Quantifying the Customer Experience: Easy as 1-2-3
| Published: August 21, 2014 | Comments
Quantifying the customer experience is a challenge—one that can pay off with huge dividends when done correctly. But what is the correct strategy for tracking your customer’s experiences? One strategy we suggest is the 1-2-3 approach:
1 Goal of collecting data that lead to meaningful action.
2 Practices for determining what to measure and when to take those measurements.
3 Metrics to track: customer satisfaction, effort, and loyalty.
In the sections below we’ll explore each aspect of the 1-2-3 approach in greater detail.
One action-focused goal for your data
Let’s first consider your goal, which we suggest should be to collect data that lead to meaningful action. How do you know when you have meaningful, actionable data? The answer lies in your ability to fill in the following sentence:
The ________ data can be used to ________, which helps our organization ________.
For example, at Zendesk, Net Promoter Score® (NPS) data can be used to identify opportunities for improving customer service, which helps our organization increase customer retention.
Two practices to employ when thinking about measurements
There are two key ways to think about measuring the customer experience, and it can be helpful to put blinders on and ask these questions one at a time.
What are you measuring?
Knowing exactly what you’re attempting to quantify is the first step in accurately quantifying it. This step is known as “identifying your construct of interest.” The customer experience is a complex phenomenon, so we need to measure a full range of constructs in order to fully capture it. Typical constructs of interest include transactional customer satisfaction, customer effort, and customer loyalty.
If you’re measuring how satisfied or dissatisfied your customers are with a narrowly defined experience, such as an individual customer support interaction, a simple up/down customer satisfaction measure is appropriate. Yet that same up/down satisfaction measure will not be sufficient with a more complex question, such as measuring customers’ perceptions of the effort they expend when interacting with your organization.
Likewise, if you’re interested in measuring a very broad experience construct like customer loyalty, you’ll need to collect attitudinal or behavioral data that help predict loyalty, including measures of customer commitment, retention, or recommendation likelihood.
When are you taking these measurements?
It’s also important to recognize the need for measuring your constructs of interest at the appropriate times.
For example, asking a transaction-based customer satisfaction question is appropriate in the early stages of a customer’s time with your organization whereas a question about customer effort is more effective after a customer has interacted with your organization multiple times, or with multiple teams (e.g., customer support, sales, and billing). Similarly, asking loyalty questions too soon can be off-putting to customers, and will generate data that are not ultimately useful.
Three voice-of-the-customer metrics to track
Now let’s talk about the actual metrics. Rather than focusing on a single slice of the complex phenomenon of customer experience, here’s why the three metrics we’ve been talking about are valuable.
Customer Satisfaction. Customer satisfaction can be a global measure, where you ask your customers how satisfied or dissatisfied they are with your organization in general, or transactional measures, where you ask your customers how satisfied or dissatisfied they are with their experience during an individual customer support interaction. Transactional measures, in particular, give you simple up/down scores.They are quick and easy for the customer, are easily communicated to support staff, and can be systematically tracked by management. For example, the Zendesk CSAT measure asks customers “How would you rate the support you received? Good, I’m satisfied or Bad, I’m unsatisfied.”
Customer Effort. Customer effort contrasts customer expectations with their actual experiences. For example, customers can be asked, “How much effort did you personally have to put forth to handle your request?” followed by “How much effort did you expect to put forth to handle your request?” Both questions should use the same answer scale, such as “0 - None at all, 1 - A little, 2 - A moderate amount, 3 - A lot, 4 - A great deal.” Using this approach, a customer effort score (CES) can be calculated by subtracting the response from the first question from the response to the second question. A CES score of 0 reflects a perfect match between customer expectation and experience, whereas CES scores of -4 and +4 reflect the largest mismatches. A score of -4 indicates the greatest effort was expended when no effort was expected and a score of +4 indicates no effort was expended when the greatest effort was expected. Aim for scores of 0 to +4!
Global Customer Loyalty. Loyalty measures can provide high-level snapshots of customer commitment, retention, or recommendation. For example, the Net Promoter Score® (NPS) question is a popular measure used to predict customer loyalty. The NPS question asks something along the lines, “How likely are you to recommend our organization to someone you know?” Respondents rate the organization on an 11-point scale from 0 for Not at all likely to 10 for Extremely likely. Generally, loyalty questions are best asked at least 3 or 6 months into the customer lifecycle, and at intervals of at least every three months or longer.
1, 2, 3, and 4
Now that you’ve set your goal, decided on the appropriate constructs and timing, and have chosen your metrics, it’s time to collect your data and take action. To learn more, join Zendesk at the ICMI Contact Center Demo & Conference, where we will dive into MindBody’s data to see how they used these metrics to drive decisions that have led to exponential growth at their company.
Metrics, Customer Experience
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