Customer experience (CX) leaders are called upon to lift customer loyalty, which, of course, means they have to measure loyalty. There are two broad ways to measure customer loyalty: Attitudinal measures and behavioral measures. Too often, CX leaders lean on one or the other, but delivering reliable CX results requires both.
Attitudinal measures are used to understand how customers feel about your brand. You collect attitudinal data via Voice of the Customer (VoC) surveys that ask about the customer’s satisfaction, likelihood to repurchase, or willingness to recommend.
Behavioral measures are used to measure if customers are acting on their feelings of loyalty. You measure behavioral loyalty using transactional and sales data. Do my customers continue to purchase? What is their purchase frequency or average order amount? At what rate to I retain or churn existing customers?
Many organizations believe that behavioral measures are most important. After all, what good are customers who feel loyal if they don’t act on that feeling? In the end, you take behavioral measures of loyalty to the bank–it is nice to get a high Net Promoter Score, but it’s customers’ behaviors that provide the dollars that drive business results.
But while behavioral measures are vital, there is considerable risk in relying on these transactional measures in the absence of attitudinal data. Repeat purchases may look like loyalty, but they can be driven by factors that are not related to customers’ feelings of brand loyalty. People may repeatedly buy out of habit, because of limited competitive options, for convenience, or because your brand offers the lowest price. A brand focused only on behavioral loyalty metrics may gain false confidence that all is well because customers are repurchasing, only to learn how little loyalty the brand earns when it tries to raise prices or a better, more-convenient or lower-price competitor enters the market. Behavioral measures tell you what customers are spending, not what they feel toward the brand.
The taxi industry offers a recent and compelling example of the risks of relying only on behavioral measures of loyalty. For decades, taxi companies owned the on-demand transportation market. Protected by regulation, they were the only option for travelers and urban residents in need of a quick ride. No one liked taxis, but they used them, so the industry’s behavioral loyalty looked great—until Uber and Lyft entered the marketplace. Customers who felt no loyalty to taxis rapidly shifted to the new entrants. Had taxi companies collected attitudinal measures of loyalty and addressed the reasons for customer dissatisfaction, the industry might have enjoyed stronger customer relationships and mounted a more effective defense against the upstart network transportation companies.
Another problem with leaning on behavioral measures is that this data is a lagging indicator. Using purchase data to measure loyalty, you can only measure a lost customer after they’ve left. As a result, behavioral loyalty data can let you know if your retention rate is declining, but it isn’t predictive of what you can expect in the future, which customers may be next, and why they are abandoning your brand.
Behavioral data may be closest to the dollars and cents of business, but attitudinal loyalty data (quantitative survey data appended with qualitative research) is even more powerful for understanding customer perception, feelings of loyalty and emotional bonds, and what adverse factors can be addressed today to reduce customer churn in the future. Smart brands use their VoC survey results to identify which customers are most at risk and target them for unique retention and recovery efforts, helping to improve loyalty and reduce turnover.
When measuring loyalty, smart CX leaders don’t lean on one kind of measure over another. By collecting and analyzing both behavioral and attitudinal loyalty, you are best prepared to identify likely causes of customer churn while also measuring the financial costs and benefits of delivering better customer experience.