July 28, 2022

Data Monetization Examples And Strategies


Data monetization emerged as a business strategy in response to the surge in data generated in our day-to-day lives.

According to Statista, the global population is estimated to create and capture 147 zettabytes of data in the year 2024. That's a 71.5x increase versus the total amount of data created in 2010. And as we've produced more and more data over the years, businesses have found that all of that information can be incredibly valuable.

It just comes down to how you use it.

In this blog post, we'll introduce the concept of data monetization and dive into some examples and tactics you can implement to build your data strategy.

What is Data Monetization?

Data monetization encompasses a range of techniques and approaches through which data is turned into economic value — everything from using analytics tools to optimize existing revenue streams to packaging data as a product to open up new revenue streams.

Data monetization business models generally fall under two types: direct or external (you sell data or insights to other entities) and indirect or internal (you use the data insights to improve your own efficiency/profits).

Direct Data Monetization Strategies

Direct or external data monetization is the most obvious approach where you directly sell your existing data or insights to other entities or individuals.

Direct Data Monetization Examples

Here are three examples of ways that companies are engaging in direct data monetization.

1. Consumer Data Sales by Retailers

Major retailers like Walmart and Tesco collect extensive consumer data through their loyalty programs. This data includes purchase histories, product preferences and shopping habits. Retailers can monetize this data by selling it to suppliers or manufacturers who seek to understand consumer trends, optimize their product offerings or target their marketing efforts more effectively.

2. Financial Data Insights by Credit Card Companies

Companies like American Express and Visa accumulate vast amounts of financial transaction data. They analyze and package these insights to sell to businesses in various sectors. These insights can include spending patterns, consumer credit behavior and market trends. This is valuable for retailers, financial institutions and marketing agencies.

3. Telematics Data from Automotive Companies

Automakers like Tesla and BMW, equipped with connected car technologies, collect telematics data. This data includes vehicle performance, driving patterns and maintenance needs. They can monetize this data by selling it to insurance companies for personalized insurance pricing, to urban planners for traffic management, or to third-party service providers for tailored automotive services.

Benefits and Drawbacks of Direct Data Monetization

Beyond the obvious benefit of opening up a new revenue stream from existing data, direct data monetization also opens up opportunities for customer acquisition and partnerships, especially in data-driven B2B sectors.

On the flipside, direct data monetization has several drawbacks:

  • Privacy/legal issues
  • Decision-makers are often not super technical (misunderstood value proposition)
  • Businesses need to be aware this type of data can help them
  • And they also need to be sure your data is of high quality
  • But they can only be sure of the quality after they see/analyze the data
  • Essentially you have a chicken-and-egg problem

And in general, it is better to sell data insights than raw data. Because it significantly reduces the chance for your competitors to get your data relatively cheaply and potentially exploit it to become more competitive. And they can do that using indirect data monetization.

Maybe you earned a little extra in the short term, but this data "leak" weakens your overall market position. In plain English, you won the battle, but you're losing the war.

Indirect Data Monetization Strategies

Indirect or internal data monetization focuses on turning available data into insights and then using those insights to improve a company's performance. It requires creativity and business thinking, but the payoff can be immense.

Whatever business you're in, you generate a lot of usable data, from big corporations to single-person operations. Even if you're just a small blogger, you can still use a small amount of data to make substantial improvements.

Examples of Indirect Data Monetization

1. Amazon's Personalized Recommendations

Amazon uses customer data to power its recommendation engine, which suggests products based on previous purchases, search history and browsing behavior. This strategy enhances customer experience and engagement, leading to increased sales and customer loyalty. By leveraging data analytics, Amazon optimizes its inventory and marketing strategies, indirectly monetizing its vast data reservoirs.

2. Netflix's Content Strategy

Netflix employs data analytics to understand viewer preferences and viewing patterns. This insight guides their content creation and acquisition strategies. By producing and acquiring content that aligns closely with user preferences, Netflix enhances user engagement and retention, indirectly driving subscription revenue.

3. Starbucks' Location Strategy

Starbucks uses geographic and demographic data to inform its store location decisions. Analyzing data on customer density, traffic patterns and local demographics helps Starbucks identify optimal locations for new stores, leading to increased foot traffic and sales. This strategic use of data to improve physical store placement indirectly monetizes their extensive data collection efforts.

Benefits of Indirect Data Monetization

It's possible for even the smallest businesses to get involved in internal data monetization. If you run a blog and you know what your most viewed pages are, you can invest a relatively small amount of effort to improve the content on those pages. Usually, a small number of pages will have the bulk of the entire site's traffic. And this is a great way to efficiently improve your website.

