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TDWI Upside - Where Data Means Business

Data Monetization: A New Way of Thinking

Re-engineering your business around analytics -- that is the true meaning of data monetization.

Data is a byproduct of doing business but it is not the business alone. It is used to monitor and enhance the business. Today, many organizations -- even those not using big data -- generate more data than they can actually process.

Let us understand what data monetization actually is: making a positive and measurable impact on business revenue by using data effectively. This definition provides you with many possibilities beyond the traditional idea of selling your data to third parties.

For Further Reading:

Monetizing the Digital Consumer Through Data

5 Steps to Monetize Your Data

Data Digest: Business Models and Advice for Monetizing Data, Designing Dashboards

There are two ways you can make money from your data. You can create a supplemental revenue stream by providing access to your data (direct monetization) or use insights to improve your business services and operations (indirect monetization).

Data monetization is not simply about turning over your existing data to another party. There are many other ways to utilize data that can impact costs or revenue. These wider opportunities are often missed, so you need to think in new ways to identify them. We'll explain both direct and indirect monetization here.

Direct Data Monetization

Direct monetization refers to more than selling your raw data. Here, "direct" refers to "converts to revenue directly." You can sell raw data if you have a large amount of it and if you are willing to deal with the complexities of data privacy policies and red tape. You must understand the legal requirements and policies encompassing the sale and exchange of data for every country in which you monetize your data directly. Data privacy is a hot topic and a privacy breach could ruin your reputation.

Many companies will pay large amounts of money for big data, but keep in mind that you need not sell all your data. You can provide other businesses with access to select data segments or just your analytics insights.

For example, a food supplier doesn't need the names and email addresses of your restaurant chain's customers. Instead, they need to know how much of which ingredients you're using in order to make accurate production forecasts and keep their supply chain running smoothly.

The advantage of monetizing data directly is that you can create a completely new revenue stream. Once you've decided what data to sell and who your target market is, you must choose your "how" -- delivery options. Here are several possibilities for direct data monetization.

Create an API or several APIs: Consider developing an application that enables your customers to access data themselves through an internal API, or develop external APIs that enable third party software to interact with your data (where you control what data is exposed). Consider examples such as Google Maps, Twilio, and social media sharing available outside of social media platforms.

Selling your data: If you have big data, you can license your data for use by other businesses, or you can sell it via brokers. This could be presegmented or raw data.

Selling your analysis: Data that is already analyzed is more helpful than raw data. You can sell the analyses to businesses that value your insights, especially if you have the resources to analyze data and they do not. This could include report subscriptions.

Barter or trade your data: Utilize your data to obtain benefits for your clients, customers, or business. In return for performance benchmarking against your competition, you could provide your data, or you could barter for favorable terms or free services for your customers in return for select data insights.

Indirect Data Monetization

Selling data directly isn't your only option. In fact, in many cases, it may not be a good option at all. Suppose you are a manufacturer and you know who bought your umbrellas last year. You will not sell that data; it's too valuable.

Instead, take that data and use it to sell more umbrellas -- that is, monetize your data indirectly. Your data gives you the opportunity to address individuals and say, "You bought this product last year. Here is why you must buy a different umbrella this year." You are using your data to identify new customer needs and create new revenue opportunities.

Indirect data monetization requires you to think about data as a strategic asset in new ways. You can use data to understand your customers and suppliers better, for example. You need to change your view of analytics; see it as a profit center, not a cost center. Analytics becomes something you invest in because of the benefits it can bring.

Indirect monetization incorporates all the ways you can impact your bottom line without the data leaving your organization. You unleash insights about your clients, customers, and partners and make changes that create a measurable impact (you are not monetizing your data if you cannot measure the impact of your actions).

Here are other ways you can indirectly monetize your data.

Discover new business categories or customer types: What other customers (those currently not buying your product or service) could benefit from what you offer?

Develop new services, products, or markets: Locate gaps in the market; look for customer problems that haven't been addressed to back the launch of a new service or product or branch out into a new market.

Enhance your service or product: Discover the secondary problems of your customers and solve them by enhancing your service or product; this can include adjusting the price or offering "similar product" recommendations on your website.

Reduce costs: Analyze your data to see where you can save money by streamlining operations such as upgrading cost-heavy business tools or reducing stock.

Improve efficiencies and productivity: Monitor how productive and efficient processes, operations, and employees are, then optimize your resource allocations.

About the Author

Savaram Ravindra is a content contributor at and He is also an author at His previous professional experience includes programmer analyst at Cognizant Technology Solutions. He holds a masters degree in nanotechnology from VIT University. He can be contacted at [email protected], LinkedIn, or Twitter.

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