The majority of banks state that they have been transforming from a product centric towards a customer centric organization. As a result banks have initiated many programs that focused on customer experience (CX) improvement.
So while the importance of CX is generally understood throughout the bank’s organization and improvements are usually measured in terms of e.g. NPS or customer satisfaction, it yet remains a challenge to quantify the value of CX. This undermines the ability of banks to make responsive decisions in order to optimise journey performance from both a customer and economic perspective.
In many phases and corresponding touchpoints of a customer journey banks either under-deliver, missing out on potential revenues, or over-deliver, wasting money. The additional challenge of customer experience is that customers keep comparing with their last, best, experience and thus the customer expectations are a moving target. This requires banks to have continuous insights in the customer journey performance, to focus investments on the most relevant improvements.
To find exactly that balance where investments and customer expectations are aligned, KPMG has developed the CX Economics solution. In a recent Proof of Value of this CX Economics solution, performed for a logistics company in The Netherlands, clear examples of both over- and under-delivering were highlighted. It turned out that more expensive delivery methods don’t necessarily lead to a higher customer satisfaction and that the vast majority of customer service contact leads to both a high additional cost ánd a significantly lower customer satisfaction.
The main challenge of quantifying CX usually originates from siloed departments and responsibilities. In the aforementioned Proof of Value we had to discuss the Customer Journey with one department, receive data on customer satisfaction from another , whilst cost- and contribution related data were delivered from yet other departments. With CX Economics we were able to combine this data, link it to each phase in the selected Customer Journey, and provide a new level of cross-silo insights to the company that allowed them a new foundation for decisions.
So let’s focus on the banking Customer Journey ‘Buying a home’. Most of the banks would have journeys that consist of the phases ‘I want a home’, ‘I buy my home’, ‘I own my home’ and ‘I sell my home’, with additional detail levels to describe the touchpoints and emotions for each sub-phase.
To quantify CX we add additional measurements to each of the touchpoints – when creating the Customer Journey, but also in a dashboard to continuously give all relevant departments and functions insight in the end-to-end journey performance. Going back to the example of the Customer Journey ‘Buying a home’ one could think of the touchpoint ‘complete mortgage application’ and gather more data around this. Some examples could be: What is the cost to serve a customer in this touchpoint, per channel? And what are the volumes per channel? What is the customer satisfaction per channel? What is the conversion rate; average per client, and zoomed in per channel? And what is the financial contribution; average per client, and zoomed in per channel?
We experienced that linking these measurements to the individual Customer Journey touchpoints, and visualizing them in a dashboard, brings great value to organizations as it aggregates measurements across multiple departments thus providing insights into previously unclear relationships.
Once the aggregated customer satisfaction, cost and contribution measurements are in place and related to the relevant touchpoints, the next step of scenario analysis becomes relevant. As a first step this could be done to verify common hypotheses that many organizations take for granted but have never been fact-based verified. In the previously mentioned Proof of Value at a logistics company the common assumption was that the most costly delivery method would result in the highest customer satisfaction. This turned out to be not true – opening a whole new perspective of more economical delivery options without compromising customer satisfaction.
In the case of the Customer Journey ‘Buying a home’ one could think of hypotheses that confirm the link between the advisor, customer satisfaction and financial contribution, the link between cost to serve and financial contribution or the link between digitization and conversion. Of course these would all be foundational hypotheses. The more data is integrated in the CX Economics solution, the more it becomes possible to convert from hypotheses to scenario’s. This allows banks to create sensitivity analysis that give insights in the optimal balance between CX and cost (cost to serve, channel costs) and/or contribution.
Examples of Analysis SKU Charts list for sensitivity analysis
Many banks have created Customer Journeys for the main journeys. They also gather a lot of data about customers and their banking interactions. CX Economics allows banks to link the Customer Journeys touchpoints with the available data to steer on end-to-end journey performance and improvements across teams.
Authors of this blog post are Nienke Wichers Hoeth, partner Customer & Brand Advisory, Leonie Vervelde, manager Customer & Brand Advisory and Kay van der Vleuten, senior consultant Customer & Brand Advisory.