Here are three innovative ways to use customer data to create products and services individual customers want — when and how they want them.

Hyper-personalization is now achievable for financial services organizations, thanks to commercially available data sources, artificial intelligence and machine learning (AI/ML), and modern software techniques. Together, these components enable businesses to build 1:1 experiences at scale.

In our work with financial services organizations to engage customers with personalized digital experiences, we advise them to incorporate the following three guidelines.

1. Look beyond defined customization, to dynamic co-creation.

Until recently, personalization has relied on “constrained modularity” — a small, finite number of hard-coded options. Perhaps your bank app allows you to personalize your dashboard by adjusting the order of accounts displayed, or to choose whether your monthly statements are mailed or delivered digitally. This, however, is actually customization — the forerunner to hyper-personalization.

Instead, financial services organizations need to engage in ongoing data collection to deliver dynamic experiences that keep changing in step with customers’ unfolding behaviors and desires. Think of this hyper-personalization as co-creating experiences with your customers. For example, DBS’ iWealth app provides tailored equity stock suggestions based on insights derived from customers’ investment patterns.

When new data arrives — an interaction with the bank or a lifecycle event discovered from an external data source — the application code automatically adapts the experience. A simple example would be a bank app that notes you always check your credit card balance first and automatically personalizes the experience by displaying your balance front and center on the app’s home page.

For some customers, a hyper-personalized experience can be unnerving — targeted ads that make the customer suspect the advertiser is scraping their private email. To make hyper-personalized experiences more welcome, consider these questions when building digital banking experiences:

• What level of control would benefit the customer if the mobile banking app could change with their patterns of behavior?
  
  
• How might healthcare data be used to understand changes in risk tolerance to dynamically shift investment portfolios?
  
  
• How might customization and dynamic cocreation be combined to produce commercial experiences that proactively grow with customers’ business?

2. Broaden the focus from individuals to their relationships.

The relentless pursuit of personalization has focused on understanding the individual, but over-indexing on the individual can miss their wider circle. People connect around shared hobbies, familial ties, pastimes and beliefs that drive their identities both online and offline. Financial services organizations need to recognize these patterns of connection, affiliation and relationship between individuals that influence everyday decision-making — including how customers manage and part with their money.

For example, Venmo provides users with the option to see who they’re paying and under what circumstances — a rich source of contextual information that has been known to spark Venmo voyeurism.

Take the market disruption caused by Reddit armchair investors who influenced the stock price of GameStop. This showed that influence has become more distributed and can come from surprising sources — even in areas that were previously considered to be untouchable by the masses. As banks map individuals’ behavior to create more personalized experiences, they should also consider widening the aperture:

• What commercial data sources can help you understand customers’ networks of influence beyond banking in order to shift targeting strategies?
  
  
• To capture this moment of the intergenerational transfer of wealth, how can you loop in influential family members when you deliver services such as estate planning and wealth management?
  
  
• How can data (which typically focuses on behaviors) start to shape banks’ understanding of context and drivers of that behavior?

3. Commit to transparency and reciprocity when gathering data.

High-profile companies have acquired their users’ personal data under the cover of complex terms and conditions, sowing mistrust. To win trust, financial institutions need to be transparent about what they’re collecting — and, more importantly, what’s in it for the customer. 

Drop — which is backed by RBC Ventures — offers rewards across big brands that consumers already spend with in exchange for access to personal transaction data. To design such tradeoffs throughout an experience, banks will need to rethink customers’ need for control. In this newly defined value exchange, this can drive more trust as customers part with data over time.

We know that customers will trade data for value. One proof point: 23andMe convinced more than 12 million people to share their most personal of information, their DNA, in exchange for health risk predictions and connections to relatives. This changed the regulatory environment around home testing and paved the way for access to better health insights.

To give customers a good reason to share data, we advise financial services organizations to ask the following questions:

• How can you identify the moments that matter to prioritize data collection efforts?
  
  
• If you treat data as a true currency, how might you demonstrate the connection between the data customers provide and the real-time value that can be returned?
  
  
• How can you shift data disclosures from “accept all cookies” buttons and lengthy T&Cs to an ongoing dialog about value exchange with customers?

Done right, personalization is the core of a great digital experience. By rethinking how they engage with customers and their personal data, financial services organizations can gain a better understanding of what drives behavior and, ultimately, build a mutually beneficial relationship between consumers and the business.