Hendrik Brackmann, Director of Data Science and Analytics at Tide and Alex James, EMEA Senior Director for Customer Success at Fivetran, joined Peter Walker, Editor of FStech, on the FStech Podcast. They chatted about the impact of the modern data stack on FinTech and how having a full view of customer activity and data is critical to marketing success and machine learning initiatives.
The Impact of the Pandemic on Data
The pandemic has impacted businesses in a number of ways, from the amount and type of data they generate to how they use it. A few notable challenges include:
Disseminating information. As Brakmann sees it, the work-from-home move has had the biggest impact and it required new methods of disseminating information internally.
Reestablishing benchmarks. The pandemic was a shock to Tide’s customers, mainly businesses in the UK, and it impacted behavior. “We collect a lot of data from our customers, but we were challenged to re-establish benchmarks after such a big shift in behavior,” shares Brakmann. “We needed to find a way to adjust for this change.”
Speeding up data access. As online traffic increases, businesses need to get their hands on data more quickly. Those that focused on effective data access before the pandemic were at an advantage, as James sees it: “Having all of their data in one place is helping our customers make it through this pandemic – companies that have all of their data in their warehouse don’t have to worry about faster data access.”
Taking Advantage of the Modern Data Stack as a FinTech Business
It wasn’t too long ago that financial services companies would have everything on prem. Now, many modern financial services companies operate completely online. With all of those channels and sources centralised into a warehouse, Tide doesn’t have to worry about data silos. But even when all your apps, databases and more live in the cloud, data silos can still exist, and it can be difficult to wrangle that data and centralise it into a warehouse.
While there are legacy tools that allow you to get your data from source to destination, they’re difficult to build and maintain. “That’s basically why Fivetran exists,” explains James. “Our customers move quickly and need to be able to add new tools or build new features. With Fivetran, that data can be synced to your warehouse with just a few clicks so you can focus on the data aspect rather than building and maintaining pipelines.”
As a Fivetran customer, Tide has all of its data automatically syncing into its data warehouse, which has been extremely helpful for the company, according to Brakmann:
One of the things we find really useful about Fivetran is the point-and-click integration. Fivetran has been really helpful in reducing our end-to-end delivery times for getting data from source to insights in almost no time.
Being a cloud-native bank and having all of its data in a warehouse has made it easier for Tide to adapt to changes, capture data and take action on insights. “All of our customers’ actions exist in a trackable channel and we can act on the information much more easily,” explains Brakmann. “Showing dynamic content online is much easier than doing so in a branch, for instance.”
Using Customer Data to Drive Business Impact
Prior to a modern data stack, if a person wanted a report, they would have to think about what data they needed to build the report and wait for the engineering teams to build the pipeline and access the data. “Businesses are bringing all of their data into a warehouse because storage is so cheap now,” says James. “Analysts can build reports with multiple data sets without relying on a lengthy process to request a field from a database from a siloed system. Just give the analysts the data, and they can build the reports that give you the insights you need.”
Tide is a perfect example of a business bringing its data into the warehouse and letting analysts build the reports that the business needs to remain competitive and adapt. Brakmann shares a few exciting use cases below:
Optimising marketing spend. With a modern data stack, Tide has been able to connect the customer journey from acquisition to retention to lifetime value (LTV). Brakmann shares:
We’re optimising our marketing spend in a differentiated way, looking not only at acquisition costs but moving more towards an ROI model. It is very exciting.
Implementing customer feedback. Tide is connecting customer feedback to the user journey, allowing the business to pinpoint where issues exist in the product and understand the benefit of resolving these issues.
Machine learning. Having large amounts of centralised customer data means the business can begin implementing machine learning use cases. “This quarter we’re focusing on using our customer data to create something that can be used for real-time decisions. Having a tool like Fivetran allows us to do this.”
Visit our Marketing Analytics Resource Center to learn more about the analytical benefits of a modern data stack and check the Tide Engineering Team Blog to learn more from the Tide team. If you’d like to listen to the full podcast, you can find it here.