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. 

Disrupting payments and unlocking the value of data

(First published on Instapay Today)

PSD2: the latest tightening of data regulations will require strategic, operational and infrastructural changes for banks and financial institutions. 

Is it an opportunity or a threat though? Judging from current opinion, it appears the financial industry hasn’t quite made up its mind. If there’s anything worse for the sector than a clear and present threat, it’s uncertainty.

In a recent survey conducted by open banking platform Tink, one thing is clear, financial institutions dislike regulation. They named it as the biggest threat to their current business models. With the final PSD2 deadline looming on the horizon, there is little time for firms to get wrapped up in an existential crisis though. Most are soldiering on, despite their doubts, to ensure they can comply with the new directive. They are investing in digitization, greater security and privacy. 

However, it’s clear that they need to do more than the bare minimum in order to not only survive, but thrive, in this new ecosystem. For banks, payment service providers (PSPs) and other players, PSD2 unearths an opportunity for them to innovate and compete.

Data should increasingly be viewed as a natural resource like oil. Yes, data is the new oil is a somewhat tiresome cliché, but sitting on an oilfield is not much use unless you have the right tools, infrastructure and capabilities to make something out of it. In that sense, firms need to grapple with how they can turn what is essentially a commodity, into a competitive advantage.

To benefit from the opportunities that will arise from PSD2, there are two key approaches any financial or payments services firms can take in the new landscape:

1. Monetize their data – Increasingly, no one party will have a monopoly on data. This means firms will need to start thinking about how to leverage their distinctive data sets as part of a data monetization strategy – without compromising sensitive personal information.

When it comes to monetizing data, many are enticed by the opportunity, but they may view it as a challenge. They may raise questions over data ownership and privacy. 

However, there is great value in anonymized, aggregated information that is used for business or investment insights. In finance, the interest is in identifying broad trends and patterns – the focus is never on the who but the what and how much. That means it’s possible to extract value from this data while preserving privacy.

Outside finance, there are other examples of how sensitive data can be used in a way that benefits the public. For instance, Uber shares anonymized data aggregated from billions of trips taken by its users in order to help urban planning around the world. 

Transparent and responsible use of this data can open the door to new revenue streams. Data might not be the core business for many of these firms, but revenue from this can quickly become meaningful as the quantity and quality of data grow over time. 

The value of their data can also increase when combined with multiple sources for consumption by third parties.

It can sound counterintuitive to deal with the threat posed by open data by sharing it even more widely. But this allows firms to strengthen existing data and play a more important role in the transactional ecosystem. Payments providers are well-positioned because they have unique insights into both merchants and consumers. 

2) Get better customer insights – The changes that will be brought on by PSD2 will show that no incumbent can afford to rest on their laurels. The classic mindset of getting all your financial services from one provider is going to change. Many payment experiences will change and become more seamless.

One hot topic is instant payments. While consumers are the biggest benefactors of this trend, merchants can also benefit from it in a number of ways. Instant payments are data-rich so they can leverage real-time data like never before. 

What does this mean for firms in this industry both big and small? Well, it will become more important than ever to convert data to actionable insights. They can use such insights to improve the customer experience, drive loyalty and even introduce better offerings.

This can help incumbents become much more data-driven and customer-centric in their approach, leading to better decision-making. Meanwhile, smaller players that can nimbly respond to these insights can outmaneuver bigger competitors and eat away at their market share. 

Ultimately, firms need to tackle PSD2 from a strategic perspective and not just from a compliance perspective. The ones that proactively capitalize on these opportunities can future-proof their business and disrupt, rather than be disrupted.

An Alternative Way of Seeing Data Monetization

From early-stage payments fintechs to giant acquirers, every company is asking themselves the same question: “How can we turn our data into dollars?”

After all, most companies these days are to some extent data companies, whether they are aware of it or not. Many businesses try to leverage certain types of data they capture, but there’s also a lot of valuable ‘data exhaust’ they could use without ever sharing any personal or sensitive information. This is known as alternative data and it is being rapidly monetized and shared in the US and Europe.

What is data exhaust?

No, it doesn’t refer to the exhausting nature of big data. (Though there is something to be said about that too!)

Data exhaust refers to the excess data that is generated as a byproduct of a company’s operations. Simply put, it’s all the data the firm might not know what to do with, or might not think is relevant to its core business. This amount is much bigger than you think – Forrester reported that on average, between 60% to 73% of all data within an enterprise goes unused.

However, with advances in IoT, machine learning and artificial intelligence, this rapidly growing volume of exhaust could hold much untapped potential. In fact, this data exhaust could end up being converted into valuable fuel, whether for better decision-making or new ancillary revenue.

Why is data monetization so hard?

Firstly, many firms struggle with what data monetization actually means. Some paths to data monetization are more obvious than others. We’re living in an era when exploiting data for advertising or marketing purposes has become a huge concern. Even when there is no threat to personal privacy, organizations still have to navigate reputational risks if there is even a whiff of data misuse.

Secondly, trying to glean insights from all this raw and unstructured data can be like finding a needle in the haystack. It’s a significant challenge in terms of resources and infrastructure, requiring data expertise that is usually not found in-house.

So what can companies do to tackle this?

Two routes to monetization

These are the two primary paths to data monetization that companies can choose to take, though they are not mutually exclusive. In fact, both paths can intersect and one can lead you down the other:

1) Getting new business insights – This is an internally focused path that may not directly lead to money on the table. But it’s about leveraging data to improve operations or the customer experience. In turn, this could lead to higher profitability or greater efficiencies that result in reduced costs.

Alternative data can yield insights that we may have otherwise not considered. But it’s easier said than done because, as Forbes reports, 87% of executives are still not confident they’re able to leverage all customer data.

But first, every organization needs to take stock of its data assets and figure out which types of data potentially hold value. Then they need to assess whether they have the data management infrastructure, tools and resources to be able to extract value from it.

2) “Externally” monetize data – These days, the mere mention of “selling data” conjures negative reactions. But there are ways of monetizing non-personal data that is aggregated and anonymized. This can be valuable to people you may not be thinking of in ways you might not have imagined.

Opportunities may exist in markets that are new and unfamiliar to the data owner. For instance, firms can open up new revenue streams by selling their data to economists, analysts, investors and any other parties that are seeking to gain new and unique insights.

Raw data by itself can be one-dimensional. It is when data from different companies and sectors is combined and enriched with complementary data sets that real value is created. For instance, a company working with vendors across the country might have data on national beverage sales. It could track these sales and provide additional insights back to the vendors to help them improve sales and promotions. The company could also share this data with beverage brands so they can finetune and optimize marketing by city.

Think about it this way: Doing nothing with your data is the equivalent of keeping all your savings under the mattress. It seems like a safe bet, but it’s outdated and you get zero returns. Data monetization is a smarter investment – it seems daunting at first but if you can find a safe, meaningful use case, your company’s data becomes a revenue driver rather than a sleeping asset.