Brooklyn

March 5-6, 2019

Brooklyn
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Does Understanding of the Net Promoter Score Calculation Lead to Score Inflation?

Room 5 | 9:15-9:45 | Wednesday, March 6, 2019

The Net Promoter Score (NPS) has gained significant traction as a measure of customer sentiment and is being extended in large enterprises to measure employee sentiment of internal applications, Web sites, services and even employee engagement. This internal study of a large enterprise ecosystem serves as an indicator of the possible effects of increasing awareness and understanding of NPS, not only with an enterprise but in the marketplace overall.

To measure sentiment via NPS, respondents are asked to provide a Likelihood to Recommend (LTR) rating on a scale from 0 (not at all likely) to 10 (extremely likely). Respondent ratings are converted to one of three categories: Detractors (percent of 0-6), Passives (percent of 7 and 8) and Promoters (percent of 9 and 10). A single score is calculated by subtracting Detractors from Promoters.

We found, via three independent studies within the ecosystem of a large enterprise, that as survey respondents’ understanding of the NPS calculation increases, there is subsequent score inflation over time. Some respondents that self-report knowledge of the NPS calculation adjust their scores to 9 or 10 so that their ratings are counted as Promoters. Our findings have implications for the use of NPS and user sentiment benchmarking where accurate trending of scores may be impacted by score inflation. In this presentation we’ll give an overview of the NPS metric, findings from three successive independent surveys, concerns about score inflation and recommendations for further actions.


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