Tim Crick draws on his experience leading the development and deployment of customer contact architecture at the Royal Bank of Scotland to share advice about rolling out next best action solutions.
Customer-oriented organisations – and financial services firms especially – are struggling to find practical ways to attract, service and retain valuable customers at a cost that is right for their business.
Many organisations, including retail banks, recognise this but their investment in systems to improve customer interaction channels often seems to fall short of expectations. Indeed, there can be a reality gap between what the organisation thinks it delivers to customers and the experience of the customers themselves.
For example, research by Pegasystems revealed that only 4% of customers felt treated as an individual, despite almost half of the customer service organisations surveyed claiming they offer a ‘personalised’ service. Customers also said they feel they know more about products and services they have with a company than their provider does (42%), and the majority of them don’t trust the information they are given.
So how to close the gap? It seems that developments in technology around real time decisioning could be a major part of the answer here. Customer decisioning solutions have the capability to help guide and adapt each inbound and outbound customer interaction and communication for every channel and line of business. As a result, customer next-best-actions are generated to deliver real benefits to both the organisation and its customers.
Drawing from my role in leading the development and deployment of customer contact architecture at the Royal Bank of Scotland in a project built around a Pegasystems decisioning solution, there are some key lessons I can share.
1. Understand where and how to deploy customer decisioning to maximise mutual value
Firstly, you need to understand where and how you can use a real time decisioning capability within your overall customer experience to maximise mutual value. The key is to understand the full potential for the use of decisioning within your customer interactions. For example, some might see decisioning as just a new and cheaper way of sending more messages to customers when they interact on inbound channels – turbo charged digital direct mail.
But decisioning is much more. You should view it as a new layer in your overall architecture. This allows you to react in real time to understand what has just happened in the customer interaction, and to work out what the ‘next best action’ should be to add value in this relationship.
It can do this not just once at the start of the interaction, but continuously throughout the process, responding as new data is captured, and so adapting and personalising responses to the customer accordingly.
One UK retail bank is using real time decisioning at multiple points throughout the online customer journey to do just this. Tens of millions of ‘decision points’ are generated daily and a combination of sophisticated business rules, self-learning adaptive models and real-time customer knowledge are working out what to do next.
It is really important not be introspective in seeking ways to apply decisioning most effectively. Banks and other organisations that are dipping their toes into this field should look to how other best practice service providers like Amazon or Facebook maximise the value of a customer’s precious time online. At Amazon, for example, decision-driven recommendation services such as a ‘customer like you who bought this, also then bought that’ have been incorporated up-front as an integral part of the customer proposition. Why not also apply something similar to financial services offers & messages?
2. Develop truly customer centred value management strategies and operating models
Secondly, you need to develop customer centred business strategies and a business operating model capable of driving the new ‘customer decisioning engine’ to unlock the full potential of the technology.
This calls for a very different mindset from traditional direct marketing. The biggest single constraint in use of direct mail, for example, is usually the cost per pack, which could be anywhere from 30-40p upwards. But once you’ve built a decisioning system using inbound digital channels, you have a new way to talk to customers with a potentially massive capacity (many millions of messages per day) and an ability to learn and respond in days not months.
Now the ongoing marginal cost per message for this new system is so low that it looks ‘free’ to the business, which is a massive temptation for any product manager with a target to hit and a need to drive sales! But nothing in life is free; it’s just that the constraints and costs are more subtle and not framed in terms of immediate spending. They are now set in terms of the customer experience. If you keep sending customers messages that are irrelevant and not engaging, they will quickly stop looking at them, seriously devaluing your new communication channel. So a practical lesson that needs to be taken is that you will need to think about the value of not saying anything at all when you don’t have anything useful or relevant to say!
So how does an approach based on working out the next best action for each customer, ‘one customer at a time’, affect your communication planning? For example, you may plan to use real time decisioning to deliver ‘Next Best Action’ within the ATM channel. But you must consider the context in which a customer is using these services, for instance, if there is a big queue for a given ATM on a Friday lunch time. Now the good news is that real time decisioning can support intelligent decision making about whether it is the right time or place to deliver a message in the light of the message type, queue length, time of day and ATM location.
You will also need to think cross channel in a truly customer centric way. If you’ve got a message that is relevant and interesting for the customer, perhaps you could use the ATM interaction as an offer to engage in another channel and at a time of the customers choosing, perhaps offering more information on SMS, or a web chat as you know they log-in online 2 or 3 times a week. Or if it’s a high value customer, perhaps a follow-up call from their relationship manager would be more appropriate?
This example demonstrates how you will need to think about ‘next best action’ elements of your communication strategies as ‘always on’ customer processes that are working for you 24/7. This demands a different approach to customer communication planning than the more traditional ‘campaign at a time’ methodology, but offers an ongoing and continuous benefits stream if you get the customer experience and process design right.
3. Continually test, learn and apply - quickly!
The third practical lesson is about using the inherent flexibility of a customer decisioning capability to continually learn how to make interactions as personal, relevant and effective as they can be.
A well designed decisioning system will have a ‘Test, Learn & Apply’ cycle measured in hours and days, not months and quarters. Combine this with the ability of a decisioning system to make messages truly personal and you have a potent combination. For example, which of these messages would be more impactful for you?
‘You could make more tax free interest next year if you moved some of the money from your current account into a Cash ISA’
‘John, you could make an extra £167.34 interest in the next 12 months if you moved the £5,000 you have spare in your current account to our new Cash ISA – press here to set up the account now’
Link decisioning with the ability of a best-in-class business process management system to provide immediate and simple execution process on a ‘straight through processing ’ basis and you have a foundation of a truly personal, relevant and effective offer that provides a great customer experience at low cost.
Consider also that the concept of customer next ‘best action decisioning’ is not restricted to digital channels, but should also form the basis of all customer communications, across traditional ‘batch’ channels as well as online, mobile, etc.
One great example of the effect of decisioning on a traditional channel is the printed Personal Annual Statement from a major UK retail bank. Within the booklet, next best actions are automatically generated to be personalised to the customer’s financial situation. For example, an easy to read graph might show that a customer has slipped into overdraft a couple of times recently due to a mortgage payment coming out before pay day. So, the next-best-action message for the customer would be to simply shift the mortgage payment date to avoid this happening in future.
So, customer decisioning is about more than just inbound or outbound marketing. It can help dynamically tailor the whole relationship based on delivering the best value for a customer right now in a way that’s also good for you.
It is inherently customer centric – working with each customer, one at a time, to work out what to do next to create value. And it can adapt to different roles in different channels, providing support to staff members when they are leading the interaction, or more pro-actively guiding a purely digital online or mobile interaction.
But remember – a customer next best action solution is a business strategy, not a technical deliverable. You will only maximise the value from a decisioning capability if you have the right customer value management strategies and business operating model to exploit the unique capabilities that an integrated customer decisioning engine can offer.
Tim Crick was head of customer contact architecture at Royal Bank of Scotland where he led several significant customer decisioning projects for the bank. He is now the managing partner at Decisioning Blueprints Ltd and can be contacted at firstname.lastname@example.org.