While customer acquisition is a critical parameter for any business to grow, neglecting current customers in pursuit of new ones can have a damaging impact. Developing and maintaining a loyal customer base can generate long-term business growth: retaining customers can lead to savings on customer acquisition costs, as current customers already know your products and, according to research, 60% of customers would tell a friend or family member about a brand they are loyal to. Loyal customers are also more likely to join loyalty programmes and spend more on products, even when offered equivalent and lower priced products by competitors.  

Having leaks in the customer pool, also known as customer churn or attrition, should therefore be a grave concern for any business. There exists a wide body of research devoted to analysing customer switching behaviours, and churn prediction focuses on spotting customers who are likely to discontinue the use of a service. Among the plethora of factors that could make a customer churn, it is widely accepted that dissatisfaction with the service they have received is a key driver. Targeting the causes of this dissatisfaction is therefore at the core of developing churn prevention or customer retention strategies. 

When talking about customer loyalty, the discussion naturally turns to the Net Promoter Score (NPS). As a customer sentiment metric, NPS has taken the world by storm since its introduction in 2003, offering an attractive ratio of relevance to simplicity, and has been adopted by two-thirds of Fortune 1000 companies. The question asked is simple: 

NPS provides a straightforward metric for tracking customer advocacy, then, acting as an indicator of customer satisfaction and loyalty as well as giving information on a company’s reputation versus its competitors. But is NPS a good predictor of customer retention? Surely it makes sense to think that loyal and satisfied customers are less likely to churn and more likely to establish a long and fulfilling relationship with a brand. 

In fact, there might not be a straightforward relationship between NPS and customer renewals: as self-reported NPS at a given point is subject to many biases, it might not by itself be useful for reliably forecasting renewal revenue for an individual organisation. Differences in how, when, and from whom results were obtained can also determine the quality and direction of results, even if in general companies with higher NPS scores experience lower churn rates. One example of a company with a high NPS and high customer retention is Amazon. According to CEO and founder Jeff Bezos the company reached 200 million subscribers in its Prime membership program worldwide in 2021. Research shows that up to 70% of customers who sign up for a trial membership convert to paid membership and it is estimated that 93% of consumers renew their paid membership after one year, with the retention rate going up to 98% after two years. Another example can be found in Netflix. The streaming service has developed a loyal customer base over the years, and most of the customers that pay for Netflix do not subscribe to other streaming services.  

In recent years there has been an increasing consensus among customer satisfaction experts that it is risky to rely on a single metric to measure customer loyalty, and a consequent increasing interest in multidimensional or hybrid approaches that combine demographic, behavioural and attitudinal customer data. By itself, NPS does not give insight into why customers are happy or unhappy, it tells us nothing about actual customer behaviour nor does it provide any insight into return on investment. But simply asking a follow-up question such as “Why did you give the answer that you gave?” can offer deeper insight. If an organisation wants to learn why its customers churn, the answer may well lie in this kind of textual feedback. By mining this written feedback, organisations may be able to spot and classify complaining, neutral and satisfied customers with greater accuracy. All this information can be used to develop targeted customer retention strategies, the effect of which can then be rapidly assessed at many points along the customer journey via NPS.  

Moving from the aggregate to the individual level, NPS offers a fast and straightforward way of identifying unsatisfied customers. Scores correlate to how satisfied customers are with the service or product at the time of asking the question, so if it is possible to reach out and act almost immediately, through strategies implemented by customer services teams, companies can attempt to win back dissatisfied clients or mitigate negative word-of-mouth before it occurs. 

In conclusion, NPS alone is not a good predictor of customer retention and does not give many valuable insights into churn. A hybrid multidimensional approach combining demographic, behavioural and attitudinal data can provide a more accurate measure of customer loyalty than a single self-reported loyalty metric. The real value of NPS comes from quantifying the effects of individual elements of the customer journey, such as experienced pain points or channels of contact, and from enabling organisations to act quickly to address issues. To gain insight on churn, looking at customer spending patterns and verbatim feedback is an effective way to identify customers who may churn and unveil drivers of attrition.