The Value of Different Customer Satisfaction and Loyalty Metrics in Predicting Business Performance

The authors used 80 publicly traded companies from 1994–2000 in the ACSI database. The authors computed six performance statistics: Tobin’s Q (a company’s market value relative to replacement cost); net operating cash flows; total shareholder returns (TSR); 12-month sales growth; gross margin; market share (all using log transformations).

The authors constructed six customer feedback metrics:

  1. Average ACSI scores (which correlate r = .9 with single satisfaction measures).
  2. Top 4 box satisfaction (7–10)—which the authors call top-two box from a five point version.
  3. Proportion of customers complaining (two items from ACSI).
  4. Net Promoters: Authors used two ACSI items but somehow claim this was the Net Promoter. Unlike other articles which use ten-point or four-point scales, or have slightly different wording, these two items seem at best only slightly similar to the likelihood-to-recommend item: “Have you discussed your experiences with [brand or company x] with anyone?” and “Have you formally or informally complained about your experiences with [brand or company x]?” Their Net Promoter was calculated as % discussing minus % complaining.
  5. Repurchase likelihood: “How likely are you to repurchase this brand/company?”
  6. Number of recommendations: “With how many people have you discussed [brand or company x]?”

The authors found that these attitudinal metrics explained between 1% (TSR) and 16% (market share) of variance in business metrics. Average satisfaction and top-two-box satisfaction accounted for the most explanatory power: 5% for net cash flow and 16% for market share.

Repurchase intentions were significant for four of the six business metrics at similar levels of R2.

For the number of recommendations, the average R2 explained from 1% for TSR to almost 12% for Tobin’s Q (only significant for gross margin and market share). For their NPS question, none of the correlations were statistically significant at p <.05. The authors stated in no uncertain terms that there’s no relationship between NPS and the business metrics.

Their study also found no correlation between recommendation behaviors and the two attitudinal customer satisfaction metrics, which is different than the other studies (e.g., East, 2011, Keiningham et al., 2007) and our analysis.

In a later paper, Morgan and Rego 2008 showed that their version of the NPS correlated very highly with the more familiar version. However, given the authors found very similar correlations with other satisfaction measures, it’s hard to know if using the LTR item would have also resulted in significant correlations for predicting future growth metrics.

Takeaway: The NPS question(s) used in this analysis differed substantially from the likelihood-to-recommend item, making the findings questionable. They did show that satisfaction correlated with future growth rates (explaining between 1% and 16% of the variation) and a single-item satisfaction measure correlated very highly (r = .9) with the average ACSI scores (see later papers on single items).

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