Suburbia launches luxury cosmetics dataset for investment insights

29 October 2019, Amsterdam – Suburbia, a technology company specializing in alternative data solutions, has introduced its second offering that leverages millions of anonymized transactions to predict the performance of luxury brands in the beauty and personal care space.

Suburbia has partnered with companies in the payments ecosystem to collect receipt line-level data from multiple sources. This unique dataset tracks sales of luxury cosmetics and fragrances in France, the largest market for this segment in Europe and the fourth largest in the world, with a total value of three billion euros. 

“France is not just a large market for the world’s biggest luxury companies and beauty brands, it is also a trendsetter and tastemaker,” said Hamza Khan, CEO of Suburbia. “By collecting accurate sales across the country, our product is a powerhouse for what is popular in France, and a strong indicator of what will be popular globally.”

The new dataset delivers daily signals on publicly listed and private companies, including key players in the industry such as L’Óréal Luxe, Coty Inc., Estée Lauder Companies and LVMH. It tracks over 100 brands including Dior, Chanel, Hermès, Hugo Boss, Kenzo, Lancôme and YSL. The data product has been built specifically for investors who want granular insights into how these companies’ main revenue drivers are performing, whether by brand, category or product.

According to a recent report, among all luxury goods sectors, cosmetics and fragrances have witnessed the highest sales growth.* The market is expected to grow annually by 3.3% (CAGR 2019-2023).**

Suburbia’s proprietary technology is capable of processing millions of consumer purchases. No personal information is ever used or shared in the process. This data is updated on a daily basis with a one-day lag, so investors can get up-to-date insights for making decisions faster.

Other highlights of this product include:

  • Ticker mapping to easily see performance of publicly traded companies over time
  • Granularity such as EAN, brand name, item pricing, product category, basket composition, geography and time of transaction. Anonymized merchant ID is provided in order to compare same-store or like-for-like sales.
  • Historical coverage, with over three years of data available for backtesting

*  Deloitte, Global Powers of Luxury Goods, April 2019
** Statista, 2019

Suburbia launches European consumer transaction data solution for investment community

19 September 2019, Amsterdam – Suburbia, a technology company specializing in alternative data solutions, today launched its first-ever offering that leverages millions of anonymized transactions across Europe to provide predictive insights into consumer goods companies.

A multi-source platform with granular insights into brand performance, it delivers daily signals on over a hundred publicly listed and large private companies. This data product has been built specifically for hedge funds, asset managers and other institutional investors to generate alpha and manage risk.

“Investors have long been tapping into transactional data to anticipate trends and consumer behavior,” said Hamza Khan, CEO, Suburbia. “But we realized most of the existing data out there is generated by a panel of users which could lead to an opt-in bias and less accuracy. In addition, this data is much harder to come by in Europe because it’s such a diverse and fragmented landscape – every country has its preferred payment methods. We believe our unique approach has resulted in the industry’s most actionable dataset.”

Suburbia’s proprietary technology is capable of processing millions of consumer purchases from thousands of hospitality and retail channels across Europe, with a strong focus on Germany and the Benelux. No personal information is ever used or shared in the process. This data is updated on a daily basis so investors can get up-to-date insights for making decisions faster.

Other highlights of this product include:

  • Ticker mapping to easily see performance of publicly traded consumer packaged goods (CPG) companies over time
  • Granularity such as product details, item pricing, basket composition, geography and time of transaction
  • Historical coverage, with over two years of data available for backtesting

How can Facebook solve its privacy crisis? Just ask Otis Elevator

You’d be hard-pressed to think of two terms that have captured the tech zeitgeist more than “big data” and “data privacy”. So what do they have to do with a 160-year-old machine?

Firstly, you might ride this humble box several times a day without realizing its significant contribution to urban life. The elevator was a transformative technology that ushered in the era of the modern city and made skyscrapers possible. 

