For years, big businesses and top brands have relied on the Net Promoter Score (NPS) as the key metric to measure customer experience and satisfaction. Recently, however, experts are challenging the validity of this longstanding metric and looking for more accurate ways to gauge customer satisfaction.

This past May, the Wall Street Journal published an article entitled “The Dubious Management Fad Sweeping Corporate America” which claimed that companies who swear by their Net Promoter Scores are misleading themselves by depending on the outdated survey method. Since then, many customer experience analysts have weighed in – saying that the time has come to move on from NPS and utilize better, smarter tools that provide more reliable results.

What is the NPS? 
The NPS is a widely-used, one-question survey that companies administer to measure customer satisfaction, loyalty, and growth.

Originally proposed in a Harvard Business Review article in 2003, the standard NPS question asks, “How likely is it that you would recommend [company name] to a friend or colleague?” Respondents are given a scale ranging from 0 - 10, with 0 labeled as “Not at all likely,” and 10 labeled as “Extremely likely.”

Respondents who submit a 9 or 10 are considered “promoters,” 7 or 8 are “passives”, and 0 -6 are “detractors.” The actual score is defined as the percentage of promoters minus the percentage of detractors. 

That’s it. Pretty simple really. And that’s been part of its allure. The NPS has been a quick and easy way to determine how satisfied customers are with a business, and perhaps that’s why it’s become so popular.

What’s Wrong with It? 
Senior Data Scientist, Brian Weinstein, wrote in a recent Medium article that, “The phrasing of the NPS question, the measurement scale it uses, and method of calculation all go against the basic principles of survey sciences.”

Specifically, experts have cited some of the following issues with the NPS:

• It asks people to answer based on a hypothetical future instead of actual experience. A question such as “Have you recommended our company to a friend or a colleague in the last 6 weeks?” can be answered more accurately than one that asks what you are likely to do in the future.
• The rating scale is complex and imprecise. The difference between a 6 (detractor) and 7 (passive) is unclear, for example. A binary yes/no response or one with 5 possible responses instead of 10 would greatly increase the accuracy of the results.
• What people say and do are often two very different things. Instead of relying solely on what people self-report, a good measure of customer satisfaction must take behavior into account.

Back in 2003, when businesses didn’t have the wealth of customer data they do now, depending on customers to answer one general question might have made sense. But today, we can go beyond that. 

With the technology now available, we can dynamically create intelligent surveys based specifically on a customer’s individual experience. These surveys can provide much more comprehensive insights for data-driven decisions in the organization. 

What Should You Use Instead?
According to a study by Walker Information, customer experience will overtake price and product as the key brand differentiator by 2020. This means that you need to not only offer great customer experience, but also have a reliable way to measure it.

Here are some metrics that may give you more accurate results than the NPS.

• Customer Effort Score (CES) – the relative amount of effort required by the customer to do business with a brand. 
• Customer Satisfaction Score (CSAT) – a survey determining satisfied your customers are on a numerical scale, e.g. 1 to 5.
• Customer Journey Mapping – a visual portrayal of the customer’s experience, identifying key interactions and pain points that the customer has with your company.
• Customer Lifetime Value (CLV) – the total worth of a customer to a company over their entire relationship. 
• Referrals & Reviews – While NPS is a measure of how many people say they would recommend you, tracking real referrals and reviews will tell you how many actually did. 

Many of today’s customer intelligence solutions allow you to create your own queries about your data and customize your reporting, so you can determine for yourselves what constitutes customer satisfaction and loyalty within your business and industry.

With the rise of AI, machine learning and predictive analytics, your knowledge about your customers (who they are, how they behave, and how loyal they are to your brand) should go far beyond the results of a one-question survey. Take advantage of the advances in customer intelligence to offer the best customer experience.

AfterWords is an intelligent customer satisfaction software that delivers the most relevant questions for the most relevant responses. We provide actionable data where you need it the most. To find out more, please contact us.