significant information about popular features, usage patterns, and user information. By harnessing that data, teams can identify and improve aspects of the product that would return the highest ROI. 

For example, teams at Apple assess how people use apps in real life and update designs and user experience to better fit with customer behavior.  Their iTunes software allowed them to capture huge swaths of data, including data from retailer points of sale. Apple used this data to tailor products that resonated with their audience and made products that worked better, and consumers enjoyed using.

Enhance SLAs and QoSs

Service level agreements (SLAs) are agreements between a service provider and a customer that define the level of service a customer can expect. Quality of Service (QoS) documentation outlines customer service benchmarks. By analyzing these documents, your business can identify areas where they may not meet customer expectations. This might include KPIs like service availability or response times. Identifying areas for improvement allows your business to improve performance and ensure it meets customer expectations.

For example, Uber uses internal data sharing to optimize its driver supply and demand, resulting in efficient, cost-effective operations and the right balance of driver availability for its customers.

Manage and optimize your supply chain

Analyzing supply chain metrics like inventory and logistics can help increase company efficiency. Many retailers have recently struggled with supply chain issues such as shipping delays, rising costs, and out-of-stocks or low on-shelf availability. Large retailers leverage their internal data and monetize customer data by sharing it with their partners. For example, Dollar General has leveraged supply chain data to adopt sorting-process and case-pack optimization. These processes make stocking more efficient and approve on-shelf availability. 

Bolster employee satisfaction and productivity

By analyzing employee retention, demographics, and surveys, HR and business teams can assess the employee experience to make data-driven decisions on staffing and other business management issues. Companies are now using employee listening tools to understand employee satisfaction, gain insight into what employees value, and help boost productivity. 

IBM uses internal data sharing to optimize its employee retention and talent management programs. The program provides managers with data-driven insights into employee performance and engagement. Similarly, Salesforce provides employees with data insights into their work patterns and identifies areas where employees can optimize their workflow.

Use data sources to address business challenges

Just as data analytics can identify internal optimization opportunities, it can also identify new business opportunities and challenges. Analyzing industry trends, competitor performance, and other factors might yield market insights to inform business strategy. These data insights can also identify new product or service offerings, markets, or business models, all of which open the business to new revenue streams. Tesla uses data from its vehicles’ sensors and software to identify potential safety issues with the car and autonomous driving. Consistent data collection and analysis allows Tesla to continually improve its products and services and address issues as they arise.

Improve your data strategy and collection

It might sound meta, but data analytics today can help improve your data tomorrow. Through efforts to analyze customer behavior and preferences, your organization can identify the most valuable data to collect and devise strategies to collect more of that data. Such insights can also help your organization target its marketing and sales efforts more effectively to increase sales and customer engagement. For example, NASA harnesses data from its spacecraft and satellites to analyze weather patterns and climate change. This data helps them improve weather forecasting and develop new technologies that help them improve their environmental predictions.

Optimize energy efficiency

Organizations can monetize energy data to save on energy costs and reduce their carbon footprint. Data can pinpoint areas for improvement and help you implement energy-saving practices that will impact your bottom line—and probably make you feel better about what you pay your energy company every month.

This can also help you optimize your network performance and improve your service quality. By identifying peak data usage patterns, you can more efficiently plan for future capacity and upgrade equipment to better fit usage habits. Walmart is an excellent example, as they use internal data sharing to optimize energy efficiency. Data from its stores helps identify areas where energy usage may be excessive. Walmart will implement targeted improvements to reduce that energy consumption.

External data monetization examples

External data monetization means selling or sharing your data with other businesses or organizations. Here are some common ways and examples you can monetize data sets.

Monetize user data and share it with other organizations

Organizations can share their data assets with partners, affiliates, or other businesses. The data provides valuable insights and access to new market opportunities. For example, Dollar General announced in 2022 that it would use its retail media network DGMN to provide audience insights and closed-loop reporting for its brand partners. They state this will better serve rural communities in the US and help partners develop better, data-driven advertising campaigns. It is also an excellent example of user data monetization.

Sell insights to third parties

Businesses looking to drive product development, marketing, or sales strategy might purchase data from data marketplaces to help them identify new opportunities. By providing data to third parties, your organization can monetize its data products and can offer insights as a standalone service or as part of a larger consulting package. This is especially prevalent with social media companies and search engines. Google is a prime example; it collects and sells data on user behavior to advertisers and third parties. The data includes user search queries, browsing history, and location data, which are valuable for targeted advertising.

Build data analytics subscriptions

Businesses are hungry for data, and many are willing to pay a subscription to access data and analytics tools. Nielsen is a fantastic example. They track media ratings, consumer buying behavior, and brand preferences. They then sell these insights to their clients like Coca-Cola or Disney so they can target their promotion budgets and optimize products. Another example is Bloomberg, which offers financial data and analytics through its Bloomberg Terminal subscription service, which finance professionals worldwide use for insights.

Turn that data ocean into a money pile

Data monetization is a powerful strategy that allows companies to turn their data sets into money. Whether that’s a competitive advantage, more efficient internal processes, or an entirely new revenue stream, data monetization tools can bolster your bottom line in myriad ways. There are so many data monetization strategies that the only limit might be your imagination. 

Ready to monetize your data? Whether you’re looking to create data products, share insights with other organizations, or improve business performance, Revelate can help. Contact us today to schedule a demo.

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