Like any technology, its evolution over time has had ups and downs, but the advancements made in its history can teach us some important things:

  1. Focus on building trust through action, not communication.

When the first passenger elevators were introduced in the early-to-mid-nineteenth century, the rate of adoption was slow. After all, there was always the risk a cable would snap, plunging the elevator and all its occupants to their possible deaths. “Thanks, but I’ll take the stairs,” was likely the common rejoinder at the time.

The makers of elevators could have dismissed them as one-off incidents, or showed how statistically rare elevator-related injuries and fatalities were. But it wouldn’t have mattered as people simply didn’t feel safe getting in there.

What really changed people’s perception was a critical safety feature that was first demonstrated by Elisha Otis at a world’s fair in New York. As detailed in the book Lifted: A Cultural History of the Elevator, the American inventor stood on a platform high above the audience when the only rope holding it up was cut with an ax on his orders. The safety mechanism kicked in immediately, preventing the platform from plummeting to the ground. 

After this, public confidence in elevators soared, particularly in Otis’ safety elevators. He became inundated with orders, which doubled every year. 

It’s a crucial lesson to social media and tech companies that the elevator pitch for their technology matters less than than their ‘elevator moment’. Most will pay lip service to the notion of privacy, without demonstrating the tangible and practical steps they’re taking to ensure the safety of users’ data. Any organization dealing with personal data needs to plan for worst case scenarios and prepare for them appropriately by having safeguards in place. Only then can they truly protect individual privacy and earn consumer trust. 

2. What seems like an obstacle now will be a pivotal opportunity in hindsight.

When GDPR (General Data Protection Regulation) was first introduced, many companies viewed it as a hurdle to overcome. How could they now monetize their data or personalize their marketing? 

It helps to take a step back into a time when elevators were still manually controlled by an operator. Sitting in an elevator to press buttons all day was an actual paying job. Then, in the 1950s came automatic elevators that didn’t need human operators, though there was just one little problem: People hated them. 

As a professor of architectural history tells The Globe and Mail, there are “stories of people walking into elevators and walking back out”. In fact, it took a good part of a decade for the technology to become commonplace and for people to get used to it.

It seems laughable now, the idea that people didn’t see it as their job to push a button and simply felt uncomfortable doing so. But aren’t we going to also look back at this era, when companies regard privacy regulations as a demanding obstacle, with incredulity? 

After all, GDPR and the growing wave of legislation worldwide should be seen as a watershed moment for businesses. This is a turning point for marketers to stop microtargeting with personal data when there is a wealth of other types of data at their disposal that can be used to generate relevant and effective content. 

There are many ways to personalize marketing without the use of personal data. For instance, there is what GDPR categorizes as pseudonymous data (data that can’t be used to directly identify an individual) like the customer’s local weather. Is it more relevant for a brand to bombard a customer with ads for umbrellas because he viewed them once, or to offer an umbrella to everyone living within a particular area on a rainy day? Does a brand have to know about your allergies, or can it use available pollen count data by geographic region?

Companies simply need to ‘push the button’ and stop seeing compliance as a chore. Instead, they need to embrace data privacy as a valuable opportunity to build trust and use non-personal data more creatively. 

3. Fast and reliable data makes it possible to predict things before they happen.

The elevator has come a pretty long way since Otis brought it into the mainstream. They have not only gotten better, faster, safer – but also a lot smarter. 

On the surface, elevators may not seem to have changed much over the last decades. In reality, the technology that keeps them moving smoothly is cutting-edge. AI and real-time data are being used by major elevator manufacturers for predictive maintenance – so they can spot problems before they arise and better anticipate breakdowns. For instance, ThyssenKrupp’s elevators are connected to the cloud, collecting data from its sensors, and transforming that data into actionable analytics. 

KONE has a similar system that incorporates IBM’s Watson IoT. Using data points transmitted by elevators across the world, KONE can glean historic failure rates of different elevator parts and the preceding conditions. For example, a temperature reading that’s slightly above normal could be a sign of engine trouble, but the system can also note if it’s a hot day, which could be a factor too. Its forecasting also improves as more data is fed into the model. 

Similarly, faster access to better data is needed to make critical business or investment decisions. Relying on traditional sources of information like earnings, filings and economic reports is akin to elevator manufacturers depending on written maintenance records. 

