Traditionally, banks have acted as the facilitators of finance and transactions, resting on a solid footing of traditional values, trust, and history. These values were built at brick-and-mortar stores through personal relationships and brand loyalty that started when we were children. Fast forward to today, the digitalisation of retail banking means that customers can switch to a more appealing offer more efficiently than ever.
In the digital age, banks are striving to foster customer loyalty by creating value that can replace the in-person elements of banks’ value proposition of years passed. Part of this shift involves streamlining and unlocking data that can create engagement. Engagement is typically conceptualised as having two components: the extent of usage (e.g., frequency, duration) and the subjective experience (e.g., interest, appeal, and attention). When deployed effectively, behavioural science can help increase the stickiness of digital banking tools by strengthening consumers’ habitual use.
Here are four behavioural science principles that are proven to improve customer engagement with digital products.
Hyper personalisation and contextual banking
Successful digital banking products of the future will provide a contextualised banking experience tailored to individual users based on a variety of information like location, time of day, personal preferences, money habits, and behavioural patterns. Contextual banking is based on the behavioural science principle of Just-In-Time-Adaptive-Intervention (JITAI). It delivers pertinent information to customers where and when they need it based on data analytics and intelligent algorithms. For example, an app might send a notification based on the user’s location or the time of day based on their previous behaviours in those contexts.
Goal setting and behavioural monitoring
These are two of the most effective behaviour change techniques (BCTs) for digital tool creators. While it’s common for banks to include some elements of goal setting and behavioural monitoring within Personal Financial Management Tools, this will become increasingly common and sophisticated as part of the new world value that banks create for their customers. Goal setting is strongly linked to increasing motivation but also usage engagement by encouraging users to log in and continually check their progress. In the future, these BCTs will become far more personalised and targeted using open data frameworks. Banks are not yet ready to utilise all the data that is available to them, but many are testing and trying new things.
Refers to the inclusion of game-like elements like point scoring, rewards, and rules in non-game contexts, to promote user engagement with products. In Australia, the CX-focused and digital-only brand Up leans heavily on gamification to encourage a positive emotional connection with customers. Their ‘Save Up 1000 Challenge’ combines gamification, goal setting, and behavioural self-monitoring in a robust and engaging offer.
Key trends in digital banking tend to support customers to self-manage their wealth and money. Therefore, retail banks will grow as agents of empowerment, helping individuals set financial goals (BCT: goal setting), track their progress towards them, and develop positive money habits and financial literacy. This will become a central element of banks’ offers, with new value created for the customer.
How to get started
The first step towards designing a behaviourally informed solution or feature is to define your behavioural challenge. We recommend that clients start with an understanding of the user’s job to be done (JTBD). This involves studying what customers are trying to accomplish rather than what they are saying they want, especially in areas with insufficient solutions, as these often make for great opportunities for innovation that gets to the heart of the job to be done.
“If I had asked people what they wanted, they would have said faster horses.” Henry Ford
JTBD is best reduced to its simplest parts while taking a zoomed-out view. Consider using a sentence framework that considers customers’ JTBD in terms of its verb, object, and context. The job to be done should focus on the end goal, not the task at hand.
“Save $60,000 for a house deposit in a rates driven market” rather than “open a new high interest saving account”
Prioritise opportunities to tackle those JTBD. While many opportunities can be available, it is essential to identify the highest value ones for your brand. What aligns most with your values and current product strengths?
There’s no doubt that COVID-19 accelerated consumer expectations around seamless digital experiences, which has driven banks to invest in furthering their digital capabilities. This is an obvious way forward for both customers and brands. Brands can lower the cost of service, and customers can avoid the annoying telephone and branch queues. While many things can be done online using self-serve, we still gravitate towards human intervention and assistance from time to time. “Chat” is a logical way of bridging these two worlds, and our research shows a growing use of this channel.
But whilst Chat is growing, our Moments of Truth study in Australian Retail Banking has shown that, as yet, there has not been a noticeable drop off in the use of other channels. Our results also show that for those that use it, chat is usually the first port of call to resolve the query and most report that they are likely to continue using it. Customers are using chat almost equally across channels: online banking, the company’s public website, and from within a mobile app, which shows that it’s an appealing way of engaging with brands across a range of situational contexts. Our research shows that at this stage, the customer ‘job to be done’ that drives usage of the chat function over other channels is a general inquiry or problem resolution rather than product research.
Our results tracking the performance of Chat across Australian Retail banking reveal four important operational breakpoints for brands to understand and monitor.
