Customer mindset metrics: A systematic evaluation of the net promoter score (NPS) vs. alternative calculation methods

Sven Baehre, Michele O'Dwyer, Lisa O'Malley and Vicky M Story

Journal of Business Research, 2022, vol. 149, issue C, 353-362

Abstract: The Likelihood-to-Recommend (LTR) question is a well-established marketing accountability metric that forms the basis of Net Promoter Score (NPS). NPS has been claimed to be a superior predictor of sales growth, which has led to widespread managerial adoption. However, academia criticized the NPS calculation because it sets arbitrary cut-off points, excludes parts of the sample, and collapses the scale into three categories; leading to calls for its abandonment. Our study explores these criticisms by systematically comparing NPS with six alternative calculation methods based on the LTR question (including alternative NPS calculations, LTR ‘top-box’, and average metrics) using 193,220 responses for seven sportswear brands. The study establishes that while NPS performs well in a comparative assessment of calculation methods, ‘top-box’ metrics perform better, undermining claims that NPS is the one number managers need to grow. In practice, managers could continue to use NPS, but there are better alternatives.

Keywords: Net Promotor Score (NPS); Likelihood-to-recommend; Calculation methods; Customer mindset metrics; Marketing performance; Marketing accountability (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:149:y:2022:i:c:p:353-362

DOI: 10.1016/j.jbusres.2022.04.048

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