But why wait 90 days for a quarterly report when one can access a steady stream of intelligent data? New sources of information, or what we call alternative data, are constantly generated around us and investment managers can leverage them to get an unprecedented level of transparency into company performance on a near real-time basis.

From anonymized transaction data to price trackers, these can be used to generate predictive insights so proactive decisions can be made, instead of mere reactions to events as they occur. For investors, that can help them forecast market movements and trends, and manage risk. 

To sum it up, businesses and investors need to use data and privacy as the vehicle of change, much as the elevator was once upon a time.


Suburbia first and only Dutch startup selected for Tokyo accelerator program

Suburbia is the first Dutch startup ever to be selected for Fintech Business Camp Tokyo, an accelerator program for young fintechs. The two-month program, which will kick off in October, is run by the office of the mayor of Tokyo with Accenture Japan.

“We feel really proud and honored to be the first and only Dutch startup picked for this program,” said Hamza Khan, CEO and founder of Suburbia. “Standing out in a crowded field only proves that our technology is truly innovative and highly scalable – what we’ve built in Europe can work just as well in Asia-Pacific or the Americas… or anywhere!”

Suburbia was selected by the Tokyo Metropolitan Government (TMG) from a pool of over 120 applicants located in 29 countries, alongside 11 other startups. They were reviewed and chosen based on their innovative technologies and business models “which do not yet have a presence in Japan”. 

The initiative, first launched in 2017, is part of the Japanese government’s four-year campaign to revitalize Tokyo’s financial sector and cement the city’s status as a global financial hub. TMG considers fintech a key element in achieving its goals. The program aims to provide startups with access to some of the nation’s leading companies and support them with their entry into the market. 

Startups that have been accepted into the program are provided with support in localization, mentoring from top Japanese banks, and networking and business matchmaking opportunities. Three of the 19 foreign companies that have participated in the program in the past two years now have a footprint in Japan.

As part of the program, Suburbia will be going to Japan to meet with local companies and investors. This will culminate with a pitch in November where the company will present a business plan developed during the course of the program.

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. 

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. 

Smells like Teen Spirit: How ’18 for Data was like ’91 for Rock and 3 key points for today

An industry dominated by a small number of old players, an audience longing for better and the upstarts who broke through big.

Yes, this describes 2018 in data, where traditional heavyweights Thomson Reuters and Bloomberg saw an increasing field of disruptors, but it also reflects, and offers a lot of lessons from, the music industry in 1991.

An industry dominated by a small number of old players, an audience longing for better and the upstarts who broke through big.  

For a quick and opinionated history, the friendly vibes of disco and psych-folk in the 70’s were eroded by the W shaped recession, stagflation and an international oil crisis, paving the way for a bleaker, heavier turn in both society and music.   

Metallica released their first studio record, Kill ’em All in 1983, but became cultural mastheads with the thrash metal darkness of Master of Puppets in 1986, with the two albums selling a combined 9 million copies in the US alone.  This heaviness was supplemented by the second wave of hair metal bands, notably Guns N’ Roses, whose Appetite for Destruction, released in ’87, sold  18 million copies domestically.  The rock incumbents were established.

The next few years saw greater bombast, and bigger sales (Metallica’s self titled 1991 record remains their best selling, with almost 17m copies sold in the US), but a waning connection with listeners.  Given the choice between heavy metal and hair metal, younger rock fans began to feel the apathy which would define Generation X.  Then came KC.

Alternative Rock Conquers the World

Little known label Sub Pop Records in Seattle released Nirvana’s first record, Bleach, in 1989 to middling success.  But it was the band’s 1991 release Nevermind on David Geffen’s DGC records which changed the face of 90’s rock, ushering in a raw sound stripped of pretense and even of meaning.  Gone were the costumes, the makeup and the arena theatrics, in their place an urgent, hazy sound, inviting the listener to define their own meaning.  This was alternative rock.

