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Seeking success in Financial Services? Learn why data maturity is key.

Julia Rasmus
August 16, 20236 min read
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The Financial Services sector in EMEA faces many challenges. Safeguarding data, global compliance, regulatory mazes, and that’s just the start. But perhaps the greatest – and most underestimated – hurdle for the Financial Services industry is how to stand out in what’s quickly becoming a crowded and highly competitive marketplace. 

The solution? Building more mature data practices. 

Data maturity is about fostering a culture that combines the power of tools and practices to support accurate, data-driven decisions within your business. It is the decision not to listen to the loudest voice in the room or go with gut instinct, but instead, find a way to work with your data to inform your future strategies. 

Being a data-mature organization is no longer a nice-to-be – it’s now more necessary than ever for survival and success. In this blog, we’ll cover three key benefits of data maturity within the Financial Services industry, including practical tips from the experts in our webinar on how to achieve them. 

Let's dive in.

Now available on-demand: Driving Success with Mature Data Practices: Insights from Financial Services Leaders

Learn from leading FinTech experts in the UK and EU how to leverage data to deliver customer-centric products and successful growth strategies across Product, Engineering, and Marketing.

Watch Now

Elevating the customer experience with data 

Understanding your customers is the first step towards building products and digital services that resonate with their needs. By leveraging product analytics, Financial Services teams can gain deeper insights into customer behavior, including their preferences and pain points. 

This is particularly important for Baha Sahin, Engineering Director at Checkout. Checkout is a payment processing platform, so fraud is always front and center as a big problem. 

“Our merchants interact with a lot of our interfaces, where they get a lot of insights about their customers,” Baha says. “They need to monitor how we deal with fraud problems because acceptance rates are a big challenge for them.” 

For Checkout, the less time customers spend on their dashboards, the better. It means customers can access the data they need quickly. As a result, Baha says they focus a lot on design and data insights to improve acceptance rates.

"Being able to measure that impact… and being able to get a good NPS score out of that because they can feel what they need to do is getting quicker and easier is a big deal for us because it means the less time they spend on their activities, the happier they are."

Mobile analytics also plays a critical role in elevating the customer experience. For Sashank Kuppa, Product Analyst at Tide, mobile analytics plays a significant role in understanding user intent and how different products are used in conjunction with one another.

“Our customers are MSMEs, so they have very diverse needs. It’s important to understand the connection between customers using one particular product and another,” says Sashank. “It becomes essential to have a strong analytics setup to understand this whole process.” 

Mobile data is also crucial when it comes to determining different plans. Sashank mentions that it’s significant to understand existing member behavior to determine pricing, features, and potential premium offerings. 

The power of experimentation to make data-informed decisions 

Experimentation is a crucial lever of success in Financial Services. Data-informed experiments help you make data-informed decisions, which in turn help you improve your CRO and deliver better products for your customers. Win-win, right? 

Sashank agrees. He says that experiments are a big part of what they do at Tide.

“The idea behind it is to establish the causality behind any correlation. The correlation is easy to do, but the causation is much harder. And that’s where experimentation comes into play.” 

Sashank describes an experimentation program to improve their customer onboarding journeys at Tide. They used data-driven experiments to test straightforward design changes, whether copy updates, infographics, or page restructuring. 

“We found that converting a list to a grid increased conversion significantly,” says Sashank.

Of course, all these experiments are data-driven – and that’s an essential aspect to remember. When running A/B experiments, you rely on accurate data to decide who the audience is, the sample size, and how long to run each test. Once you’ve done that, it’s time to track absolutely everything.

“You track the audience. You track their actions in the application,” says Sashank. “Sometimes we also extend this beyond the experiment and say, hey, this particular cohort in this experiment, what did they do elsewhere in the application? And tools like Heap are super helpful when you're in that journey of tracking everything.” 

The benefits of experimentation are clear. But how do you approach experimentation in the right way? 

According to Shameer Sachdev, Founder & Managing Director at Growth Gorilla, approaching experimentation can be broadly divided into three: 

  1. Ramping up

  2. Establishing a baseline

  3. Looking for opportunities where you can take the most significant swings 

“Starting with a baseline of activity and picking what we think are going to be the most appropriate channels to reach your target customer,” says Shameer. “And then from there, you can add in more channels or start to optimize the channels you're on.” 

Your budget and the size of your audience determine this. The larger your organization, the broader you’ll need to go.

Your next step should be testing. 

“Once we've kind of got some threads that we think we can pull on, it's a case of just doing rigorous testing around everything. Creative types, messaging, where we're sending the traffic to from a landing page, or whether we send them directly to the App Store.” 

Shameer notes that your focus should be on experiments with substantial outcomes rather than minor ones, so focusing on statistical significance over rigid timelines is good. 

Finally, being bold is also on the recommendation list during experimentation. And it makes sense – if there is ever a time to play a bold move, surely it’s when you’re in test mode, right? 

"Don't be worried about going into new channels where others aren't,” says Shameer. “Because if you've got good quality tracking, frankly speaking, you might be able to pick up on one of those pockets of opportunity, double down, and end up with an audience that no one's going after."

Financial Services companies can unlock the full potential of data-driven decision-making by overcoming resistance, establishing a culture of experimentation, and aligning expectations with measurable outcomes.

The future of Financial Services 

With the rise of new language models, AI will revolutionize all industries. But at the moment, the financial sector seems poised to take on the most significant transformation as a result. In our webinar, each speaker predicted that AI would tremendously impact the Financial Services industry – from automation to reducing operational costs to streamlining customer interactions. 

Sashank believes AI and automation will help save the industry a lot of money.

"We are already making as much money from people as possible. I think the next step for us is to improve the operational cost," says Sashank. “Can we automate many of these repeated tasks we must do?”

But Sashank also reminds us that as an industry, the financial sector has always needed to be faster to adopt new technologies due to an overall fear of different regulatory measures. However, Shameer counters this opinion. He says that organizations with high data maturity levels will be ready to take on AI and be a part of the next evolution. 

“We’re seeing how efficiently platforms like Google and Facebook can target and reach audiences with all of the data that they have. Imagine a Financial Services organization with millions of users, all those data points, and an insight into their behaviors. Imagine the sorts of journeys and the degree of personalization that they could create,” says Shameer.

Conclusion

Today’s business landscape is getting more competitive, expensive, and crowded. And for Financial Services organizations in EMEA, standing out is no easy task. Data maturity stands as the best way to gain a competitive edge. The more data mature your practices, the more you’ll be able to tap into your customers' real needs and scale your organization appropriately. 

Want to hear more from our Financial Services experts about data maturity? Watch the webinar recording here and learn how big names in the industry are navigating a world of change. 

If you own a digital experience for a Financial Services organization, you can learn how to increase data maturity in our actionable guide.

Julia Rasmus, Customer Success Manager at Heap

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