Why Monetize Data A Brief Guide

Why Monetize Data? A Brief Guide


Table Of Contents

If you’re looking to monetize data, the market is expected to hit as much as $15 billion by 2030. In other words, in just under ten years, it’s expected that the value of data will rise by over $10 billion.

Data monetization is critical to businesses for a few reasons, including:

  • It allows them to create another reliable revenue stream just by selling the data they already have.
  • It allows them to gain insights into their customers, business operations, and more and identify opportunities that benefit the entire organization, such as increased workflow and process efficiency, optimization, and product development.
  • It allows them to foster partnerships with child companies under the organizational umbrella, as well as with external organizations, for mutual benefit.

These are just a few examples, but there’s a lot more to data monetization that’s worthy of discussion. This guide examines data monetization and further looks into the benefits it can provide for businesses.

What Is Data Monetization?

To put it simply, data monetization means using data to receive quantifiable economic benefits. With the big data industry worth around $271 billion, there’s certainly a lot of economic benefits to be had, regardless of whether that’s financial or not.

Prepared data contains all kinds of information that can help businesses make better decisions. Businesses can use this data internally to improve operations, sell to third parties in order to increase revenue streams, or develop strategic partnerships.

There are two main approaches to data monetization that businesses can use to gain value from purchased or shared data:

  • Internal or indirect methods: using data to make measurable improvements within their business and drawing value from data for use within the company
  • External or direct methods: selling data to third parties in order to gain some sort of economic benefit (usually financial)

Indirect data monetization methods, for example, could involve a company conducting data analysis using their own internal data and using the results to optimize their sales workflow between suppliers and distributors. Let’s say that the data showed a consistent problem: when a distributor requests product from a supplier, it takes a week or more for the supplier to action that request. Based on this information, the next logical step would be investigating the reasons behind why this delay exists, and taking steps to fix it. This process optimization has real economic benefits in terms of saved time.

On the other hand, direct methods of data monetization could involve packaging existing data and selling it to third parties. This direct sale of data would also benefit the business economically, adding another revenue stream that increases the value of the organization.

Why Monetize Data?

Organizations choose to monetize data for three reasons:

  1. Build strategic partnerships
  2. Create new revenue streams
  3. Streamline operations

Let’s go over each of these reasons in more detail.

Create Strategic Partnerships

One major way that companies can benefit from monetizing data is to create strategic partnerships. When companies choose to sell their data to third parties, they can foster strong, mutually-beneficial relationships that result in better processes, cost savings, and a myriad of other benefits.

For instance, businesses can create cloud-based data sharing systems that allow themselves and other business partners in their supply chain access to valuable insights about typical customer buying patterns in their industry. The result is that partners across the data sharing network have a better understanding of seasonality, meaning they can more accurately predict needed inventory levels and save money on overall inventory costs.

Creates New Revenue Streams

Even if a company doesn’t plan to sell its data to a third party, this data can still generate new income streams.

Data monetization can help businesses identify new trends and business opportunities. Companies can then use those insights to build new products, improve customer service, improve processes, and much more. For example, a manufacturer could sell datasets that can be used to increase the efficiency of machines that those in their industry often use. The augmented data could show how, when, and under what conditions certain machines can be run at a higher capacity when manufacturing certain products safely—increasing output in the same amount of time and allowing more products to be produced and sold. By selling this dataset to other businesses in the same industry⁠—and promising to augment it over time with additional real-time data— a revenue stream is created.

Streamlines Operations

Internal data monetization can have major implications for company operations, too. When businesses make strategic use of their internal data marketplace, they can develop analyses that give them greater insight into their customers and operations.

That could mean using insights to improve workflows and processes, leading to more efficient and optimized operations throughout the organization. For example, a ready-mix concrete company could use data to determine the best mix configurations, maximizing the use of raw materials to reduce waste.

On the other hand, route data from concrete deliveries could be sold to third parties inside and outside of the ready-mix concrete industry to improve their own routing and delivery schedules.

