In recent years, researchers have created a number of metrics to explain the connections between customer behavior and growth. But under the harsh reality of the marketplace, these efforts have generated more smoke than heat. Nevertheless, managers continue to search for insight into how customers feel – and how they will behave.
In recent years, researchers and consultants have advanced a number of customer metrics to explain the connections between customer behavior and growth. But these efforts have generated more smoke than heat. Despite claims to the contrary, the authors argue that the most popular metrics have shown only modest correlations to growth. None of them have shown themselves to be universally effective across all competitive environments.
Early customer metrics tried to explain why people buy. To many companies, it came down to marketing. Yet, as the authors explain, the issues that affect customer loyalty are complex and go beyond standard marketing. This gave rise to a new category of metrics aimed at understanding the customer experience. Although managers have learned a lot about the components of service quality (including reliability, responsiveness and empathy), the approach doesn’t point managers to specific actions they can take. Beginning in the 1990s, many managers began paying closer attention to customer retention — in particular, understanding what makes for dissatisfaction and satisfaction. But as the authors note, the linkages among satisfaction, customer behavior and positive financial outcomes have been modest.
Today’s most popular metric, the Net Promoter Score, focuses on how customer word of mouth — both negative and positive — can advance growth. Developed by Bain & Company Inc. consultant Fred Reichheld, it claims the ability to predict future growth from customer replies to one question: “How likely is it that you would recommend this company to a friend or colleague?” The authors found that the linkage between the Net Promoter Score and subsequent customer behavior was modest at best; models based on multiple variables consistently outperformed models based on Net Performer. The authors are skeptical that there can be a single metric that reduces complex, multifaceted constructs to one or two dimensions; if there is, they write, “there’s a good chance it will ignore one or more important aspects of the equation.”