With access to more data than ever before, companies have never been better positioned to adopt precision marketing methods and target the right customers at the right time. Emarsys, a digital marketing platform, enables its clients to collect, analyze, and act on a wide variety of data. From websites to mobile apps to emails, Emarsys’ customers can handle data from all its digital channels on a single, easy-to-use platform. Emarsys also makes sure that customers receive the highest quality data possible, making for smarter decisions and better business practices.

“We were close to the limits of our internal data warehouse, scalability-wise. We didn’t want to get to the point where we’d have to delete data or cancel projects. In Google Cloud we saw a platform that could scale with our ambitions and be optimized for AI and real-time solutions.”

—Levente Otti, Head of Data, Emarsys

Since launching as an email solutions provider in 2000, Emarsys has grown into the world’s largest independent digital marketing platform, with more than 2,500 clients worldwide and reaching more than 1.4 billion people. By 2016, the company felt that its existing data warehouse platform was close to its limits, affecting not just day-to-day operations but also important strategic goals.

“We were close to the limits of our internal data warehouse, scalability-wise. We didn’t want to get to the point where we’d have to delete data or cancel projects,” says Levente Otti, Head of Data at Emarsys. “In Google Cloud, we saw a platform that could scale with our ambitions and be optimized for AI and real-time solutions.”

Minimal maintenance, unlimited scale with Google Cloud

Digital marketing is a highly competitive environment. Emarsys works alongside big players with a huge market share on the one hand and smaller, specialist companies on the other. It has thrived by successfully combining the all-inclusive offerings of the former with the agility of the latter, constantly looking for ways to innovate and improve. In recent years, the company had started to feel that the ability to handle large quantities of data was no longer enough. The next challenge was speed. “We truly believe that in the future, everything will be done in real time, including data processing, analytics, and AI predictive models,” Levente says.

At the start of 2016, Emarsys’ existing data warehouse was a software-as-a-service solution running on-premises, which required hardware and software maintenance in order to keep up with the company’s growing appetite for data-heavy use cases such as prediction and analytics. The existing platform had proven its worth processing large amounts of data in batches, but its real-time capabilities were limited. Moreover, Emarsys had begun to experiment with AI technology, but found that its data warehouse couldn’t scale to accommodate some of the more resource-intensive processes, such as training the predictive models. The company decided that it needed a new, cloud-based data platform.

After evaluating some of the leading cloud providers, Emarsys chose Google Cloud for its mature AI capabilities and its ease of use. “With the other solutions, we still had to rent virtual machines and hardware and be responsible for maintenance. At the time, Google Cloud was the only provider that could take that management overhead away from us, while keeping customers accounted for on every query level,” Levente says.

To implement its new data platform, Emarsys teamed up with Google Cloud Partner Aliz. Over a series of meetings, workshops, and architecture reviews, Aliz helped Emarsys navigate the Google Cloud ecosystem to find the right products for the solution it was looking for. “Aliz really helped us set off in the right direction,” explains Levente.

With Google BigQuery, we can run queries which process terabytes of data, in seconds. We can also develop our own user-defined functions, incorporating Bayesian statistics into our predictive algorithms. That means we can take into account historical data, resulting in much more accurate predictions in a scalable way within seconds.”

—Levente Otti, Head of Data, Emarsys

Emarsys’ new data platform would actually be two: one platform for batch processing data and one for real-time analysis and interactions. Firstly, a proprietary publishing component gathered all the data points from Emarsys’ various channels including the website, mobile, emails, and custom events. With Cloud Pub/Sub and Cloud Dataflow, Emarsys transported and processed the data into BigQuery, which allows for further work and reviews that take into account errors or delayed events. After this, the data was exported to the main batch processing platform, which ran on BigQuery. For the real-time analytics, Emarsys used Cloud Bigtable to access data and Cloud Dataflow to pipeline it into the real-time platform, which could communicate with AI components or interaction components via an API to deliver real-time interactions with customers.

On top of the overall data infrastructure, Emarsys built a new AI platform with Google Cloud components. Training the predictive models had been an issue in the past due to the large number of resources required, so Emarsys chose to use Google Kubernetes Engine clusters, which can scale up and down on demand, without the need for hardware configuration or management. The trained models were held securely in Cloud Storage. From here, they were integrated with BigQuery for power and flexibility, allowing Emarsys to improve not just the speed of its AI predictions but also the quality.

