How RBS Used Data Science as a Service to Improve Customer Service
In my last blog post, Data Science as a Service – What it Means for Customer Intelligence, I talked about how the delivery model we’ve been calling “data science as a service” really enables a level of insight democratization that hasn’t been achievable with traditional business intelligence tools. We’re democratizing data not just for those workflows focused on performing analysis but also for a wide range of business workflows that are naturally enhanced by surfacing data within them. The combination of the delivery model, real-time programmatic access to the data in the cloud and machine learning as a lever to automate the most common workflows has proven to be very powerful for our customers.
One of the most prominent users of these capabilities is the Royal Bank of Scotland (RBS). You may have seen the case study we published recently describing the transformation that RBS has been able to achieve largely in part to the dynamics we’ve been discussing as part of this blog series. RBS decided to take a leadership position when it comes to using data to integrate the experiences that their customers have across the multiple touchpoints with the bank. Those include not just their digital channels, but their offline touchpoints as well. They invested in the use of data science as a service to drive customer intelligence through a large number of stakeholders within the company. These stakeholders then used this information to control how the bank’s brand was presented to their customers.
Giles Richardson, head of analytics at RBS, knows the power of the capabilities they implemented better than most. In our case study, he described the approach he and his team have used as they’ve driven this change in the bank.
My team and I have established new identities for our digital marketing leaders, called Superstar DJs (short for digital journeys). DJs are basically product managers for the different journeys that their customers experience as they interact with the RBS brand. They team up with guest DJs from outside teams — such as Customer Experience, HR, and legal — to participate and lend cross-functional expertise and insights. For example, the DJ manager for checking accounts may invite a manager from RBS’s call center team to participate as a guest DJ to help optimize customer experiences on a web page to sign up for new services. As a result, RBS marketers can tap into insights from colleagues across departments to uncover new ideas for transforming customer experiences and returns.
Who would have thought data could drive such a positive cultural shift? A key example of the benefit of the new visibility into customer behaviors is learning that 30 percent of all customers use mobile devices to apply for loans. However, conversion rates were low. After testing and then rolling out a streamlined mobile experience, customer conversion on mobile jumped by 20 percent and loan applications were completed in minutes rather than days.
This type of data-driven approach applies across all of the touch points our customer has with our brand. Whether a customer opens a direct-mail piece, receives a follow-up email, visits a branch, or applies for a loan on a mobile device, the entire customer experience should mirror their needs perfectly. We must be everywhere customers are and personally cater to their needs at every turn.
We don’t expect customer trust — we earn it. We’ve become helpful and relevant in every customer interaction online, through call centers and in branches. This drive toward being data-driven in all we do for our customers is driving a sense of excitement and teamwork at RBS as we learn how to treat customers better and better.
Even though RBS is a 300-year-old brand, their attitude toward data as a strategic asset to be used as widely as possible is paying huge dividends. They lead the way in adeptly using data to understand and optimize how their customers interact with their brand at scale.