How to Create a Successful Data Monetization Strategy

How to Create a Successful Data Monetization Strategy

Even though data monetization can be extremely valuable, it can also create many challenges if not implemented correctly. As a result, proper planning is key to developing a successful data monetization strategy.

Understand the Value of Data to Your Company

One big part of ensuring that you develop a successful data monetization strategy is understanding how valuable a certain data set is to your business.

For example, if you have information on customers but have no way of using it or connecting it to your business, that data isn’t very valuable. On the other hand, data that provides unique and actionable insights into your company or market segment is highly valuable for improving and streamlining operations.

Essentially, to measure the value of data, you need to measure how data contributes to your overall business goals and objectives. One way to determine this is to look at how data helps your business achieve its KPIs. Additionally, you can also create systems that are flexible and can vary as you discover which pieces of data provide further insights and aid to your business for current and future needs.

Managing Data Correctly

Your data is only as good as the management is. In other words, when companies have poorly organized and managed data, it can become ineffective.

Part of developing a strong data strategy for monetization means setting up systems that make data easy to sort, organize, and find. It also reduces duplication and helps increase the overall quality of the data that companies are dealing with.

A few best practices for strong data management are outlined below.

Method Explanation
Create standardized naming systems Organize information according to date, location, time, or another uniform standard. This should be descriptive of the data and user-friendly to help individuals find key information in the future.
Attach metadata to data sets Add metadata details such as the author name, time and date, location of creation, and other descriptive information. This can make sorting and sifting through data much faster and easier when looking back and looking for old information.
Set up multiple documentation levels Come up with a documentation system that helps you sort and classify data. This could involve organizing data at the project and file level to keep information streamlined, coherent, and easily identifiable.
Establish secure systems Cyber attacks happen roughly every 39 seconds, making having secure systems for sorting, accessing, and sharing data key. Add security measures in place that ensure your data sets don’t get into the wrong hands or suffer breaches.

With good management of data, it also becomes easier to resell insights to other companies. That means this adds value for internal data monetization and improves external data monetization by making better-sorted insights that can be sold at higher prices.

Understand the Value of Your Data to External Stakeholders

Just as it’s important to know the value of data to your business, it’s also important to understand your data’s relative value to other companies.

This involves identifying how exclusive and specific data is. If the data you have is something that only you have access to, that makes it much more valuable than if it’s data that most companies already have.

Another thing to note when understanding the value of data is that the more specific a piece of data is, the more valuable it tends to be. Data that is very detailed and provides specific information tend to hold higher weight than data that is general or doesn’t provide as much detailed information to companies.

Finally, it pays to know how workable the data is. Data may be organized in a way that’s useful to one business but not to another. If a great deal of additional processing is needed to prepare data for a third party, this may reduce the value of the information.

Assess the Price to Monetize Your Data

Data products pricing can be tricky, especially considering that there are several ways organizations can price their products. For instance, through Revelate, companies can choose from a few different pricing models for data monetization:

  1. Pay-as-you-go
  2. Subscription
  3. One-time purchase

Revelate also has six data sales business models available to monetize data. These business models include:

  1. Direct sales
  2. Self-service sales
  3. Resellers
  4. Data brokers
  5. Marketplaces
  6. Guided sales

These models give companies various methods for making buyable data available to potential consumers and for assessing a price that makes sense for specific companies.

Manage and Deliver the Data

Finally, a solid data monetization strategy involves correctly delivering information. Data delivery involves knowing how to market your insights to other companies to drive value and create demand for the information.

Additionally, it involves determining an appropriate channel of distribution. Using a data-sharing platform or service can help enterprises distribute data to third parties and accelerate data monetization.

Before settling on a data monetization platform, it’s important to ask key questions, such as:

  1. How will customers access data?
  2. How much choice do customers have in the data they select?
  3. What payment model will be accepted?
  4. Who benefits from this model?
  5. How will data be distributed?

