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How to Monetize Your Data

February 1, 2019

How to Monetize Your Data

How to Monetize Your Data

If content is king, data is the myriad advisors who make that king successful. Data is the king’s eyes and ears and the subject matter experts who make a monarchy more powerful than a solitary ruler could possibly be. The monarch may rightfully get a lot of attention, but in a world where everyone uses data, data gives him his power.

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The world produces an estimated 2.5 exabytes, or 2.5 billion gigabytes, of data every day. Of that data, 90 percent was created in the last two years. The amount of information available to use is growing — and growing fast. That data comes from a variety of sources including online transactions, social media, search engines, web traffic and more.

Data is valuable because it tells companies about their audience’s interests, allowing them to improve their customers’ experiences. Companies can derive value from their own data and they can purchase it from other sources. If you have high-quality data, you can also sell it to create a more direct economic benefit.

Data Analytics Statistic

The Need for Data

Accessing high-quality data is becoming increasingly important for marketers, agencies and all sorts of businesses. Data analytics is a top-five “most important” issue for 38 percent of companies, while 21 percent say it’s the best way to get a competitive advantage. 100 percent of marketers say they believe it will play a major role in the future, according to one survey.

Big data use is expanding so fast that it’s hard to keep track of its growth. It’s no longer just a good idea — now that so many businesses are using it, it’s become absolutely necessary for keeping up with the competition. And as the business intelligence software used to collect, organize and analyze data becomes more sophisticated, that information becomes even more powerful. With the ever-increasing volume of information, data management platforms and advanced analytics become more essential.

The Value of Data

What is it that makes big data so valuable?

Marketing teams, agencies, and advertisers use data to learn more about their audience’s preferences, allowing them to create advertisements and online content that more reliably appeals to users. When marketers know more about their customers, they know better how to meet their needs, resulting in a happier clientele and improved sales figures for their companies. It also helps companies more wisely allocate their marketing dollars.

Businesses can also use data to track how their products and services perform. They can see what’s performing well and what isn’t and take advantage of insights into the needs of their customers. Based on insights derived from data, a company might decide to stop funding an unpopular offering and focus on the options customers prefer. They might also decide to revise their product or strategy to make it better meet customer needs.

The information an organization collects might even explain why certain products, services or marketing messages performed well while others didn’t. Through smart analytics, companies can go beyond just sales figures to obtain insight into people’s motivations and personal preferences.

Businesses, marketers and publishers can use this information to gain a clearer overall picture of their audience, customer base and operations. They can also drill down to different subsectors of the population and even individual users. This enables them to customize their messaging for different groups of individuals to enhance their customers’ experience and create a more personal connection with them.

Companies Collect Information

The information companies collect about their customers and their own operations is valuable because it can improve their products, services and marketing. Your data could also have value for others. What that value is depends on the nature of the information and who’s buying it. If you can provide quality data and communicate its potential uses well, you can earn revenue directly from your data in addition to taking advantage of its more indirect economic benefits.

Is Your Data Ready for Monetization?

If you already collect data, you could be sitting on a potential goldmine. It might also lack value or, more likely, it may not yet be ready for monetization. If you’ve gotten benefits from your data, chances are good someone else will be able to as well.

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But to really know if you’re ready to monetize, you need to assess what you have. Before you attempt to earn revenue from your information, make sure that it is:

  • Dependable
  • Relevant
  • Segmented
  • Secure and anonymized, if necessary

Let’s look at each of those four considerations in more detail.

1. Dependable

The first point has to do with data quality. For your data to be valuable and monetizable, you need to be able to trust its accuracy. You must be able to verify that you gathered your information from a reliable source and in a manner that didn’t compromise validity. You also need enough data and the right data to have a representative sample — one that you can reasonably assume represents reality.

Verify Reliable Information

Say, for example, that you own a newspaper website and are considering selling data to local car dealerships. You could survey five readers about their car-buying habits, but that wouldn’t be enough to make any generalizations. To make that data valuable, you’d have to survey many more.

On the other hand, you can collect online data from your readers who are active on the “Auto” section of your website. This audience of auto readers would also be valuable to local car dealerships, who would prefer to target that specific audience of your website rather than a more general “spray and pray” advertising strategy.

2. Relevant

For your data to be worth anything to an organization, it has to be relevant to their business needs. Those needs, of course, will vary from company to company. Determining whether information will be useful to a buyer requires you to understand their goals and figure out how your information can help. You should make sure it’s organized and in a format they can use.

Data about whether certain customers are in the market for a new car would be valuable to a car dealership because it allows them to market directly to people who are interested in their products. Other businesses would be less interested in this information because, even if it impacts them indirectly, it wouldn’t lead directly to an increase in sales.

3. Segmented

Segmenting your data refers to organizing it into relevant categories to make it more useful. It’s a way to make sense of your data and it allows you to sell data with a specific purpose in mind as opposed to just as a nebulous chunk of raw data. People want to know what they’re buying, so segmentation will make your data more marketable.

The newspaper publisher could segment their audience into groups based on the types of articles people read and the terms they search for. They could then sell data on the users that read car-related stories to car dealerships. Although the dealerships wouldn’t know exactly who those readers are, they could send them targeted ads. This segmented data would be much more useful to them than a batch of unfiltered, generic information.

4. Secure and Anonymized

 Keeping your data protected helps to preserve its value and, when using customer information, is absolutely vital for privacy and security. Insufficient security can lead to a loss in customer trust and even legal trouble. If the data includes personally identifiable information, it carries potentially serious risks.