These industry breakpoints are consistent with the types of guardrails we see for interactions in other channels. They consider customers’ expectations around how long it takes to get a response, length of chat, and resolution rates.
Customers expect a response within 5 minutes, and NPS drops off markedly if the chat duration exceeds 10 minutes. These figures also outline that knowledge is power. Customers are more likely to recommend the channel when an organisation can quickly and effectively answer questions.
A key measure that is also highly important is how easy they were to deal with, which is going to be in part influenced by these operational outcomes, but is also a marker for the quality of the interaction on the chat itself. And that’s where brands are still struggling with the purely digital part of chat. Across the industry (and, of course, it varies by brands), the mix of chat conversations across humans (live chat), AI chatbots and both is roughly equal. And whilst the AI chatbot-only conversations outperform on efficiency measures, response time and chat duration, they carry lower resolution rates and lower customer satisfaction with “easy”.
If we equalise the operational elements of the experience across these different use cases, we can see that the Human obtains an overall better score for the SAME outcome than the other two delivery methods. In the hypothetical scenario below, where a chat enquiry is answered in under 5 mins, completed in under 10 mins, and resolved by the end, we can see the difference in NPS across different chat agents.
What does this mean for brands?
To increase perceived humanness, many systems with conversational user interfaces (e.g., AI chatbots) use response delays to simulate the time it would take humans to respond to a message. However, as we can see from the breakpoints above, delayed responses can negatively impact user satisfaction, particularly in situations where fast response times are expected, such as in customer service. Brands who engage in delayed responses to Chat interactions, even if only a few seconds, could be missing the point of this channel! They also look to use Natural Language Processing but have a way to go.
The disparity in NPS results across digital and human poses challenges for brands looking to remove humans from the equation altogether and still maintain positive customer sentiment towards the channel and ultimately, the brand. There is a fine line between technology and human interaction due to the empathy and sense of value a human can provide. These experiences need to be seamlessly connected. At this stage, the technology is not yet able to provide a seamless experience as well as high-resolution rates, so humans still have to get involved. But one thing that Chat does do is remove some of the communication issues that can arise in telephone conversations. This, in part, maybe a way to get around some of the implicit human biases that customers have with offshore call centres that are more formulaic and use more standardised responses.
It’s not so surprising, then, that at this stage of the game, the brands which are performing the best in Chat are the ones that have a higher use of humans in the interaction. Newcomer UP has the highest % of human vs AI chatbot interactions, followed by ING. But UP’s lead amongst the competitive set is also fuelled by market-leading resolution rates; 97% of its Chat interactions are resolved by the end, vs only 75% to 80% of those amongst the big4 banks. Westpac stands out for exceptional response times, with 64% answered within 5 minutes and 87% dealt with in under 10 minutes which far exceeds CBA, ANZ and NAB. But this lineup is ever-changing, and it’s important to keep your finger on the pulse and monitor whether you are within the critical operational guardrails that underpin good performance outcomes.
Digital adoption is not an aged-based play!
Naturally, any conversation involving the digital vs human debate sees our clients speculating that it’s really just older people who hold onto human interactions! Whilst as a general trend, this is partly true, digital has been more readily adopted by younger cohorts; we would be missing a trick if we ignored the wider cohort of customers. Our research shows that across brands 32% of customers aged 50 to 74 think they will use Chat a little, if not a lot more, in the future. At this point, I like to share the experience I have with my 80-year-old mother, who whips out her mobile to check the menus via the QR codes the moment we sit down in a café, vs me a young at heart and I like to think forward-thinking 50 year old, who prefers to go up to the counter and get the real thing. Age is not the only factor and many other contextual and psychosocial drivers of digital adoption play a role.
If brands truly want to drive digital adoption, it’s not a great strategy to sit around and wait for a new generation of customers! Here are three behavioural interventions you can use to help reframe preferences for a real human, highlight the benefits of digital, and drive greater use of your Chat function. These are drawn from BVA Nudge Consulting‘s proprietary Drivers of Influence, summarising 200+ human biases into 21 Drivers of Influence©. We’ve made it simple so you can apply it!
Our Australian Moments of Truth Study in Retail banking benchmarks both the behavioural and operational aspects of Chat experiences and allows brands to set themselves apart from the rest, increase efficiency and, most importantly, customer satisfaction. MOT complements your internal perspective giving a competitive lens and powerful insight into industry breakpoints and acceptable service thresholds for operational performance. Context is king! The market is always moving, and you can guarantee that your competitors are also investing in digital capability.