What is Alternative data? Alternative data is defined as data collected from new sources such as satellites or sensors, or used in new ways

And readers can now probably see the parallels.  Alternative data, defined as data collected from new sources such as satellites or sensors, or used in new ways, has been around for a long time, picking up pace in the middle of the last decade.  But 2018 was its major label moment, as NASDAQ purchased alternative data pioneer Quandl and almost 400 alternative data providers competed in the space.  

Indeed, Quandl’s Alternative Data Conference in February 2019, which Suburbia will be attending, is titled “The race to be first is over”.  The question is what comes next, and I believe the music industry has three important lessons for everyone.

1. Expect the Majors to Muscle in

Seattle post-Nirvana saw a flood of attention from major record labels, giving greater attention to bands like Alice in Chains or Pearl Jam.  Others were met with less commercial success, like Nirvana precursors the Melvins or Tad. Similarly, Quandl was not the only alternative data provider to be purchased, with 7Park being bought by Vista Equity Partners in December.

In theory this influx of capital benefits everyone, by giving smaller players more resources, the bigger players more market control, and end users easier access to new platforms.  

In reality, I see upsides and downsides.  The influx of capital has only just begun, and by 2020 expect smart investments to bring today’s alternative data startups to the next level of success.  On the downside, there will be major players who overpay to establish presence in a crowded market.

But don’t worry, the incumbents have the money to lose and are not going anywhere – Guns N’ Roses still sell out stadiums, and Bloomberg and Thomson Reuters’ Eikon will remain Wall Street fixtures.  They just won’t have the field to themselves anymore.

2. New players will be distributed globally

The Pacific Northwest is considered the birthplace of grunge but by no means its only home.  New York’s Gumball came from the opposite coast, The Smashing Pumpkins hailed from Illinois, Bush from across the Atlantic in London and Silverchair  across the Pacfic flew the grunge flag in Australia.    

Alternative data has similarly been an East Coast play, with Toronoto’s Quandl focusing on the hedge fund crowd in Connecticut and the banks in New York.  But there is a growing field internationally, with Eagle Alpha, one of the industry’s earliest and most influential players, based in Ireland and Suburbia headquartered in Amsterdam.

Asia remains under-served, with some firms including IHS Markit having a presence, but the heavy hand of government-linked corporations creates headwinds for independent measurements and verification.   Regardless, it is a matter of time before alternative data users and suppliers are truly global.

3. Nothing will be the same

Grunge as a genre began to fade by the mid-90’s, with Nirvana’s last album In Utero released in 1993 and the band dissolving the next year.  Mother Love Bone’s tenure was even shorter, breaking apart before their first album was released.  Even bands who stayed together changed their sound, with Pearl Jam’s 1996 album No Code turning towards ballads and garage rock.


But the mark of grunge was inedible in music, either directly as Nirvana drummer Dave Grohl’s next band Foo Fighters owned radio rock airways in the mid-90’s, indirectly with Marilyn Manson, getting input on his 1998 record Mechanical Animals from Billy Corgan of the Smashing Pumpkins, and passively in trending pop acts like Halsey, photographed in Nirvana t-shirts and whose 2018 track New Americana mentions Nirvana directly.

Outside of music, filmmaker Gus Van Sant’s mumbling cast were the outsiders raised on grunge, most clearly in his semi-biopic Last Days.  In fashion and art, the band’s iconic designs from the yellow smiley face to the swimming baby have been emulated from high fashion brand Lad Musician in Japan to TV’s The Simpsons, and broadly the dividing line between the mainstream and the underground has been blurred.

This last point is crucial when it comes to data.  Much like David Geffen’s major label DGC traded with tiny Sub Pop records, traditional releases like government reports or company earnings will become enriched with alternative data, and alternative data suppliers will find themselves collaborating with traditional sources.

Data driven decisions will no longer be the enclave of hedge funds who can afford multiple Bloomberg terminals, or large financial institutions purchasing reports from consultancies.  

In a few years the influence of new data will be pervasive across mediums, roles and industries, leading to more accurate measurements and better decisions for everyone.  Add that to the enduring legacy of Nirvana.