Another approach is to use data to identify which blog posts are on page two of search results. Improving those pages could mean moving to page one on search results. And that is a huge difference.

But in all these cases, you can see that data can help you identify critical points in your business. And once identified, you can do a very small set of targeted changes that have a significant overall effect. Also, there is no downside to leveraging your data this way, so give it a try.

What's the Difference Between Internally and Externally Generated Data?

In addition to direct and indirect data monetization, we can also split the data itself based on its origin:

  • Internally generated is data you collected yourself or gathered from your users.
  • Externally generated is data purchased from other entities or open data that is publicly available.

Internal Data Monetization

Internal data is everything your business, website, or project generates during its regular operation:

  • Usage data (which pages are used the most and what products are most sought after)‍
  • User data (which customers buy the most)‍
  • Performance data (which web pages get the most traffic and which convert the most)‍
  • Employee data (for example, in sales teams: which employee made the most sales)

This data can be shared with internal and external stakeholders to help them do their jobs more effectively via direct and indirect data monetization strategies.

There is a whole host of internal data monetization tools available to businesses looking to leverage the data that they create, from BI tools like Tableau and Google Analytics to sophisticated AI frameworks like TensorFlow and Azure Machine Learning.

It can be easy to be dazzled by your toolset, so always remember to make sure that when dealing with data and statistics, you apply common sense and do not follow the numbers blindly.

External Data Monetization Examples

External data is any data that is not directly generated by your business. But you identified it as useful and acquired it through other APIs or by getting publicly available data on sites like data.gov.

Externally generated data is the key to your company's growth because limiting yourself only to your own data is… limiting. And companies that use the full potential of the data are the ones that are going to win.

1. Experian and Credit Information

Perhaps the most classic example of external data monetization is Experian, a global leader in consumer and business credit reporting. Experian collects and analyzes credit-related data from numerous sources. They monetize this data by providing credit scores, detailed credit reports and risk analysis tools to banks, lenders and other financial institutions. This service aids these institutions in making informed lending decisions.

2. Retailer Data Analysis

Dunnhumby, a customer data science company, partners with retailers to analyze customer data. They specialize in interpreting complex data from loyalty programs and shopping transactions to understand consumer behavior. Dunnhumby then monetizes this data by providing insights to consumer goods companies for targeted marketing and product development.

How Do I Get Started With My Data Strategy?

Do you have any data? Even if you don't, you can still benefit from data monetization. And here are some detailed instructions on how to do it.

If you have the data, the best way is to provide it in a simple, accessible way through an API. However, if you don't know where to start and who would be your customer, check out an article about API business ideas.

If you don't have the data, you can still monetize it. How? By processing publicly available data and making it more valuable. To learn more, read this article on how to monetize open data sets.

If you have an API that provides useful data, how do you monetize it? If you go through a list of popular pricing models, you might find the one best suited for your business (and your customers). Find out more in this article about API monetization strategy.

If you don't have an API, you can build one today without ever leaving this browser. Imagine just defining your data model through a simple UI interface, and all the necessary API endpoints are automatically created for you. That is the power of low-code technology.

Benefits Of Monetizing Data

The direct monetary benefit is the first one that comes to mind. Everyone understands this one because more revenue is always better.

Getting more clients is one benefit that is rarely discussed. If you have a data API, even if it's completely free to use, it gets you exposure. If this data is something your ideal clients need, it will be easier for them to find you.

This makes your business recognizable. If you provide a reliable API service, your customers trust you more. And since you do it all for free, they also like you. And these are three main ingredients for every transaction - people do business with people who they know, like, and trust.

Attracting new talent by exposing your business to potential employees. This is especially important in highly-skilled professions like software development. Because it's never easy to find good people. So why not make it easy for yourself and allow them to find you?

Gaining a competitive advantage is yet another benefit that rarely comes to mind. By providing filtered and structured data to others, your business will inevitably go through large amounts of data.

Not everything is going to end up in your API because not every data analysis ends up finding something useful. However, sometimes you'll come across some absolute golden nuggets of insight. This strategic information might be too valuable to be released publicly, just to be snatched by your competitors the next day.

By finding and keeping this information, your business is building a competitive advantage arsenal. And that is the biggest (and most overlooked) benefit of data monetization.

To Sum It Up

Whether you have the data or not, you can greatly benefit from data monetization. You can use it to find new customers and gain strategic advantage.

The best way to provide data is through an API. And the most cost-effective way to build a scalable API is using low-code technology.

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