From the day when supermarkets first introduced customer loyalty card schemes 20 years ago, the retail industry has been leading the way in analysing customer data to provide personalised product and service marketing. This has evolved from targeting customers with discounted offers based on purchase history to dynamic marketing based on a customer’s online behaviour and geolocation data.
The retail banking industry has been slow to adopt similar personalised marketing services. But why? In a sector dominated by the Big 5 high street banks in the UK (Barclays, HSBC, Lloyds Banking Group, RBS/NatWest and Santander), there’s been an inertia to change. However, the rise of challenger and digital banks is increasing the pressure on the Big 5 to reorient themselves, aligning their value proposition around the customer in order to retain their existing ones. Given the challenge in repurposing legacy architecture to enable transactional data to be extracted, analysed and used for the customers’ benefit, banks have been reluctant to experiment. However, with technological advances in predictive data analytics software, banks now have the opportunity to gain real insight from this data, surely a source of significant competitive advantage?
Furthermore, mass-market bank customers are showing the desire to pay more for an ‘advanced basic’ service. Yet, while some banks have been experimenting with current accounts which offer ‘premium’ features, they are yet to truly harness customer loyalty programmes as a hook to attract and retain customers. We believe that the time is ripe for the established retail banks to behave more like retailers, and build customer loyalty schemes to foster long-term customer relationships.
What will the value proposition be?
With a growing push from regulators for increased competition in the retail banking marketplace, and perennially low net interest margins, banks are coming under increasing pressure to find new revenue streams. We see an opportunity for them to act more like retailers and expand their customer loyalty programmes, thereby attaching a greater focus on retaining and developing their existing customer base.
By analysing and linking data points to understand customers’ decisions and spending patterns, retail banks could morph their customer relationships from purely transactional to a more advisory, lifestyle service. By extending tailored offers based on customers’ needs, they will be able to develop a deeper relationship with customers, foster increased loyalty, and create more value for both parties.
Supermarket loyalty programmes are predicated on a simple principle: purchasing one product prompts future discounted offers on that product, or similar ones. Banks are in a position to be able to offer much more sophisticated loyalty programmes than supermarkets. The rich transactional data they own can be used to gain deeper insight into customer behaviour and help customers navigate future decisions at important moments in their lives. Examples of some of these key moments are detailed below.
Moreover, if banks were to introduce a supermarket-style points system to reward longer serving customers who take up these offers, this could lead to a self-fulfilling prophecy. Sainsbury’s, one of the first retailers to offer a loyalty scheme with Nectar card, remains one of the leading players here. Their simple offering is a loyalty point scheme, 1 point for every pound spent, which equates to discount vouchers. The key to their continued success however is on partnerships. They have a network of 400 partners, including Argos, BP and Merlin Entertainments Group, so their customers can extend their basket of goods way beyond the supermarket. This benefits all 3 parties: the customer, Sainsbury’s, and the partner.
“Banks are in a position to be able to offer much more sophisticated loyalty programmes than supermarkets.”
Provisioning digital wallets, apps that combine payment with loyalty card functionality could help banks to close the gap on retailers. John Lewis serves as a leading example here, adding its loyalty scheme to its app in 2015. Customers benefit as they no longer need to carry around physical cards. And for the banks, this would be a cost-saver.
It is important that established retail banks consider how their organisational structure could support this value proposition. They are traditionally organised by product, channel and function, (i.e. based on their internal organisation, and not around the customer). Disruptive digital banks are behaving more like retailers by building their organisation up around their customers. This allows the bank to truly understand their customers, as discussed in our recent paper on the state of play in digital banking. Established players should look to reinvent the way they are set up.
What example scenarios for cross-selling can we envisage?
We have identified a range of scenarios for tailoring customer marketing based on predictive analytics. These are based around major life events during which customers need to make important financial decisions. Here are some examples:
The bank detects that a customer’s monthly salary has recently increased (on a consecutive monthly basis). They send a notification to the customer offering a targeted range of savings and investment products, based on the extent of the salary increase as well as the overall size of the customer’s assets across all accounts (main salary account, as well as any others).
Scenario 2 – Starting university
The bank identifies a recent transaction to UCAS for a university application payment on a parents’ account, and offers a student current account and incentives to the existing customer (parent) in order to entice them to set up a new student account for their son or daughter.
Scenario 3 – Planning a wedding
The bank detects that a customer has just put down an advance payment on a wedding venue and extends an introduction to a financial planning toolkit to support event budgeting, as well as special product bundles on travel insurance, foreign currency and loan products to facilitate honeymoon planning. In addition to financial planning, the bank could for example partner with wine retailers to offer a voucher for a complimentary bottle of champagne to the customer, to attract them to use its planning toolkit.
