Monetizing Data: A Suburbia Partner’s Story

This payment solutions company has partnered with Suburbia to monetize its point-of-sale transaction data and create value for its clients. Due to client confidentiality, this company has chosen to remain unnamed, though every effort has been made to preserve the integrity and accuracy of their statements.

This fast-growing European company provides point-of-sale (POS) solutions as well as other payment related products and services merchants need to run their business smoothly. It specializes in several niche markets though its solutions can be found in tens of thousands of merchants.

Our goal: “Payments are becoming commoditized so we’re aiming to offer a variety of complete merchant solutions and value-add services to encourage greater customer loyalty. This will also create new growth opportunities for us as a business.” 

Our problem: “As our POS systems capture millions of transactions annually, we were sitting on a mountain of data – but we weren’t doing anything with it. But this data started drawing the attention of major market research companies.

We didn’t feel comfortable working with them. They would ask for a CSV dump or ask if we could simply load the data on a USB stick and hand it to them. Once we were asked to report numbers over the phone and someone on the other end would be recording them in an Excel sheet. There are a number of things that can go wrong in these scenarios. It also doesn’t build a whole lot of trust and confidence when you see data being handled that way.”

The solution: “When we met Suburbia, what we learnt was a real eye opener for us. We learnt how our data could be useful for a financial audience. The way that different sources of ‘alternative data’ are being combined to yield new insights was really interesting to us. It made us look at our own data in a whole new light and see the possibilities.

In the beginning, the challenge for us was in making sure we provided our data to Suburbia in a form so that our merchants remain anonymous. Our clients are aware that their data is shared in an aggregated and anonymized way. But you can make some accurate inferences based on, for example, the location and time of transaction. In some cases, there are own-brand products, like a store called Bill’s that sells an item called Bill’s Burger. We took pains to ensure they couldn’t be identified based on details like that, so Bill’s Burger is just listed as a generic burger.

Our mission is for our clients to see that our POS is not just a good investment but they will also see returns on that investment. We have been investigating different propositions and potential revenue models with a small group of trusted clients or ambassadors. So they can potentially be rewarded a certain fee for every transaction processed. They didn’t even know their data could be useful and valuable for others. That’s a fantastic value-add for them and it can become a competitive advantage for us.

It’s not just the money but there’s the possibility of sharing data and insights with our customers. Imagine if they can see not just their own data, but data from across the industry that allows them to benchmark their performance.

Advice for other businesses looking to monetize their data: “It will seem like there are a lot of initial hurdles to overcome. But if you’re working with a partner for data monetization, it’s important to just get to know each other and establish a relationship of trust. Once that’s done, there are two important things to keep in mind: 

First, go all in if you’re serious about monetizing your data. Don’t give out a partial data set. Commit to reliably delivering the data at the frequency specified without fail, whether it’s daily or weekly. 

Secondly, don’t rush it. Monetizing your data doesn’t happen overnight and we appreciate that it’s a long cycle. It’s a journey where we’re testing and learning together with Suburbia. It’s better to get it done right than to get it done fast, especially in a business like ours.”

If you think that your business generates interesting data, please talk to us. We have a simple, confidential process that lets us evaluate the quality and potential monetary value of your data, and come back to you with a roadmap to monetization.

Monetizing Payments Data Responsibly Pays Off

Originally published in Financial IT

If you are opening a small kiosk near a university campus in the Netherlands’ biggest student city of Utrecht, make sure you stock more premium coffee than cheap coffee.

At least that’s what the point-of-sale transaction data* shows. We’ve all seen the news articles poking fun at broke millennials for spending too much on artisanal products and avocado toast, so it’s not a groundbreaking insight that they also like splurging on fancy coffee. But it’s only now with the advent of connected devices that trends can be quantified accurately and in real time.

Payments have become a seamless part of the customer experience, able to be now completed with a tap, a wave or a click. Despite their invisibility, payments data can yield rich insights about economic trends.

Building an ecosystem of insights
Traditional methods of understanding consumer preferences are no longer effective on their own. For instance, surveys are limited, inefficient and biased. Transaction data can provide far more granular insights to various stakeholders – from retailers and restaurants to corporations and investors. Institutional investors and economists are already using this data to make better decisions. 

This means companies, from retailers to payments firms, can create a new revenue stream by monetizing their data. Even when this data is anonymized, many are still concerned about unintentionally exposing the identities of their customers. However, the key is in aggregating the data in a way that doesn’t include sensitive information about any individual source. 

Aggregate data, stripped of identifying details, can still be a powerful source of insights. For example, we track data on beverage sales in on-trade channels (the industry term for restaurants, bars and cafes) across six countries in Europe. This data can be used in all sorts of ways. A business can use it to help price products competitively without having to physically visit all the other bars in the city. An international food and beverage (F&B) operator can use this information to decide on the best location for its new outlet. Meanwhile, the payments solution provider collecting this data can tap into it to serve merchant partners’ needs. This means the same data can have a meaningful impact across different organizations and across the whole value chain.

