In Freefall: COVID-19 and Retail Sales

This article is translated and republished from the original article in German by Inga Fechner, economist at ING.

Chart of the Week

Numerous restrictions have been in place for over a week to reduce the spread of COVID-19. Schools and stores are closed. Places that tend to be bustling with people, especially when the weather is pleasant, are now eerily empty. It is no surprise that sales in the retail sector have plummeted, as our chart of the week shows.

Daily turnover in Germany and Austria (% change compared to the previous week)

Source: Suburbia, ING Economic & Financial Analysis

While extensive restrictions have been in effect in Austria since March 16, which were announced on March 13, the German government took a little longer to act. Yet, at the same time, public life was grinding to a halt. People’s increasing adoption of social distancing is clearly evident in retail sales since the weekend of 13th March, as we determined from data from Suburbia. Turnover across restaurants, hotels and leisure venues dramatically dropped over the weekend, compared to the previous weekend. 

The restrictions are still in effect, at least until Easter, and will continue to be a problem for numerous economic sectors. Fiscal support measures by governments and central banks are an important step in cushioning the impact of the slump. However, the impact cannot be completely reversed. At least for this year, we will see negative growth for the first time since the financial crisis for many economies.  

Data Shows that Pandemic Compelled Businesses to Act Faster Than the Government

  • Businesses more proactive than governments in Europe
  • Public behaviour no different in hardest hit regions in Germany and the Netherlands

The COVID-19 outbreak has thrown much of Europe into lockdown. Germany and the Netherlands have shut bars, while restaurants are allowed to stay open only for takeout and delivery services.

In recent days, both countries have also tightened rules on social interaction, banning groups of more than two or three people for gathering. It has been two months since the first confirmed case surfaced in Germany and nearly a month since the Netherlands’ first case – so have these moves come too late?

While this is up for debate among epidemiologists and public health policy experts, we analysed our CPG data* to determine two things: business response and public response to the crisis in Germany and the Netherlands over the first quarter. As a proxy for public behaviour, we looked at key indicators such as the number of transactions and sales volume at thousands of F&B outlets across these two countries.

Store closures preceded government action

In both countries, a plunge in open outlets occurred just days before the government introduced tougher measures to combat the spread of the virus, and mandated the closure of clubs and bars.

It seems that many businesses had already taken the initiative to close their doors before any government order. In Germany, voluntary closure of restaurants increased a few days earlier than in the Netherlands. On March 9, when the first COVID-19 deaths in Germany were reported, one-third fewer restaurants remained open compared to the Q1 weekly average.

Restaurants probably decided to shut down since more customers were staying home and shunning busy places in the wake of growing cases. Or they might have found it hard to enforce social distancing by seating diners at least 1.5 meters (5 feet) apart. Regardless of the reason, we can see from total sales volume below that this was a sudden, rather than gradual, dip in activity. It seems the rapidly escalating outbreak had little impact on public life – people were still going out to eat and drink as usual – but this was brought to a virtual standstill on the weekend of March 14.

We looked at sales volume in regions that were hit hardest by the pandemic – Germany’s North-Rhine Westphalia and the Netherlands’ Noord-Brabant province – to see if activity there differed from activity at a national level. But it appears that business and public behaviour in those regions were not significantly different from the rest of the nation, despite more stringent regulations being introduced there first.

In summary, the data demonstrates that even when the pandemic strikes close to home, it tends to be business as usual during the early days of the outbreak. However, businesses felt the impact earlier and acted quicker than governments did. While efforts to curb social interactions at a state or regional level can change public behaviour, not everyone will comply with the rules until there is a total shutdown.

About our data:
Suburbia partners with companies in the payments and retail industries to create data sets that track anonymized consumer purchases across Europe, delivering a daily view into some of the world’s biggest consumer brands. For insights on consumer packaged goods (CPG) trends, Suburbia’s data set covers sales in over 14,000 on-trade channels across six countries in Europe.

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

Do French people love their lovers or mothers more?

France is renowned as a nation of romantics. So with Valentine’s Day around the corner, we wanted to see if this reputation is justified. 

We looked into our luxury cosmetics and fragrances dataset* to compare sales in the periods leading up to Valentine’s Day, Mother’s Day and Father’s Day. Outside of Christmas, these are all historically the most popular times of year for fragrance purchases.

When surveyed before Valentine’s Day back in 2016, 69% of French people said they weren’t even planning to celebrate it. But it appears attitudes have shifted since then… 

Our data reveals that French people spend more on their significant others than they do on their mothers or fathers. The difference isn’t marginal either – Valentine’s Day sales are a whopping 39% higher than Mother’s Day sales! 

And while news reports show Father’s Day spending continues to trail far behind Mother’s Day, our data shows just the opposite with 34% higher sales for the former. 

What’s interesting is that Valentine’s Day sales have steadily increased year on year, while sales for the other two occasions have experienced dips in previous years. 

Of course, there could be other reasons to explain these gaps. People may be splashing out on flowers or a nice evening out instead. Buying habits are also shifting as millennials increasingly seek experiential gifts for Mom like spa treatments, according to retail consulting firm Unity Marketing

As for Valentine’s Day, we expect the boom in fragrance sales around Valentine’s Day to continue. A perfume may not be as enduring as the memory of an experience – but at least it lasts longer than flowers and candy!

About our data:

Suburbia partners with companies in the payments and retail industries to create data sets that track anonymized consumer purchases across Europe, delivering a daily view into some of the world’s biggest consumer brands. For insights on luxury cosmetics and fragrances trends, Suburbia’s data set covers sales in over 130 retail outlets in France.