Because of this, you need to strike the right balance between access and security. In some cases, this might require anonymizing data. Some useful data security tools include:

Useful Data Security Tools

  • Authorization: This refers to controlling who can access the data. It prevents unauthorized people from getting to the data but doesn’t obscure it from privileged users who have been allowed access. This is the minimal level of security and may not be enough to meet regulatory requirements in some situations.
  • Encryption: Encryption obscures data so it can’t be read if stolen. There are different levels of encryption. You could encrypt data only when it’s stored, keep it encrypted when it’s in transit and accessed by privileged users or keep it encrypted at all times. Generally, the higher the level of security, the longer the data will take to process.
  • Masking: Masking replaces the actual numerals of the data while keeping its type and length so that it’s still useful without including sensitive information. You can either mask data permanently or store it in its original form and mask it as necessary.
  • Tokenization: Like masking, tokenization replaces the values in the data while preserving certain elements but uses a different process to do so. It keeps the information secured at all times and you have more flexibility in choosing what fields should be tokenized and can even tokenize only parts of fields.

Depending on the type of records you have and how it will be used, you might wish to make sure you also include other aspects before you try to monetize it. These four things, though, are the main features you should always check for.

How to Monetize Enterprise Data in Five Easy Steps

  1. Identify Available Data Sources
  2. Organize Your Data
  3. Conduct Research and Analytics
  4. Set Terms and Prices
  5. Finalize the Product

If you’ve assessed your data and determined that you could potentially monetize it, your next step is figuring out how to actually go about creating a sellable data product. This process can be a bit intimidating, so we’ve broken it down into five steps:

1. Identify Available Data Sources

Determine what data you have available as well as what other information you need, if any, to make that data valuable or enhance its value. This step basically involves taking stock of everything you have and how it all relates. You should start thinking at this point about how someone could use this data so you can identify any other information you want to collect to make it more marketable.

2. Organize Your Data

In this step, you’ll need to organize your data into a readily usable form. This requires you to unify, connect, attribute, structure and validate your data, among other things. During this part of the process, your data will start to look like a product that organizations will find practical and want to buy.

This is one area where a data management platform, or DMP, and other services, will be especially helpful. A DMP will enable you to collect all of your information into one place and organize it as well as prepare it for analyzing and transfer.

3. Conduct Research and Analytics

Next, you’ll want to analyze your data to determine what insights other organizations could potentially get from it.

When you start selling your data, you’ll communicate these benefits to potential buyers to help them understand its potential uses and make it more marketable. These advantages could include insights into customer demographics, interests, preferences and online behaviors, among many other things.

4. Set Terms and Prices

In this step, you will determine how buyers will access the data, how to decide the conditions of any agreement and how your pricing will work. In this step, you should take into account any legal and privacy issues, which you must balance with allowing access and creating value.

You’ll also need to determine how much your data is worth and you’ll price it. Here are the two main types of data product pricing:

Main Types of Data Product Pricing

  • Cost-based pricing: Based on the cost you incurred to create the data product plus a mark-up.
  • Value-based pricing: Based on the value the customer will derive from the data and, consequently, what they’re willing to pay.

Pricing factors to consider include the volume of data, frequency with which you collected the data, the completeness of the data set, the scarcity of the information, its organization, its reliability and how easy it is to analyze.

5. Finalizing the Product

Once you have a thorough understanding of what you have, you can package it into sellable data products and come up with any other related services you could potentially offer, such as real-time updates and analytics help. It’s likely that your product will be gradable and customizable so it can include different data sets based on buyers’ individual needs.

Three Ways to Monetize Data

Now that you have your data product, how do you actually go about selling it? To take advantage of the economic benefit of collecting data, you’ll likely either sell your data on an exchange or sell it privately. You could also sell either raw data or the insights you obtain from your records:

    • Using a Data Exchange: One method for selling data is to join a data network or marketplace dedicated to buying and selling data products. If you don’t have any leads on potential buyers, you might want to use one of these networks to find them. The advantage is that your buyers come to you and the exchange is already set up for you. The downside is that you don’t have as much control over the process. You’ll also need to conduct careful research about the exchange to ensure that it’s a reputable, capable and secure company.

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  • Using a Private Marketplace: If you already have potential buyers in mind, you might choose to sell your product privately. You’ll have more control over the transaction and won’t have to go through a third party. You could contact a possible purchaser directly and inquire about a sale. You might also set up a private marketplace, which is like a public exchange, except you create the exchange yourself and only invite a few companies to bid on your product. Some organizations, including Lotame, run private marketplaces where you can sell second-party data directly to participating users, while still having control over pricing and other terms.
  • Raw Data vs. Insights: Some businesses sell access to data while others maintain sole control of their data and instead offer to share insights they gained from it. You might offer the results of analyses you already performed or, if you have resources and personnel to do it, offer to use your data to solve specific problems and produce custom insights.

Solutions from Lotame

At Lotame, we’ve followed these steps to create our own global data exchange. The Lotame Data Exchange takes care of the hard work for you by providing you with access to information from billions of mobile and desktop users worldwide and over 5,000 pre-packaged audience segments. We’ve also taken measures to remove bots from our profiles and to maintain top-notch privacy standards.

Syndicate is our private, second-party data marketplace where premium publishers can connect directly with buyers in a transparent environment. Syndicate gives you access to buyers, but you still maintain control over pricing and other commercial terms. You can choose to exchange data within Lotame’s DMP or transfer it directly to the buyer through a demand-side platform, or DSP.

For more information on our data services, contact us or request a demo.

Start to Monetize Your Data Today