Why ‘big data’ could be the answer to addressing banking customer service

By Mike Hughes, managing director for European operations at intuitive consumer experience firm [24]7

Customer service in the financial sector hasn’t always enjoyed the best of reputations. Whilst this reputation is not entirely justified, it is true to say that whilst other industries have embraced technology for customer service, FS organisations have been slow to do so. There has been a fundamental shift in customer expectations. Consumers are increasingly using their mobile devices to connect to the web use social networks such as Facebook and Twitter and they expect to interact with organisations at their convenience, using smart mobile devices and employing multiple channels.  Recent research from Ovum suggests that 74% of consumers employ three different channels to resolve customer service issues. In too many cases, each communication channel operates in a silo, keeping it isolated from vital data and interactions the customer may have made through an alternate channel. Mike Hughes

The answer lies not just in adding more and more channels through which to communicate, but also in analysing the data gleaned from those channels and predicting what consumers want, regardless of which channel they choose to interact.  When applied to areas such as customer loyalty and reduction of customer effort, the application of predictive analytics and interactions driven by intuitive communication models can reap great rewards for banks.

Not making the most of new channels
Part of the challenge for the financial services industry is that customers’ expectations have changed. Computing and communications technologies have advanced to the extent that customers now have the opportunity to reach out to their bank in a number of ways, 24 hours a day, through web self-service, social media and mobile phone apps. The access is right at their fingertips and customers expect the same rapid and intuitive experience from the organisation they contact as can be found on the smart devices they use to communicate with.

The challenge is to integrate the information received through the various channels and approach the problem holistically, from the customer perspective. Addressing the issue of multi-channel interactions, experts have started to talk about the Single Customer View (SCV); a recent Experian Marketing Services study suggests only 25% of FS organisations are addressing the SCV as a priority. New channels such as web self-service, social media and mobile phone apps were intended to reduce the volume of customer service calls, but this hasn’t happened. Channel information needs to be fully integrated and approached from the consumer perspective.

Not enough is being done to address the opportunity of customer-centric communications which offer a seamless service across multiple channels. As well as the benefit of positive customer service, the data gained from such a solution allows an FS organisation to get a picture of the “real” customer and gain an understanding of how to fulfil their needs.

Banks need to develop this seamless experience to ensure that the customer is taken through the same simple steps regardless of whether they’re visiting a branch, engaging online, speaking to a representative on the telephone or a combination of these. Most banks already have all the data they need to deliver a modern and intuitive service which could make their customers’ lives easier.

Delivering a predictive experience
[24]7 works with a number of banks to deliver a predictive experience for customers which anticipates their requirements to smooth the path of their interaction. This is done by analysing the customer data and developing smart models which learn to adapt and intuit customer needs. Using these big data techniques to reduce customer effort will pay dividends in brand loyalty and reduced resources required for managing enquiries and complaints. However, the benefits can also extend into the development of a platform which can support cross-selling and upselling as the system learns to understand customer requirements and patterns and can suggest relevant complementary financial products and services.

Ultimately, modelling the customer journey has benefits for the customer and the bank. For example, if a customer has recently obtained a new loan, their next interactions will likely be about their first statement, automatic payments, and transferring funds between accounts. The system can make a reasonable estimate as to their likely requirements and appropriate product or service options can be presented in a timely fashion, rather than bombarding each visitor with irrelevant marketing offers in the hope that one will hit the mark.

At [24]7 we have a data analysis model that allows us to develop a continually learning model which adapts incrementally as customer behaviour changes over time. Our company ethos is – Anticipate, Simplify, Learn – which highlights our focus on customer needs. The last element – Learning – is not only causing a revolution in customer service today but also guarantees the future evolution of positive customer service channels which change with the needs and expectations of customers.

Those who don’t keep pace with their customers may find that the only revolution they experience is the dramatic loss of customers who turn elsewhere. Whether in-branch or online, the smarter revolution of engagement lies within the grasp of all FS organisations. If they make use of the data they already have to make their customers’ lives easier, loyalty will grow and the profits will follow.

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