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Estimating Other "Likelihood to Recommend" Metrics from Your Net Promoter Score (NPS)

In the realm of customer experience management, businesses can employ different summary metrics of customer feedback ratings. That is, the same set of data can be summarized in different ways. Popular summary metrics include mean scores, net scores and customer segment percentages. Prior analysis of different likelihood to recommend metrics reveal, however, that they are highly […]

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Battling Misinformation in Customer Experience Management

I read an article last week in Scientific American that has implications about the field of customer experience management (CEM). The article, Diss Information: Is There a Way to Stop Popular Falsehoods from Morphing into "Facts"?, discusses the phenomenon of widely held beliefs that are not true. Think about President Barack Obama's US citizenship status still […]

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Unmasking the Problem with Net Scores and the NPS Claims

I wrote about net scores last week and presented evidence that showed net scores are ambiguous and unnecessary.  Net scores are created by taking the difference between the percent of "positive" scores and the percent of "negative" scores. Net scores were made popular by Fred Reichheld and Satmetrix in their work on customer loyalty measurement. Their […]

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The Best Likelihood to Recommend Metric: Mean Score or Net Promoter Score?

A successful customer experience management (CEM) program requires the collection, synthesis, analysis and dissemination of customer metrics.  Customer metrics are numerical scores or indices that summarize customer feedback results for a given customer group or segment. Customer metrics are typically calculated using customer ratings of survey questions. I recently wrote about how you can evaluate the quality of your customer metrics and listed four questions […]

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