While the underlying analytical technology required to realise these types of example scenarios is not new, a set of conditions have now aligned such that the time is right for change. Extending marketing campaigns like these provide personalised ways of making the customer feel special. That would be game changing in the current market.
Why should established retail banks act now?
With more than 68m active personal current accounts in the UK, retail banks are sitting on more data today than ever. Yet less than 5% of all data is ever analysed. Online retailers such as Amazon are particularly good at analysing customers’ online behaviour to target marketing campaigns, so why aren’t banks mining their own rich seams of customer data to cross-sell and up-sell their products and services?
Established retail banks need to reinvent their organisations quickly to ensure they maintain their market share, and they should act now.
- When it comes to customer trust, established retail banks now find themselves in a reinvigorated position. 86% of customers in North America now trust their bank over all other institutions to securely manage their customer data, a platform which has been slowly strengthening since the collapse in trust following the Global Financial Crisis.
- Analytics toolkits are increasingly powerful and are becoming more affordable. Analysing customer data in order to create personal customer relationships has traditionally been exclusive to private banking and wealth management. But now some data analytics tools are now priced attractively enough to be implemented on a larger dataset of customers.
- New digital banking startups like Monzo and Starling are branding themselves as ‘lifestyle’ banks and will likely offer this kind of analytics service as standard. Established players need to react in order to prevent losing market share to new and innovative players. While these new banks may be setting themselves up with the right analytical toolkit, it is the established banks who have the scale and the trove of customer data which they are yet to monetise – these are assets no startup bank can hope to emulate.
Of the leading high street banks, early in 2016 HSBC soft-launched HSBC Nudge to 500 customers (HSBC employees only). Based on the nudge theory, current account data is used to alert customers of their spending habits, advising on those that they might want to eradicate. While results of the study are yet to be released, given that the new digital banks are increasingly becoming operational, it is clear that banks should recognise the need to focus on this, and do so now before digital banks gain critical mass.
Before embarking on such a project, it’s important to gain clarity on what the business model for such an offering would be. Considerations include:
How to define what the customer offering would be
A ‘full’ offering could include a paid for, managed account, for which the bank’s service to the customer includes the provision of sophisticated marketing based on the customer’s data. An alternative solution could be to simply provision a well-presented extract of analysed customer transaction data. A light offering could be to provision the data extract of transactions only, without any analytical overlay.
How to monetise the offering
There are a number of ‘premium’ current accounts in the marketplace offered by the established banks. The value proposition of these accounts range from offering travel insurance, interest on current account balances and an improved quality of customer service. Crucially, these focus on generic, and not personalised benefits. With the obvious cost incurred in developing such an offering, it is important for banks to consider what they gain from this strategy. This could include an increase in profitability per customer, without having to incur additional marketing costs.
How to identify the customer segment to target
This includes whether to focus on a segment based on account size, as per the traditional model, or to target based on a chosen age cohort, for example to attract the ‘millennial’ customer.
Once a strategic decision has been made, the next consideration would be on how to deploy the proposition. While none of these challenges and considerations are insurmountable, all require serious discussion.
Along with developing the data technologies to be able to realise such a value proposition, there’s a need to assess how the proposition aligns to the wider data strategy of the organisation. When doing this the bank needs to consider its place in the evolving competitive landscape, and its preferred strategy on how to engage the new Fintech players in the market.
Irrespective of which route to market the established banks take, there’s a need to act now. Banks arguably possess richer customer data sources than any other organisation, and are yet to fully use them.
The competition is fierce, and is only going to get more so. New entities with innovative models have the technology, but lack the scale and customer numbers. If established banks can create this innovative customer-centric environment and use their existing scale to get ahead of the pack, they’ll gain a significant competitive advantage.
Right now, established banks are a long way behind retailers in how they engage with their customers.
This should not be the case. The building blocks are now all in place for banks to change this and the first bank to properly address this challenge stands to reap great rewards.
How can we help?
We would be delighted to talk to you about how we could work together. We are well-placed to support a bank in considering the merits of a proposition like this. Our experience includes:
- Providing innovation scouting services for our banking clients. Through our extensive network in Silicon Valley, Tel Aviv and London, we personally vet and match startups who provide exciting and relevant new capabilities in data extraction and analysis to established retail banks
- Developing a strategy in response to the new General Data Protection Regulation
- Developing customer value propositions, particularly in the digital space
- Developing such models from conception into reality
- Developing the required operating model
- Evaluating the impact on organisation design
- Understanding and planning how existing technology can be integrated with new solutions
- Developing cyber security strategies
- Assessing cultural change needs, in order to drive fundamental behaviour change
Let’s work on a project together.
Get in touch: email@example.com
- Your business must prepare today for 2018 EU data protection laws – ITPro
- Capgemini World Retail Banking Report 2016