Understanding the Complete Customer Experience
How to control costs, enhance customer satisfaction and reduce customer defection, while also identifying opportunities to improve sales. Article by Myles Rose, vice president EMEA, ClickFox. 
Today’s businesses are faced with an urgent need to control costs, enhance customer satisfaction and reduce customer defection, while at the same time identifying opportunities to improve sales of products and services.
Historically, enterprises have invested millions of pounds in traditional siloed analytics tools designed to help to address these ever-increasing challenges by providing quantitative information about customer interactions.
Such solutions are good at answering traditional questions such as how many hits have there been on the company website, how many calls have been received over a given period, what is the average call length, or what is the busiest channel. However, they invariably cannot say why a customer has acted in a particular way in a given situation. More importantly, they consistently struggle to provide an understanding of what really was the customer experience.
The good news is that businesses can now gain these invaluable insights into the factors driving customer behaviour through a new approach known as customer experience analytics (CEA). CEA monitors and examines how customers interact across and within all touch points of an enterprise, typically including interactive voice response (IVR), web, CRM, agent desktops, point of sale and interactive kiosks.
This ability enables businesses to pinpoint bottlenecks in transactional flow, identify causes of costly opt-outs to live agents and uncover opportunities for extending automation, cost-savings or increasing revenues. Understanding what drives customers from one channel to another also gives businesses the power to maximise and change behaviour, optimising their most efficient channels while enhancing customers’ success and satisfaction and ultimately securing their brand loyalty.
Critically, it offers the most effective method available of turning customer behaviour insight into measurable customer service improvement.
Seeing the True Picture
One of the primary dangers of the traditional silo-ed approach to analytics is that data gleaned in this way can often be misinterpreted. For example, an analytics provider may provide logs that tell the business the number of people that accessed an IVR touch point and what percentage of those individuals subsequently took the option to contact a customer service agent.
If, for example, one million did the former and of those 600,000 went on to do the latter then the enterprise might reasonably infer that it had achieved a 40 per cent containment rate and that the same percentage of its customers had ‘self-served’ and were satisfied in interacting with the IVR system. In fact, this would be a dangerous conclusion to draw. Standard reporting tools are not able to show whether an individual customer was actually satisfied by his or her IVR experience.
In contrast, the best CEA systems will provide a ‘map’ that gives the enterprise a comprehensive view of their customers from the point they enter their systems to the point they leave. The insight that this provides allows businesses to pinpoint and address potential issues and problems with their customer base. They can now identify, for example, that a customer that was apparently contained within the IVR and therefore apparently satisfied, had in reality taken nine separate steps simply to enter his PIN number and had therefore left the system frustrated.
A Raft of Benefits
The best CEA systems are capable of providing enterprises with other far-reaching benefits. One of the most important of these is the ability to model the standard traversal routes customers take across the enterprise in a way that is easily understood by the business leaders within that organisation. As a result, those decision-makers can re-assess the way they have designed and deployed those systems, to ensure that they are running them in the most effective manner possible.
For organisations that are dynamically changing their offers either on their website or their IVR, whether they are up-selling, cross-selling or simply regularly releasing new services, CEA provides the ability to take a snapshot of how customers work through the system before and after the changes. Again, this ability to compare and contrast is beyond the capabilities of most traditional analytics systems.
The ability to use CEA to discover where each customer interaction goes right or wrong can be invaluable to any enterprise. It enables them to use the knowledge they have gained to fix issues and problems in their systems and processes and see immediate impact on their most crucial business drivers: operational costs, customer satisfaction, first-contact resolution, self-service completion, up-sell opportunity and customer retention.
Making Accurate Predictions
Another key advantage of this type of approach is that it provides a continuously-evolving dashboard view of the customer, capable of measuring his or her behaviour over time. This compares favourably with most traditional systems which provide a quantitative view of the customer experience and typically feature static historical data.
The ability to analyse customer behaviour and to build a behavioural DNA profile of each individual over time positions enterprises to move into the evolving area of predictive analytics. By monitoring customer behaviour, systems that have this capability can start to identify certain trends, not only in the behaviour of individuals but also in that of groups.
Businesses may find, for example, that 80 per cent of customers follow the same steps every time they go onto the system to pay their bills. This provides the opportunity to start dynamically changing some of the prompts and opportunities that they present to their customers, so cutting down frustration levels and enhancing the overall experience by enabling them to traverse the system more quickly and efficiently.
In the future, we are likely to see a growing focus on this area of predictability. ClickFox’s system has a recognition engine, which profiles the past and current behaviour patterns of each customer. By analysing these patterns, enterprises can effectively predict what customers are likely to do at any point in time and can therefore take action to streamline and enhance the experience they have.
Call Avoidance is not a Panacea
The encouragement of customer self service has become something of a mantra across the customer relationship management sector. And it is widely believed that this is all about call avoidance and the consequent reduction in the operational costs of a business. This focus has led to the emergence of customer-focused services like web-based self-learning lists of frequently asked questions, click-to-chat, or email services, for example.
However, an over-riding focus on call avoidance does bring with it certain problems. Enterprises inevitably make mistakes in the options they give to customers and the assumptions they have about the objectives of those customers. Only by tracking activity with the help of a CEA system, can they accurately deduce whether those assumptions are correct.
Using these systems also enables businesses to acknowledge the importance of customer interactions and the benefits of an automated approach to those interactions in terms of cost and efficiency. Critically, however, it also allows them to go ‘one step further’ by allowing enterprises to monitor and understand the interactive process and to become more proactive and more intelligent in the options they provide to customers as a result.
Building Loyalty and Reducing Churn
CEA systems can also play a key role in enabling businesses to build customer loyalty, reduce churn and improve the value of their customer base. The best CEA systems allow businesses to segment their client base and create a picture of activity and trend by client type, whether by chosen service option, age, or demographics, for example.
After a period of time spent observing behaviour, it will be possible to pool customers into different ‘buckets’ depending on the behaviour they have adopted. Specifically, in terms of customer loyalty, businesses can group those customers that have left the business and analyse the pattern of experiences specific to those customers.
By segmenting customers in this way, a business can configure its system to say, for example, if ‘customer A’ behaves in a certain way over a given period of time, then that particular customer is likely to defect.
So, if businesses want to improve customer retention figures they can use CEA to identify the key issues that drive them to leave. We believe CEA systems are well-placed to do this, because in our experience these issues invariably relate to service rather than product or price. This identification of similarities in the precise experience undergone by those customers that have subsequently defected will in turn help businesses redesign their customer service offerings to ensure that such problems do not re-occur in the future.
CEA – Positive Future Ahead
CEA really is a technology whose time has come. Today’s companies are using multiple channels and complicated paths to do business. Traditional reporting and analytics tools are not capable of identifying the ideal customer experience across all of these channels, nor can they tell businesses where they are effective and where they need to change.
The best CEA systems answer these questions by tracking the behaviour of individuals and groups over time, creating a visual view of the complete customer experience and providing actionable insights to drive key business decisions. For the customer, this means greater satisfaction: for the enterprise, enhanced levels of retention and, ultimately, higher levels of revenue.