Consumer’s expectations for a better customer experience are rising. Research shows that 86% of people will stop doing business with a company because of a negative service experience—with 51% of consumers giving companies only one chance. To differentiate from competitors and provide exceptional customer service, businesses need to elevate the customer experience. But to do so requires insight into which processes are working and which are not.
Data can provide these types of insights and drive positive transformation. The challenge, however, is not just in collecting the right type of data, but knowing how to pull insight from it. What data points are important? Which are not?
Determining the Type of Data You Need and Where to Find It
Contact centers, where agents interact directly with customers, provide a gold mine of customer intelligence. Each interaction is an opportunity to learn more about consumers in order to improve the customer experience. Typically there are three types of data you will want to collect:
Volume Data – Contact events are signs that something isn’t easy for customers to solve on their own. Knowing why customers contact you, by what channels, and with what frequency is key to understanding what they are trying to accomplish and where it is difficult. Look at average handle times, rates of repeat contacts, escalations, and transfers to determine where there are breakdowns in the contact experience that may be negatively impacting your customers and your business.
Behavioral and Emotional Data – This type of data measures how your agents handle each customer and how customers respond to the interaction. The data collected should include attributes such as communication and interaction skills, compliance, and product and procedural knowledge.
Outcome Data – It’s important to be able to predict and replicate success. Outcome data tells you how frequently you are successful in meeting your business objectives once the interaction is over. For example, completing a sale, avoiding a cancel, or gaining a high customer satisfaction rating are all positive outcomes you want to replicate.
It is also critical that your data captures interactions that occur across all channels so you can connect the pieces of the journey and understand which events trigger or prevent others.
Finding Insights within the Data
Now that you have collected a substantial amount of data, how can you use it to find insights into the customer experience? A recent Harvard Business Review article highlighted seven categories of insight to look for when seeking transformation. Here’s a look at those categories translated into the context of customer experience analytics:
Anomalies – Look at places where the result deviates from the norm. These statistical anomalies can identify areas of potential breakage in the customer experience.
Confluence – Identify where trends, such as economic and social (e.g., consumer spending habits and mobility trends), intersect with each other. The confluence of these trends can reveal new insights or opportunities.
Frustrations – Processes that result in poor outcomes, higher escalation rates, or frequent complaints from frontline employees can pinpoint areas where resolution may be cumbersome or ineffective.
Orthodoxies – Question any beliefs or assumptions that are not supported by correlative data. “How it has always been done” is not always the most effective way.
Extremities – Look at your outliers. Observing contacts with strongly positive outcome data compared with those in similar situations with strongly negative outcome data can help you determine what differentiates a poor outcome from a positive one.
Voyages – Allow the data to build a history or timeline that you can replicate and immerse yourself in. From it you can glean contextual insights that help you understand which sequences of events culminate in positive or negative outcomes.
Analogies – What you borrow or learn from the patterns and benchmarks of your competitors and other companies can enlighten your own business processes.
The discoveries you make from your data can inform how you coach and develop your employees, how you program your interactive voice response, what tools you use, and how you evaluate and reward your employees and customers.
Applying Insights to Drive Transformation
To effectively apply the insights gleaned from the data to create transformation, you must make it digestible to those who have the ability to make change or alter course based on the findings. This effort requires collaboration and coordination across departments. It should make the translation from “What does it say?” to “What does it mean?” so the cross-functional team can determine what to do about it.
When presented in these terms, the insights allow customer experience executives to not only clearly define what is going wrong (or right), but also to quantify the costs of problems—and any required remediation. Thus, business decisions become easier to make and to justify, and thereby speed up the transformation process and allow your business to remain competitive.