Asking these questions, among others, can help establish a platform that makes data distribution for monetization purposes easy and straightforward.

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Revelate provides a suite of capabilities for data sharing and data commercialization for our customers to fully realize the value of their data. Harness the power of your data today!

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Data Monetization Use Cases

In order to really understand monetization, it pays to take a look at a few use cases. Although there are multiple industries that can benefit from data monetization, let’s take a look at the following three specifically:

  1. Consumer goods
  2. Agribusiness
  3. Financial Services

Data Monetization in Consumer Goods

Companies that sell services or products can use a variety of data, such as consumer interaction data, one-off data sets, survey data, forecasting reports, or benchmarking.

From there, those businesses can monetize data in numerous ways, including:

  • ESG reporting data sharing to optimize regional product pricing
  • Optimizing product purchase and logistics via data analytics
  • Incorporating third-party data to forecast retail store foot traffic

These are just a few of the ways that businesses can use data monetization to improve and streamline their businesses or to create new revenue streams.

Data Monetization in Agribusiness

Although the agricultural industry isn’t one that most people think of as involving a lot of data, it does. Farm field data and the information that agricultural sector workers glean from their work each season can be collected, organized, and shared to help improve the following year’s crops or to improve other businesses.

Here are a few examples of how agricultural workers and farmers can monetize data.

Method of Data Monetization Explanation
Share Incentives Federal and state governments within the US and other countries provide incentive programs, such as the cap and trade program, to sustainable farmers. However, in order to take advantage of those credits, industry workers have to be able to provide data showing things like reduced electricity or water usage.
R&D Agricultural workers constantly make adjustments to their crops based on insights from last year’s harvest and planting efforts. When compiled, all that information can help farmers improve their operations on their own farms. It can also be sold to third parties who could benefit from those same insights to further their business objectives.
Aggregating data selling When farmers pool their data, they can gain additional insights that make their jobs easier. Although this can create more competition, it can also be leveraged to farmers’ advantage. When farmers pool that data, they can sell it to large corporations that can use those insights to target farmers and agricultural workers better.
Real estate Having insights into the yield of a specific agricultural land can help realtors better determine the value. If you choose to sell that land, you can end up improving your profits just by having data to support your claims of how much the land is worth.

Data Monetization in the Financial Services Sector

Financial institutions have also made use of data monetization to help further their objectives. They’ve also established their own internal systems for capturing data which they can then use towards effective internal improvement.

A few examples of how data monetization can improve financial institutions include:

  • Optimizing investments
  • Improving risk models
  • Adhering to ever-changing regulations
  • Incorporating alternative data

Additionally, new companies can receive information from a third-party data collector that aggregates statistics to their own internal data. The combination of these data sources allows financial services providers important information for use cases such as determining lending risk, investment opportunities, and more. Financial services and banks have adopted dozens of data monetization techniques to generate more income through this practice.

These industries hold large amounts of information from customer transactions, for example, and use it to generate cross-sell offers and in general, improve information collection technologies, and create customer reward programs, among others.

For example, financial institutions can reduce risk in lending. By acquiring internal data on lender habits and trends and using external risk analyses, companies can determine which customers are more likely to default on loans and which are more likely to be responsible borrowers.

How to Prepare for Data Monetization

Implementing successful data monetization involves being fully prepared. In order to properly prepare for data monetization, your business should create a framework that ensures the success of your data monetization strategy through:

  • Gaining buy-in
  • Assessing existing data and determining future collection
  • Deciding on an audience
  • And establishing objectives

Let’s take a closer look at these steps and how they can be properly leveraged in order to set the stage for a strong data monetization program.

Gain Buy-Ins

Gaining buy-ins means ensuring that everyone involved in implementing the new strategy is on board with the program and believes in it. When leadership buys into the new process, the rest of the team is more likely to as well.

Gaining buy-ins should start with internal leadership. Once internal leadership buys into the idea, they can gain the support of stakeholders by sharing their position on the strategy and explaining the strategic benefit to the business.

