We live in a world of big data, where endless amounts of information can be stored in the cloud at an ever-decreasing cost per byte of storage. While this may sound great to data-driven marketers, the blessing of cheap storage and increasingly simple application programming interface (API) connections between data sources can quickly enough turn into a curse of too much information and not enough time to sort through it all.
To overcome this, it is necessary to choose the right customer experience (CX) metrics. Part of this means that you need to choose data and performance calculations that are critical to your business’ key performance indicators (KPIs). In order to do this, it’s important to take into account the various types of metrics available to get a more holistic picture.
For instance, many of my clients are marketers. Thus, many of the metrics and data sources they are dealing with on a daily basis are marketing-driven. Whether they are indicators like website traffic or Social Media engagement, or conversion statistics on sales or registrations, solely looking at one type of data doesn’t give you a comprehensive view of the customer experience.
A good customer experience metrics system includes the following four components that span an entire organization, which we’ll review in detail below:
We will start with the broadest, and perhaps the most complex, type of metric. Operational metrics are the events and actions that happen to customers across their journeys and during their interactions, regardless of the channel (website, phone call, email, Social Media) or specific department (sales, customer service, accounting) they might be interacting with.
For example, operational metrics can often include some of the best performance-related measurements of what it’s truly like to be a customer. How long does it take an insurance customer to go through an entire registration or enrollment process when it might extend across multiple departments and systems? Or what is the average resolution time for a customer who calls to complain about their high-speed internet being unavailable?
Analyzing operational metrics can often be the best way to uncover cracks in a business process or disconnects between different teams because they often span disciplines and departments.
The biggest challenge with operational metrics is that, because they often span multiple systems, teams and potentially even categorization of data, it can often be difficult to implement a way to track them.
Subjective metrics demonstrate the perceptions a customer has about what happens and the effect this has on their overall experience and intent. They are often measured either immediately after or closely following a transaction such as a purchase, customer service inquiry or other interaction with a brand. Their aim is to capture a customer’s feelings and impressions as close to “in the moment” as possible.
For example, the Net Promoter Score (NPS) is a great way to measure a customer’s subjective opinion about their experience. By using a simple set of questions, companies can measure consumers’ feelings about an interaction or process and compare those in the aggregate to relative timeframes. Understanding year over year (YoY) or even quarter over quarter (QoQ) trends in your NPS can highlight how changes and modifications in your customer experience have affected customer satisfaction.
Subjective metrics are relatively easy to measure, with many simple survey tools readily available to do so. While not the only indicator of your customers’ satisfaction, subjective metrics cover extremely useful information that is easily gained. They shouldn’t, however, be used as the only measure of success because they can often be an immediate emotional reaction to an experience. Mixing them with more objective metrics provides a more comprehensive view.
The actions customers take as a result of their experience and perceptions are defined as behavioral metrics. Unlike subjective metrics, these are objective and observed by either built-in or proprietary reporting platforms on channels that customers interact with. They can range from digital platforms like email communications to other offline systems such as call center tracking.
For example, website analytics are a great way to measure customer behavior on that channel. By measuring both individual behavior, as well as the behavior of users as a whole, companies can quickly and easily get a good understanding of how their website is performing at a macro and micro level.
Behavioral metrics are relatively easy to measure, though they are often measured in the aggregate and not on a customer-by-customer basis. There is value in measuring both, but companies should strive to get as much individual customer metrics as possible to truly analyze individual experiences and pathways.
We will end with the type of data that most clearly gives us a sense of the health of an organization and how well we are executing our strategy. Business metrics can be defined as how customer actions impact your business strategy and goals.
For example, business metrics would measure the number of new car buyers over the course of a year or the number of marketing qualified leads (MQLs) that become sales qualified leads (SQLs) per quarter.
Similar to operational metrics, business metrics can often span disciplines and departments but are incredibly valuable to an organization. This is simply because business metrics are the most directly tied to the financial performance of the company.
A diverse set of customer experience metrics will give your organization a more comprehensive understanding of where critical issues are, where there is room for improvement and where you are currently successful. Using these four types of metrics in a comprehensive measurement system will give you the best possible view of the performance of your customer experience.