“With Google BigQuery, we can run queries which process terabytes of data, in seconds,” shares Levente. “We can also develop our own user-defined functions incorporating Bayesian statistics into our predictive algorithms. That means we can take into account historical data, resulting in much more accurate predictions in a scalable way within seconds.”

Real-time insight, long-term satisfaction

Google Cloud enabled Emarsys to build a scalable data and AI platform that delivers powerful, actionable insights in real time. According to Levente, the company wanted to spend less time managing overload and more time considering how it should handle data. An immediate result of the new platform has been that data is now available in a scalable way, without hardware additions and management.

“With Google Cloud, we’ve been able to build a truly real-time data platform. The norm used to be daily batch processing of data. Now, if an event happens, marketing actions can be executed within seconds, and customers can react immediately. That makes us very competitive in our market.”

—Levente Otti, Head of Data, Emarsys

The clear and innovative pricing schemes of Google Cloud have also brought a new level of accountability to Emarsys’ costs in a way that wasn’t possible with its on-premises infrastructure. “Now that we only pay for what we use, we can assign costs to specific customers or queries, which has a huge impact on our pricing and product development strategies,” says Levente.

Thanks to the power of BigQuery and the scale at which it can handle data, Emarsys can now apply its analytics and AI tools to their full potential. “It’s very important to enable our clients to create the best possible experience for customers,” says Levente. At the same time, the company has cut its AI platform costs by 70% with Kubernetes while increasing scalability compared to the previous solution. The whole data platform was built to be scalable, and its first big test came during the retail peak of Black Friday, when it comfortably handled 250,000 events per second. “Perhaps the biggest impact on the business came with the real-time nature of the new platform,” says Levente.

“With Google Cloud, we’ve been able to build a truly real-time data platform,” he explains. “The norm used to be daily batch processing of data. Now, if an event happens, marketing actions can be executed within seconds, and customers can react immediately. That makes us very competitive in our market.”

Since implementing the new platform, Emarsys has continued to innovate with it and is about to release a new Real-Time Decision Framework, which will provide customers with even more real-time products and tools. The company continues to work with Aliz and Google Cloud, exploring other products such as Google BigQuery ML and TensorFlow to improve its AI processes. “We had a problem that we wanted to tackle now, and for us, Google Cloud was the best way of doing that,” says Levente. “But it was also about looking ahead. We felt that Google Cloud offered us the best way of future-proofing our platform.”

The ability to quickly introduce and evolve payment options for products or services is essential for businesses, as nearly 50% of consumers who can’t use a preferred payment method abandon their purchase. At the same time, gift cards, branded credit cards and rewards programs are critical tools that companies rely on to build more loyal and lasting customer relationships. With Highnote, companies have an all-in-one embedded platform to quickly create payment cards and wallets, offer innovative rewards programs and credit, and provide sustainable wage access. It is the first platform that allows enterprises to make card issuance an embedded capability of their product without creating an entirely new (and costly) organization.

Creating an exciting fintech future with Google Cloud

When thinking about building the industry’s first end-to-end embedded finance platform, we quickly realized Highnote would only be successful if it enabled companies to truly innovate and quickly roll out new programs. To do so, the platform would have to be built on scalable infrastructure capable of securely delivering services with speed and reliability while offering easy access to actionable Big Data analytics.

Working closely with the team at the Google for Startups Cloud Program, we successfully implemented Google Cloud as a versatile, future-proof foundation of our platform—and built Highnote from the ground up in just one year. Highnote’s GraphQL-based API platform reinvents the card issuance process. Utilizing the developer-friendly Highnote platform, product and engineering teams at digital enterprises of all sizes can easily and efficiently embed virtual and physical payment cards (commercial and consumer prepaid, debit, credit, and charge), ledger, and wallet capabilities into their existing products. This creates compelling value while growing revenue and building a unique and differentiated brand.

We leverage Cloud Spanner, BigQuery, and Google Kubernetes Engine (GKE) to create a unified and highly secure PCI DSS-compliant platform with GraphQL APIs that provide rapid and flexible money transfers. This gives us a reliable platform to deliver and test customer experiences, respond to outcomes, and make better business decisions. Powered by Google Cloud, our data models and application domains are architected to support configurations and customizations that unlock a diverse set of new use cases across industries, including retail, travel, logistics, healthcare, and sustainable wage access programs.

