Valuing Your Data: A Checklist For Companies Looking To Monetize

Not all data is created equal.

When companies make their tentative first steps on the road to direct data monetization (that is, selling non-personal data they own), they have to start by understanding the value of their data. They need to assess what types of data they are collecting or generating in the course of business, and whether these could potentially be a new driver of revenue.


It’s often said that data is an important and valuable asset in any organization, but there’s a reason why it never appears on a balance sheet. Data valuation is a complex and challenging exercise. But knowing what their data is worth can help companies explore monetization, allocate resources and properly structure their technology infrastructure. 

In addition, they have to understand the market’s perception of value. Some firms might be overestimating the monetary value of their data, while others are unaware that their data is valuable, often to people in sectors and industries they may not have even thought of. A Forbes contributor compared the latter to the instance when companies realize they’re sitting on patents they don’t really need, but actually have value to someone else.

So what are the fundamental characteristics of high-quality data that organizations need to consider when trying to measure its value? Or more simply put – what makes data valuable and how much is your data worth?

1. Does it tell a story?

Does the data tell you something about the economy or market trends? Does it track which brands are growing or which products are in high demand? The better your data reflects real world behavior, the higher its value.

2. Is it unique? 

Generally, the more exclusive the dataset, the more lucrative it is. Do you have data that nobody else has, or is it already widely available from other sources? 

3. Is it anonymized and compliant?

If you are planning to share raw data, it needs to be stripped of all personally identifiable information (PII) to protect the privacy of individual customers. This is critical in order to monetize data responsibly, as data privacy is not optional but essential.

4. Is it timely? 

Is your dataset updated on a weekly, monthly or a near real-time basis? The latter is most desired, especially for economists and institutional investors that are looking for faster insights to stay ahead of the market. 

5. Is it specific? 

The more granular and detailed the data, the more valuable it is. (Though to reiterate, personal details should definitely be excluded!) For example, data showing a million smartphones were sold last week is valuable. But its value grows significantly if it also indicates how many of those smartphones were iPhone X or Samsung Galaxy, etc.

6. Is it complete?

Do you have data for every day, without any gaps? Missing data could be as bad as inaccurate data, as it provides only a partial view of the real trends. 

7. Is it reliable and consistent? 

If there are multiple servers where data is collected or stored, do they all add up properly? Or do they contradict with one another? Are there potential duplicates or other data errors?

8. Do you have archives of historical data? 

The further back your data goes, the better. Historical information is used in all kinds of analytics. In most use cases, two or more years of data are important to see how trends are changing over time. 

Can Data Monetization and Privacy Co-Exist?

Spoiler alert: Yes, they can.

The media often makes it sound like a choice has to be made between monetizing business data and maintaining privacy. But it’s not an either/or situation, it’s possible to do both at the same time.

Since the EU rolled out sweeping data protection directives through the General Data Protection Regulation (GDPR) in 2018, firms have been questioning how to leverage their data while being compliant.

Indeed, the Business Application Research Center (BARC) found the issue of data security is one of the major stumbling blocks for organizations in monetizing their data. If they fail to find a way past these barriers, they are not only missing out on a valuable opportunity, but they could also end up eating the dust of more agile competitors.

In its report, BARC stated that, “for many the risk of using data for internal and external monetization seems to outweigh the potential benefits.”

Maybe it is because businesses have been so unnerved by negative headlines regarding data privacy scandals that they fail to truly grasp what is possible under these regulations. 

Let’s focus on external monetization, which is basically about leveraging your internal operational data to create a new revenue stream. But today, the mere mention of “selling data” creates a fear of reputational risk. 

Ensuring data privacy should rightly be a chief concern for every company that is dealing with highly sensitive customer data. It’s not important just from a compliance perspective, but essential for building customer trust and loyalty. 

However, there are ways of monetizing non-personal data and this is often an opportunity that is overlooked. Companies may ask, “How can my data be valuable if it’s missing certain pieces of the puzzle?” That is because they assume the personal details form the critical components. But in fact, even an aggregated, anonymized form of the data could still form a complete picture for others. These could be people in different markets and industries, like economists, analysts or investors looking to identify patterns and trends. 

In addition, new tools and technologies have made it easier and faster to extract, refine, enrich and anonymize this data. It is this process, enabled by technology, that helps to wring the maximum value out of a company’s data. 

The early adopters in the use of alternative data, institutional investors, are rapidly increasing spending to acquire information that helps them make better decisions. Unlike advertisers, they have absolutely zero interest in personally identifiable information (PII). What they want is empirical, anonymized data that tells them how companies and markets are performing. How many beers are being sold by Heineken across Europe this quarter? Is Deliveroo seeing more orders than UberEats? Economists and analysts  have strict compliance procedures and actually demand that the data they buy are stripped of consumer-level data.

Service providers are well-positioned to capitalize on the rapidly growing opportunities to leverage their data in the digital economy. But there shouldn’t be a tug-of-war between monetization and privacy. Forward-thinking firms will understand how they can turn their data into profit while having the utmost respect for privacy.