Innovation Heroes: inspiring ideas from two ambitious food & beverage businesses
Talk of the digital economy is nothing new. But the pandemic may have taken us past the tipping point. As McKinsey found, businesses who were the first to experiment with new technologies and invested more in digital capabilities earlier fared better during the crisis.
This has forced a global mindset shift on the strategic importance of technology an.d accelerated digital adoption by an estimated six years or more. But as businesses in virtually every vertical scramble to digitalize, the competition is heating up. Not only is the playing field becoming increasingly global, the lines between industry sectors are also blurring. Competition can suddenly spring up from what may have been previously considered an unrelated sector.
To stay competitive, digital businesses must be constantly innovating and adapting – seeking out ways to better serve customers at scale while keeping their operations as streamlined as possible. This relentless pressure has pushed them to the forefront of the innovation wave, making them ideal candidates for our Innovation Heroes series.
In this edition, we are spotlighting five of our fast-growing merchant partners. They have diverse business models, ranging from ridesharing to ticket-booking. But they all have a few things in common when it comes to dealing with the challenges of scaling.
We’ve all heard the “data is the new oil” metaphor. But just like oil, the crude version pulled straight from the ground is of little use. We need to refine it to turn raw data into business fuel. That’s why the data analytics market size is estimated to hit $274.3 billion by 2022, and why recent surveys found that 67% of small businesses are spending over $10,000 a year on analytics.
Proper analytics is key for ensuring that customer insights remain the guiding star of the business. This can sometimes lead to unexpected innovations.
They attribute a lot of their growth to closely tracking all their data, which helps them make quicker decisions about where to invest. One example is in making the payment experience as frictionless as possible.
One of the things I appreciate most about Adyen is that you can pull a report on almost anything. The fact that we get all data in the same format means that we can be data-driven in our approach and much more agile than if we had separate reporting for different payment methods and markets.
But while this has helped them scale, it also had an unexpected, though welcome, effect – turning them into an insights engine for the entire industry. They can now look beyond simple book sales, analyzing engagement via completion rates and further segmenting subscribers.
As CEO Niclas Sandin notes, that’s “pretty cool.”
Mobile-focused open ticketing platform SeatGeek often has months where they process over $100 million in tickets. That can equate to thousands of ticketing payments a second. And every delay or failed transaction is a hit to the customers’ experience and the SeatGeek brand.
SeatGeek payments manager Shawn Kelly says that switching to Aden was like “night and day,” noting that they can now pull data faster, without needing to first go through their data warehouse. The result? An improved experience for any SeatGeek customer – whether an enterprise client asking about authorization rates or an individual ticket buyer needing a refund.
This shouldn’t be a surprise. After all, every payment is essentially a customer. Their payment preferences and buying behavior can thus be major assets, which can be used to increase conversion and authorization rates as well as customer lifetime value. Breaking things down by channel, device, location, average spend, preferred payment methods, and decline reasons are just a few ways businesses can mine these assets for valuable insights.
This applies to both B2C and B2B. For the former, it can give you ideas on how to incentivize recurring purchases or build loyalty programs. And for the latter, it can provide guidance on which customers to invest more in, for example through dedicated support or discounts.
European ride-sharing app Bolt, the world’s fastest growing platform for taxi bookings, understands just how valuable payment data can be. For them, payments data provides interesting customer insights. With this, they can explore customer segments and their behaviors, then implement various tests to keep improving the customer experience. They also use transaction data, in combination with other data types, to predict when and where users will book a taxi.
In a market where people use multiple ride-sharing apps and are quick to switch, this laser focus on customer experience is vital. But to collect all this data, they must also make the payment experience as seamless as possible. We’ve helped them do that using our tokenization feature to enable easy one-click recurring payments.
We like to implement options that don’t require customer registration and improve the flow for people without a Bolt account. Apple Pay and Google Pay™ for example. Adyen’s tokenization tooling means that payments for mobile wallets can be made on a recurring basis, and when riders authenticate once, the info is stored.
In digital economies, the network effect usually means that the first one to reach sufficient scale wins. But amid this intense race, companies must be ever mindful of burgeoning costs, which risk jeopardizing their efforts if not carefully controlled.
So, it’s no wonder that companies are increasingly harnessing the tools of intelligent automation to keep their operations streamlined. Prior to the pandemic, a survey by Deloitte found that 58% of surveyed companies had started their automation journey, compared to just 29% in 2018. The current figure is no doubt much higher.
One way companies are doing this is by leveraging their technology partners.
Athlinks is a social networking website for competitive endurance athletes. They host the most comprehensive database of endurance race results and events in the world, and allow users to register and pay for these events.
Because these events take place all around the world, they must adapt to many different local payment landscapes. This can lead to inefficiencies. For instance, in Mexico, Athlinks chargeback rates once hit 24%. On top of that, they also had to negotiate with new payments-related vendors and partners in every market, slowing down their capacity to scale.
We helped Athlinks optimize their operations by becoming their one-stop payments solutions partner, working with them on risk analysis and boosting authorization rates. Together, we managed to reduce their chargeback rates in Mexico to 1% and saved them the trouble of having to negotiate with local vendors and partners.
Adyen helps us technically because we get to work with them as an all-in-one stop for payments. It really is a plug-and-play option.
Supporting McKinsey’s assertion that businesses who got a head start in the digitization and automation game came out ahead is Colombian delivery app Rappi. They invested in automation and machine learning features before the pandemic, such as enabling their Mexican users to open a digital account via smartphone within 5 minutes. They realized early on that their team would be unable to perform these processes manually considering the pace of their growth.
So, when the pandemic struck, Rappi reaped the rewards. They saw increased order values and volumes, as well as higher cross-selling among their different verticals. The lesson? It pays to be prepared.
These five thriving digital businesses have shown the importance of being able to effectively analyze their data and simplifying their operations to achieve scale. If you’re operating in a similar vertical you should ask yourself two big questions:
We can help you tackle both. We give you real-time visibility on payments at a granular level, from decline reasons and authorization to risk settings and reconciliation. Plus, our platform also uses machine learning to optimize your payments flow and help increase your revenue. Adyen automatically tests and runs multiple optimizations for every transaction, learning in real time.
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