Identification of Key Drivers of Net Promoter Score Using a Statistical Classification Model

Abstract

Net Promoter Score (NPS) is a popular metric used in a variety of industries for measuring customer advocacy. Introduced by Reichheld (2003), NPS measures the likelihood that an existing customer will recommend a company to another prospective customer. NPS is derived from a single question that may be included as part of a larger customer survey. The single question asks the customer to use a scale of 0 to 10 to rate their willingness and intention to recommend the company to another person. Ratings of 9 and 10 are used to characterize so-called ‘promoters,’ ratings of 0 through 6 characterize ‘detractors,’ and ratings of 7 and 8 characterize ‘passives.’ The NPS is calculated as the percentage of respondents that are promoters minus the percentage of respondents that are detractors. The idea behind the labels given to customers is as follows. Promoters are thought to be extremely satisfied customers that see little to no room for improvement, and consequently would offer persuasive recommendations that could lead to new revenue. The passive ratings, on the other hand, begin to hint at room for improvement and consequently the effectiveness of a recommendation from a Passive may be muted by explicit or implied caveats. Ratings at the low end are thought to be associated with negative experiences that might cloud a recommendation and likely scare off prospective new customers. Additional discussion on the long history of NPS can be found in Hayes (2008). Some implementations of NPS methodology use reduced 5-point or 7-point scales that align with traditional Likert scales. However it is implemented, the hope is that movements in NPS are positively correlated with revenue growth for the company. While Reichheld’s research presented some evidence of that, other findings are not as corroborative (Kenningham et al., 2007). Regardless of whether there is a predictive relationship between NPS and revenue growth, implementing policies and programs within a company that improve NPS is an intuitively sensible thing to do [see, for example, Vavra (1997)]. A difficult and important question, however, is how to identify key drivers of NPS. Calculating NPS alone does not do this.