Our mission is to democratize access to this underutilized data so that someday, even a consumer can use this data to find out where the cheapest gin and tonic cocktails are in their city!

Bringing outside insights into the boardroom

Sometimes analyzing your own business data simply isn’t enough to provide the full picture.

According to research**, the rate at which companies are using external data sources is outpacing that of internal sources. In a more connected and complex world, organizations are starting to realize that their internal data is just one piece of the puzzle.

For instance, many companies may already have a good grasp of what they sold last week, last month, or last year. But this may not be sufficient to predict what will sell tomorrow. The most accurate predictors often come from external sources – forward-looking market trends, competitive intelligence and insights that provide greater understanding of the environment in which the business operates. For example, by looking at historical sales of premium alcohol in our dataset, one can make inferences about growing affluence or gentrification in certain neighborhoods. Now, imagine being able to get a sense of that in real time!

The problem is most merchants don’t have the capability to easily crunch through all this information. This creates an opportunity for their payments partners to help connect the dots. They can use this data in a strategic way to create new products or expose the data in a way that delivers value to merchants.

Merchants shouldn’t have to think about data, after all, and be distracted from their core business. What matters for them is getting actionable insights. For instance, insights on anonymous customers’ full wallet spend and basket composition can help merchants optimize their operations or improve the end-customer experience. 

Knowing what your customers purchase in your store or restaurant is one thing – but being able to access aggregate industry data is even more powerful. If we see that nachos and beer in the same transaction lead to an average 30% higher consumption in beer, then we can advise merchants trying to increase beer sales to include nachos on the menu. 

Getting data monetization right

As all the examples above show, a robust data monetization strategy is important for innovation, growth and a competitive edge. But many companies are also wary of the challenges of extracting value from such vast amounts of data.

This is why it’s important for them to find partners that can help them establish a strong and safe data foundation in order to build the business case and technical platform needed to effectively monetize data. This requires close collaboration and a unified approach that can turn their data into both revenue and insights.

*Coffee sales in Utrecht from October 2017 – September 2018

**Business Application Research Center, March 2018

Lemon Lime and Data: How Sprite Has the Secret to Data Security

It’s cold, it’s refreshing and it pairs well with spicy food, but what can Sprite teach the world’s biggest tech companies?

In the raging debate about companies’ use of personal data for profit, people often think there are only two choices: Hand over all your personal data, or stop using online services like Facebook or Google Maps completely.

But this puts the burden of responsibility on consumers, who may not have the resources or information available to make the right decision. Instead, companies handling personal data should take proactive steps for better, safer products. And they only have to look to the soda industry for inspiration.

For decades, soda titans like Coca-Cola and Pepsi enjoyed uninterrupted growth, building global beverage empires and becoming household names. While there were always concerns linking soda to health problems, they didn’t start hitting the mainstream consciousness until the end of the 20th century. By then, soft drinks makers were often fingered as the sole culprits for rising obesity rates.

Today, dozens of countries around the world, including the UK, France and Norway, have slapped a tax on sugary drinks. While the tax has not yet been introduced in the Netherlands, Coca-Cola took an unprecedented step there to stay ahead of regulations.  

Coca-Cola’s game-changing decision

In 2017, the company pulled normal Sprite from the market, replacing it with the no-sugar Sprite Zero. This means when you order a Sprite in Holland, you will be served the sugar and calorie-free version by default. It has become the “regular” Sprite.


Coca-Cola said Sprite had been performing well, so it wasn’t just another move to boost sales. Instead, the beverage giant was making an important step to future-proof its business and provide a healthier product, without forcing customers to choose. Although they eliminated the bad choices, they were still able to offer variety to consumers, with new flavors like lemon lime and cucumber. 

So what if we take the same step for data? 


While businesses handling our personal data assure us that our privacy matters to them, the news headlines tell a radically different story. How can consumers trust companies when there are high-profile data breaches and incidents of companies misusing our data on a regular basis?

Most firms handling personal data are unlikely to make a change unless they feel the noose of legislation tightening. But as we’ve seen before, legislation is not a magic bullet. Consider Europe after new data and privacy protections (grouped under GDPR) went into effect in 2018. According to the International Association of Privacy Professionals, almost 100,000 privacy complaints have been filed but only a few have led to meaningful penalties.

In the case of soft drinks, Dutch experts have questioned whether a sugar tax would even make a serious dent in consumption unless the tax was a substantial one. 