We are especially proud to highlight our enablement of sustainable wage access, as this program helps the 50% of Americans living paycheck to paycheck. Embedding this program within payroll systems provides a viable alternative to payday lenders who often charge exorbitant fees and interest rates. In real world terms, this means Highnote helps people access earned wages before payday at no cost.

The other customer we just went live with was Tillful, and their Tillful card helps small businesses build their business credit. This program will help new and emerging businesses as well as underrepresented owners of small businesses by making the credit ecosystem accessible. Highnote’s platform is designed to support multiple use cases across many industries. For example, we also help the trucking and logistics companies to develop fleet and fuel cards, and spend management companies who are looking to uplevel offerings.

Delivering high-performance transactions with Cloud Spanner

Building one of the world’s most modern card platforms would not have been possible without Cloud Spanner. We needed a solution that would keep our massive petabyte databases from buckling and more securely deliver data anywhere in the U.S. Cloud Spanner does all this and more, as it routinely connects purchases from millions of customers to tens of thousands of vendors. We also wanted to reduce overhead by 80% by eliminating manual sharding, partitioning, and optimization of data. These processes are automatic with Cloud Spanner so we can operate at maximum efficiency.

We specifically selected Cloud Spanner as our distributed SQL database management and storage solution because of its outstanding availability, zero plan maintenance downtime, security certifications, and the highest consistency guarantees of any scale-out database. We continue to optimally scale without any downtime or compromises to the integrity or security of our data. This is key for us because we can address unexpected spikes, long-term growth, and new services without costly rearchitecting.

Highnote is designed to perform over billions of transactions on Cloud Spanner, and the average latency of less than 250 ms is a testament to the robustness of Google Cloud services.

Enabling actionable customer insights at scale

BigQuery is another key Google Cloud solution that we rely on to deliver deep insights and visibility for our customers on a highly secure and scalable platform. When building Highnote, we knew we needed a cost-effective solution that excelled at data analytics. This is particularly critical for accurately measuring the performance—whether profitability or efficacy—of any program or card.

Using BigQuery, we successfully run analytics at scale with as much as a 34% lower three-year TCO than cloud data warehouse alternatives. Over the past year, BigQuery has enabled our customers to unlock data-rich capabilities with a ledger that tracks money in real time and serves up complete debit and credit entries for every event across their accounts. Companies also access real time balances for revenue, fees, customer accounts, and available funds management without complicated spreadsheets.

To quickly and efficiently roll out Highnote to our customers, we needed a simple way to automatically deploy, scale, and manage Kubernetes. When selecting a Kubernetes management tool, our top priorities were rapidly spinning up and securely scaling across multiple sites. As part of Google Cloud’s expansive ecosystem, Google Kubernetes Engine (GKE) was the top choice due to seamless and automatic Kubernetes scaling and management.

We quickly got off the ground with single-click clusters and scaled up by using the high-availability control plane—including multi-zonal and regional clusters—to easily accommodate multiple active-active regions (which other solutions cannot do). As an embedded finance platform, stringent security protocols were obviously a key consideration for us. GKE is secure by default and runs routine vulnerability scans of container images and data encryption. Further security assistance was provided by Google Cloud partners 66degrees and DoiT International to help us rapidly validate VPC PCI compliance and ensure the uninterrupted performance of thousands of transactions per second.

Winning in fintech with Google for Startups

Building the industry’s first end-to-end embedded finance platform would have been extremely challenging without the extensive Google Cloud support. By working closely with our Startups team and Google partners, we had access to Google Cloud services to more easily validate VPC PCI compliance and address most issues before we exited stealth. Their responsiveness is incredible and stands out compared to support services we’ve seen from other technology providers.

Our participation in the Google for Startups Cloud program has been instrumental to our success. With Google Cloud, we are making embedded payments accessible to our customers without a big budget price tag. By doing so, we help unleash the creativity of emerging enterprises by enabling them to innovate with payment services and rewards programs to reach new markets and customers. If companies can dream, we can enable them to realize it on Highnote. Our platform really is that flexible. We’re excited where we can go and grow with Google Cloud.

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