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Customer Centricity for the Masses

Many financial services companies talk floridly about being customer centric. Customers have surely never had it better.

As advertising guru Bill Bernbach once said, “A principle isn’t a principle until it costs you something.” When talking about the principle of customer centricity, many companies focus on the intersection of what’s good for the company and what’s good for the customer. Customer centricity as long as it makes the business money in the short term. Customer centricity with an asterisk.

One of the reasons companies cannot translate customer needs and wants into products and experiences is because they don’t understand the “why.” Digitalization has resulted in companies gaining access to accurate data in a timely fashion. Mobile apps, ecommerce platforms and websites of all varieties generate a large amount of data which is turned into dashboards, reports, insights and ultimately some form of data-driven decision making. Digital is data after all.

However, those 1s and 0s rarely provide an insight into the motivation of a customer. Various studies suggest that over 70% of interpersonal communication is non-verbal1. Good luck capturing that information from a mobile or web application. The problem with most digital analytics is not a lack of data, but the means to analyze that data to generate actionable insight beyond the blindingly obvious.

In a Harvard Business Review article2, leadership luminary Thomas Davenport reported that less than 1% of a company’s unstructured data gets analyzed. If you combine that figure with the broadly published and generally accepted heuristic that 80% of a company’s data is unstructured, there is a sizeable blind spot in customer understanding.

Every company is sitting on a veritable gold mine of insight in the form of customer service interactions, in-bound customer contacts, field engineer reports, key account manager conversations, contracts, customer satisfaction surveys (the long answers that nobody reads) and product reviews. This data is freely offered and when it comes to customer reviews, publicly available.

Fortunately, advances in machine learning, particularly in the field of natural language processing (NLP), have made the process of mining unstructured data for gold significantly more accessible.

To prove the point, we analysed over 100,000 customer banking reviews from publicly available sources to rate and compare customer experience across Tier 1 and Tier 2 Banks, as well as Neobanks, within the UK using our Customer Experience Growth Index. The world of customer reviews can easily be gamed. There is a strong positive correlation between the number of reviews a bank has and the score (generally out of five stars) it achieves. This is largely due to some banks engaging in managing their customer service score with a customer review company. So, an analysis of customer review scores only yields limited insight. Almost all banking mobile apps in the UK achieve 4.9 or 4.8 scores on the Apple Store, making the scores practically meaningless. Analysis loves variance. The variance can be found in the verbatim review comments rather than the star rating.

An analysis of language comparing good and bad reviews reveals the insights you would expect. People use positive words in five-star reviews and negative terms in one-star reviews. Instead, we compared the language used in five-star reviews only, and compared the differences between banks, to isolate the things consumers like about their provider when they are happy with their bank.

Looking at the UK banking sector, there is a clear divide between challenger banks and their established high-street rivals. When challenger banks are compared head-to-head what we see is a battle over features.

Figure 1 is a Venn diagram of topics that appear in Monzo and Starling Bank five-star reviews. Both challenger banks have a feature, Pots for Monzo and Spaces for Starling, which allow the customer to divide their current account up into separate pools of money to either save, pay bills or fund their social life. Monzo five-star reviews predominantly focus on key features of bill splitting (being able to pay a bill between friends), easy upload of phone contacts as payees and being able to access your salary at 4pm the day before its paid in. All key features that Monzo has innovatively brought to the market. Starling on the other hand has reviews that cover its own feature set, the ability to integrate with Xero accounting software, to pay cash into post offices in the UK and to be able to set up accounts in different currencies.

Key topics comparing challenger banks: a battle over features

This makes sense, both banks to date have been successful at acquiring new customers, using an innovative set of features to shake high-street banks out of their slumber. Many high-street banks over time have copied these new features, rolling them out into their own mobile apps. Monzo and Starling have the highest scoring UK banking apps (both 4.9), and according to data3 have some of the highest net current account switching volumes in the market.

But is copying an innovator a winning strategy? One of the benefits of digital transformation in banking is the cycle time from idea to execution has reduced by over 100%. According to our own internal research, Publicis Sapient estimates that the average time to getting a new feature into production is approximately four months (down from nine months+).  There are kudos in being first, and this reinforces a status of innovator, but the window of competitive advantage of a feature in a mobile application is now getting shorter. The copying of innovators and the reduced cycle time is leading to a convergence of functionality and ultimately customer experience in UK banks. It’s hard to lead if your strategy is one of imitation.

Perhaps the answer lies in the comparison of reviews of a challenger bank and a traditional high-street bank. Figure 2 shows a similar Venn diagram featuring Monzo compared to Barclays. While similar topics are identified as appearing predominantly in Monzo’s reviews, in addition to some user experience superlatives, the Barclays reviews contain a completely different set of topics.

Key topics challenger versus high street bank: features versus traits

Barclays’ five-star reviews contain far more terms that relate to the personal service the bank provides. Barclays’ customers were 28 times more likely to refer the bank (and its employees) as being kind, 24 times more likely to say polite, 48 times more likely to say patient and five times more likely to say helpful.

Monzo might be competing on innovative features, but Barclays is competing on service and the positive emotions this generates. It would therefore be a mistake for a high-street bank such as Barclays to purely copy Monzo’s innovation.

There is clearly a requirement to provide functionality that customers expect from their banking app. However, leadership is rarely achieved by copying others. A quick Google search will reveal numerous sets of best practices and golden rules for customer service, but the reality is there is no single set of rules to follow, and even if there was, this is the road to commoditization and ubiquity. Instead, banks need to understand, from a customer perspective, what it is that people value and is distinctive about the service they provide.

This raises a significant issue in the path to digital transformation. If customers value human interactions with colleagues, how do you digitize these services without losing their empathy? In robotics the phenomenon known as the uncanny valley suggests that the closer robots resemble human beings the more we, as humans, are repulsed. When humans are humans and robots are robots everything is fine. When robots pretend to be humans we start to get a bit freaked out. This issue is at the heart of any attempt to digitize empathy. Regardless of intent it often comes across a bit weird. Whether it’s a clearly automated chat bot that is pretending to be a real person or robo-investment advice, the challenges to digitizing relationship-based services are challenging to overcome.

Part of the answer may lie in how banking colleagues’ experiences are being transformed. One of the assets that high-street banks have over their digital rivals is the volume of highly trained and experienced customer-facing staff. During various COVID lockdowns many different types of face-to-face interactions have been digitized. From GP appointments to parents’ evenings now being conducted through a mobile device, banking appointments are increasingly being conducted digitally. One high-street bank recently suggested that digital appointments have risen from 400 to 10,000 a week over the last two years. Obviously, the quality of that experience for customers relies heavily on the quality of experience for colleagues.

Cryptic as it may sound, a path to true customer centricity may necessarily travel through colleague centricity first. If the colleague experience can be modernized and transformed, taking advantage of advances in technology and data, the effect will be noticeably felt in the customer experience, and that is a feature challenger banks, with their digital only experiences, struggle to match.




Simon James
Simon James
International Lead Data & AI

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