Even when there are stricter rules in place, they can still fail to change consumer behavior or address the loopholes that allow companies to conduct business as usual. The ubiquity of those consent forms on websites have only encouraged people to adopt a click-and-ignore mentality, so that they can just make the pesky pop-up disappear as quickly as possible.

When it comes to data privacy, there are those who argue that people can actively choose not to use the services of companies that exploit their data. Well, maybe they shouldn’t have to make that choice themselves. 

Facebook Zero 

Just like how Coca-Cola offers only the zero-sugar Sprite in the Netherlands, zero personal data could also be the norm. Companies may need to collect some user data in the course of doing business but there should be limits as to how much information they can amass on an individual. Why does a social network even need to know your gender, in the first place?

It has become untenable for firms to say they value consumer privacy while collecting and hoarding user data, putting it at greater risk of breach or misuse. The same way it was impossible for soft drinks makers to say they care about their customers’ health while shilling beverages loaded with sugar.

More importantly, instead of trying to defend their key sales driver, the soda companies innovated and looked for new opportunities. They reformulated, they introduced smaller packages and they made it easier for consumers to embrace a healthier lifestyle. As a result, Coca-Cola’s revenues have stayed sweet even if their drinks haven’t.

Finally, what could be the most interesting parallel between sodas and personal data monetization is their innocuous beginnings. 

The first fizzy drinks were marketed as health drinks. If you were ordering a Sprite occasionally to wash down your meal, then soft drinks weren’t going to send you to an early grave. But over the years, with growing prosperity and the convenience of technology like vending machines, people started guzzling unhealthy amounts of soda.

It’s much the same with the harvesting of personal data. Initially, receiving services for free in exchange for your data didn’t seem like a bad trade-off. But increasingly, consumers are beginning to realize they are getting the raw end of the deal. A tectonic shift has occurred and companies, especially Big Tech, need to make major changes to their approach. 

This is already happening in the world of alternative data – for instance, Suburbia tracks sales of consumer products like Sprite, with zero personal information. It shows there can be real value in non-personal data and it is how we harness it that matters.

Can today’s companies follow in the footsteps of the soda giants, and come up with a new formula for monetization? It might seem impossible, but Sprite shows lemon, lime and consumer benefits can win together. 

Data Monetization in a Pro-Privacy World

(First published on Dataconomy)

For over the last decade, some of the most successful companies on earth have made their riches by mining user data and selling it to advertisers. The big question is whether this will continue to be a sustainable business model with the ever-mounting scrutiny on data privacy and if not – what’s the alternative?

Many say the Cambridge Analytica scandal sparked a great data awakening by bringing to light the ways in which some companies were amassing and monetizing personal data about their users. As a result, Facebook was recently slapped with a record $5 billion fine and new privacy checks.

This isn’t a problem that is exclusive to the giants of Silicon Valley. In Europe, hefty fines have also recently been meted out to British Airways and Marriott for data breaches. As data protection complaints have doubled year-on-year, regulators will be getting tougher on companies to ensure their compliance with GDPR (General Data Protection Regulation).

Meanwhile, GDPR has driven a global movement as governments outside the EU, from Australia to Brazil, are set to introduce similar data protection regulations.

In addition, GDPR has helped to create greater awareness about data protection among the general public. The European Commission’s March 2019 Eurobarometer survey showed that about 67% of European citizens surveyed know what GDPR is.

The convergence of a compliance culture within organizations, stricter data privacy regulations globally, and consumers becoming more aware of their rights will continue to have a huge impact on businesses that profit from personal data, and even any business which collects it.

The situation demands urgency as the stakes have never been higher. According to a report by Gartner, by 2020, personal data will represent the largest area of privacy risk for 70% of organizations, up from 10% in 2018.

But better privacy for individuals doesn’t mean it’s bad for business. On the contrary, companies can use this opportunity to establish trust with customers while becoming more thoughtful and innovative about their approach to data monetization.

For many firms, data monetization has been inextricably linked with the personal data of their customers. However, they could be collecting, generating or archiving other types of non-personal data that could be valuable to certain end users. That is, the alternative data that may even be overlooked by the business generating it.

This data might be structured or unstructured, but new tools and technologies have made it easier to mine and process such data into insights. These insights could serve as timely intelligence to those in other sectors, like economists, analysts or investors looking to identify patterns and trends.

In fact, there are many use cases for such alternative data in the world of investing when every bit of timely information helps to gain an edge. This is where anonymized and aggregated data matters most and personally identifiable information has zero value. What economists and asset managers most want to know is how many soft drinks Coca Cola is selling across Europe this quarter, not whether John Doe bought a Coke.

The growing focus on privacy doesn’t mean data monetization has been taken off the table. Data will always be an important and valuable asset for any organization, but it needs to be harnessed with the full respect of individual rights to privacy. 

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.