How will the banking industry transform in 2021? has been saved
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The global pandemic is pushing us toward a future we were already headed toward faster than we even thought. And nowhere is this more true than banking. Let’s look at how banks can adapt in a world of less touch and more distance.
If you haven’t noticed already, we like to talk a lot about customer experience. Or as we call it, human experience. In a world where in-person interactions have become digital experiences, banks need to adapt their strategies for connecting with their customers. We work together with leading technology providers like Adobe and platforms like Adobe Experience Platform (AEP) to build deep personalisation into customer experience to drive connection, loyalty, and ultimately, growth. Here’s what we’ve learned.
If you’re building a house, you start with a blueprint. If you’re building customer experiences, you start with data. For years now, banking providers have had a ton of data stored within complex data systems. But the sheer amount of data and complexity of the systems made it difficult to truly gain a full picture of a customer’s behaviours, expectations, and needs.
In this accelerated digital age, great is the ability to recognise your customer and provide them with a fully personalised experience regardless of the channel they chose to interact with. Data sits at the core of making this possible and should be activated rapidly and efficiently. We need to migrate from “data-rich” to “activation rich" environments.
A customer data platform (that’s CDP, in the biz) allows banks to easily look into customer data in real-time in order to enhance the overall customer journey. The CDP needs to record and track customers’ online behaviour across devices in real-time, gather insights on customers’ data trails, and be supplemented by other owned data sources like call centre history, purchase history and demographic information. This provides a 360-degree view of customers, creating the foundation for an omnichannel customer experience.
The end result is a single source of truth that contains all relevant customer profile information that is accessible and activated as near to real-time as possible. Building and retaining ownership of this customer profile data enables activation, advanced analytics, and business intelligence, not to mention the ability to meet today’s ever-changing data privacy and security regulations.
A customer’s data can certainly tell us a lot. But numbers and data sets can miss out on a crucial element: that humans are, well, humans. Where data and emotions intersect, banks can find smart ways to build great experiences.
There are few topics more emotional than someone’s relationship with their money. Our research has found that emotions drive a significant part of how we behave with our finances. Unfortunately, banks aren’t very good at capturing and acting on this emotion in the bit and bytes that drive their typical data strategy. The good news is that critical information that banks need to know about their customers—buying habits, intentions, how they feel, hopes and dreams—is hidden in plain sight. It’s up to banks to identify, capture, and unlock this data to deliver a meaningful experience. For example, milestones—like getting married, starting a business, or purchasing a house—cause us to feel all sorts of ways. Emotions like joy, sadness, and anticipation impact our lives and our choices. To help build human experiences, banks need to be able to look beyond the obvious to see their customers as they truly are—complex humans with all sorts of emotions who are simply looking to navigate their lives. They’re telling us who they are with every click, swipe, call, chat, and interaction. We simply need to listen digitally, just as we have done for years in our branches.
Once we start listening, we’ll be amazed at what the data will tell us, which is where artificial intelligence (AI) and machine learning (ML) comes in. When combined with sentiment platforms, these technologies can help banks collect and understand data signals that help identify when our customers are experiencing a milestone, when they’re frustrated, when they’re looking for something, or when they’re considering leaving us. Once we’ve found the signal and have the insight, we have to decide what to do.
AI and ML can help identify the best way and time to engage with each customer and take us on a journey to scale great experiences. Autonomous marketing can help banks create and deliver customer segmentation and targeting at scale, automate decision making, and curate the right experience for each segment. In the Australian market, where there are often resource constraints for marketing execution, these technologies can really help enhance the human experience and take personalisation to scale.
When used intelligently and ethically, insights like these can help banks unlock the full potential of customer data.
As we navigate this year and the next, competition from traditional banks and disruptors will be stiff—everyone is adjusting their strategy, making digital a priority, and prioritising the personalised customer experience. Today’s leapfrog is tomorrow’s table stakes. Only by knowing more about your customers, through data, and by being prepared to act at scale on the insight it provides, can you sustainably differentiate yourself.
Frederik applies his two decades of technology, data, and marketing experience to turning data into personalised experiences at scale. He is known for helping his clients to deliver award winning personalised experiences to become better, data-driven organisations. He leads the MarTech capability of the Deloitte Digital practice in Australia. He has created a team of marketing and advertising technology experts who thrive on leveraging Artificial Intelligence (AI) and Machine Learning (ML) to deliver customer segmentation and targeting at scale, automate decision making, and curate the right experience for each customer at the right time. Frederik’s true passion is to turn organisations around from being “data rich” to being “activation rich” and he loves to use automation to scale personalised experiences. He believes that great experiences are created with the ability to recognise customers, their needs, and their emotions to provide them with the right experience regardless of the interaction channel.