Assess Existing Data and Define the Future Collection

The next step is to look at the data that your organization already has. In some cases, this data may already offer insights and have an appropriate analysis which means it can be immediately put toward data monetization purposes.

To assess your existing data, take inventory of the data you already have. Sort it into categories that allow you to easily see what information you have, what you’re missing, and what could be useful in the future.

Sometimes, you may need to go back through and process this data to prepare it for use. Doing so helps prepare existing raw data for use in the future It can also help establish how you’ll process future raw data that your organization collects.

Once you’ve taken inventory of and assessed your existing data, it’s time to define future collection efforts. Use the information you’ve gathered from existing data sets to figure out what’s missing and what you need to focus on collecting moving forward.

Decide on an Audience

Deciding on an audience will help you properly monetize data. Data is used differently depending on the industry, niche, and organization involved. As a result, it needs to be processed and prepared differently depending on how it will be used.

In order to determine this, businesses need to consider who the audience will be. This involves determining your customers, how they’ll use your data, and how it might be relevant to them. From there, you can start developing a data monetization strategy that furthers their objectives.

Establish Objectives

The main goal of data monetization is to gain some economic benefit. Within that goal, however, will be smaller objectives.

Organizations need to think first about whether they plan to monetize data internally or externally. From there, they’re able to define what outcomes they want to achieve in doing so.

For example, a business indirectly monetizing data could make their objective to target their market segment better. Or, a business directly monetizing data could set their objective to be to create larger partnerships and more accessible data within their niche.

Benefits of the Monetization of Data

Why Monetize Data A Brief Guide

Implementing a successful data monetization strategy can improve your competitive advantage and strengthen your understanding of your customer base. It can also create more streamlined operations and help with business growth.

Here’s a deeper look at some of the benefits of the monetization of data for businesses.

Improving Your Competitive Advantage

Businesses that have access to valuable data and put it to use can strengthen their competitive advantage. When they use the insights available to them through data, they’re able to improve market targeting.

This means that they can spend more time marketing to consumers who are likely to make purchases and become customers than those who aren’t. With these changes, they gain an advantage over companies that aren’t making use of this type of data.

Strengthens Your Understanding of Customers

Proper data monetization can strengthen your understanding of customers. That’s because, by monetizing data, you can conduct an analysis of information and gain powerful insights into your customers’ behavior.

In many cases, this type of data monetization is indirect, meaning that businesses monetize data internally in order to drive economic value within their own company rather than through the sale of data.

Considering that 81% of businesses compete solely based on customer experience, improving your customer satisfaction is a major factor in the success of your organization. When companies better understand their customers, they know what customers like and dislike. This enables them to enhance the customer experience by addressing pain points and creating more user-friendly processes across sales, support, and deliveries, and more.

Assists in Finding New Areas of Growth

Internal data monetization can also help businesses identify new areas of growth. This could be identifying the need for an entirely new product or service, or using customer insights to determine changes to an existing product or service in order to target a new part of the market and expand operations.

Helps Streamline Decision-Making and Planning

When access to data is democratized through an effective data monetization effort, making access to datasets easy for internal and external stakeholders, data-driven operational decisions can be made faster and easier.


Thanks to the increasing value of information in today’s commercial climate, data monetization is becoming a winning initiative for businesses looking to enhance their economic value.

On top of that, this market will only grow within the next few years. That makes leveraging data monetization even more important to businesses today.

If you plan on starting a data monetization strategy within your company, one of the key aspects of doing so is to make use of data marketplaces and data web stores in order to manage, package, market, distribute, and access data securely.

Book a demo with Revelate to learn more about integrated data systems and how they can support your data monetization strategy..

Simplify Data Fulfillment with Revelate

Revelate provides a suite of capabilities for data sharing and data commercialization for our customers to fully realize the value of their data. Harness the power of your data today!

Get Started