How to Get Customer Feedback Without Asking the Customer

This article originally appeared on The Wall Street Journal's The Experts.

Customer-feedback surveys are everywhere: at the bottom of cash-register receipts, at the end of phone calls with customer-service reps, and clogging the email inbox. Recently, I saw an electronic touch screen in an airport bathroom, soliciting my impression of cleanliness.

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This barrage underscores the importance that many companies now place on customer experience. But it has diminishing returns, as many people don't want to answer more surveys. No wonder that response rates have been declining for years. Yet without feedback, how can companies keep in touch with their customers' needs and priorities?

Increasingly, companies obtain feedback without even asking a customer. Advanced analytics, applied in the right ways, can foster customer intimacy by using digital interaction data to remember, interpret and enhance the interactions. Some firms, for instance, parse what happened during a customer encounter in order to experiment with different service methods or product offers. Others send tailored offers or recommendations, based on predicted customer behavior and on inferences about the most effective timing and channel.

Still another use of analytics is to forecast a customer's future behavior. One telecommunications carrier, for instance, built a statistical model to identify the key causes of customer attrition. The company populated the model with characteristics and behaviors of customers who canceled their service, ranging from their calling patterns, to their worth to the company and what happened during recent interactions before they left. The model narrowed the field of potential reasons to a few that really mattered. It unearthed an interesting insight: When one customer defects, other customers in her calling circle also tend to cancel their accounts. The company now can identify customers at risk of attrition much earlier in the process, and then enhance service to earn their loyalty. Reducing churn in the telecom business pays off heavily.

For large companies, advanced analytics offers one defense against threats from digital startups. Despite the popular view of incumbent companies as lumbering behemoths unable to deal with disruption, incumbents have a hidden edge over the upstarts: the data and history they amass about large numbers of customers. They also have the scale and resources to support and fund such analytics.

Consider the experience of a service provider in China with more than 400 million users. The terabytes of data generated by all those transactions give this company a huge information advantage. Matching the data it collects on those transactions with the mobile app ratings from its customers allows the company to create predictive models that show which types of experiences typically delight customers, and which types annoy them.

As a result, the company does not need to ask all its customers for feedback. Instead, its computer models generate a rating score for almost every transaction. Those predictive scores match up reliably—more than 80% and improving—with what customers say in traditional feedback.

Analytics gives the company two advantages: It provides almost instantaneous modeled feedback to employees, and it instantly identifies situations with some need for relationship or service recovery, triggering an intervention. If the algorithms identify a delay or other problem, the company can issue an apology or a credit. If things went especially well, then the app can prompt the customer with ways to tell friends about the service's benefits.

Advanced analytics is not just the cool new thing. Large firms have copious customer data, and the ones that figure out how to use this new form of scale advantage often can outmaneuver their smaller competitors.

James Allen is co-leader of the global strategy practice at Bain & Co. and co-author of The Founder's Mentality.