The financial press and national media are full of stories of the differences between the generations coming of age compared to those that are close to retirement. The column inches focus on millennials’ challenge to get onto the property ladder or generation Xers starting to think towards a retirement that may never come.
As a marketer, your role is not to fight this context, but to reach your existing and potential customers in ways that support them get to where they want to go.
Whilst they may be sweeping statements, there’s some truth in the postulations that younger financial consumers have increased expectations of immediacy (“fast”) in the provision of services; whilst the older generations expect their service providers to understand their needs over the longer term (“slow”).
There is certainly some overlap amongst the generations - and what is clear is that these expectations place ever increasing demands on financial services organisations, that need to hold on to their existing customer base, whilst attracting younger customers.
Before we get ahead of ourselves and say “AI to the rescue!”, we pragmatically recommend that through considered user experience design and application of the latest machine learning techniques, customer relationships can be deepened both ‘fast and slow’.
More than ever, brands need to have a clear understanding of their customers’ entire experience, and an even better integrated view of how they deliver their services over that journey.
There are two specific ways of delivering the customer experience that can aid in delivering the wider project. The first, what we will call “fast”, is about being able to respond rapidly to customer needs; the second mode, “slow”, is about being proactive to their needs over the long term.
Fast - in the moment
How is it possible for financial services brands to respond to customers needs at the speed of an Uber?
Like many of our customers, we watched chatbots reach their ‘peak-hype’ in 2016, and gratefully, we’re now entering a period where applications of machine-learning-supported conversational interfaces are being applied more sensibly. As we map out Minimum Viable Products (MVPs) with our customers, we are investigating opportunities from the omni-bot (the layer that can sit above all customer touch points) to the very specific use cases that address one particular customer need, such as resetting a PIN.
The primary objective is to solve the customer’s need state with as little friction as possible - that need could be a customer service enquiry, or could be a new business opportunity, such as with Lemonade, the American insurance company.
Lemonade’s on-boarding process to provide its customers with an insurance quote is entirely done through a conversational flow, but it does not display much intelligence beyond its well-designed conversation tree. It does however point to a future where companies, during an on-boarding process, chunk complicated financial products into smaller understandable pieces, led by empathetic user experience design, in a way that a very effective adviser might do face-to-face.
UK online Mortgage Broker, Habito, has incorporated a similar conversational on-boarding process, but the human adviser has not been removed from the process. In fact, every mortgage enquiry is discussed between the adviser and potential customer - but for the customer they have already had a positive interaction with the company when it suited them, and the pre-qualification has been done for the adviser.
Slow - over the longer term
The objective of designing “fast” digital touch points is to serve the customer at the moment they have a precise need, be that as an existing customer with a problem, or a new customer enquiry, whereas implementing solutions in “slow” mode is proactively serving the needs of a client over the long term.
To draw a parallel, it would be like the traditional financial adviser who has a direct relationship with her customers over many years and has an understanding of their needs such that she would be keeping tabs on news and market developments that could affect her client.
At Codehouse, we worked with a professional services firm to establish how we could support their clients understand changes in a rapidly-evolving niche market, by leveraging the firm’s vast thought leadership content. Manually configuring tailored content marketing plans on an individualised basis would be a mammoth manual effort given the hugely diverse interest sets of their client base. We developed a proof of concept with a machine learning software vendor, which harnessed natural language processing to understand the meaning of their content and to create semantic links between articles, podcasts and videos. Based on the user interests and their communication preferences, they could then receive fully personalised, meaningful content recommendations.
Deepening customer relationships in “Slow” mode is not limited to marketing communications.
Financial services companies are leveraging automation in the way they deliver their services over the long term, from mortgage brokers continually tracking if their customers can get a better rate with another provider, to wealth management platforms automatically re-balancing portfolios. These offerings are no longer at the cutting edge of technology, but they are indicative of the broader trend to provide customers with value over the long term, without requiring the expensive overhead of individual client managers.
Whilst the “Fast” and “Slow” lens is not a holistic approach to developing and delivering end-to-end customer journeys, it provides a useful perspective on how companies can build deeper relationships with their customers in the moments that matter most, and over the long term.
Want to learn more?
Codehouse’s breadth of capabilities and knowledge of the cutting edge in customer experience, design and web and enterprise technologies enable us to help our clients successfully navigate the financial generation gap.
If you'd like to know more about how we can help your organisation, then get in touch today.