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Author: Eric Larse


Net Referrers: The Single Satisfaction and Growth Metric

For all of Albert Einstein's successes early in his career, he struggled late in life without success to answer what, to him, was the fundamental question in theoretical physics - what is the theory of everything. Einstein, like most of us, believed in an ordered universe, one in which inconsistency could not exist. His problem, and the problem facing all physicists, was the inconsistency among the different theories of physics. For example, much of the work Einstein did in describing the universe on the largest of scales (his explanations of space and time on the galactic scale) simply falls apart when the scale is reduced to the sub-atomic level. The two theories which describe the universe at the largest and the smallest of scales cannot co-exist; they are inconsistent with each other.

Einstein, believing in an ordered universe, was among the earliest to propose that a unified theory (a theory of "everything") must exist, and he struggled for most of his later life, to find the right theory, which would resolve all inconsistencies.

Today, we may be on the verge of realizing Einstein's dream. String theory is currently the most promising candidate for a unified theory. We are not yet sure that it correctly describes nature, but it broadly describes a universe similar to ours.

String theory is utterly simple, elegant and consistent. Instead of a universe composed of the many types of elementary particles we learned about in high school physics (protons, neutrons, electrons and others), theorists propose that in nature there is a single variety of string-like object. As with musical strings, this basic string can vibrate, and how it vibrates determines its properties - determining if the string will be an electron, proton, etc. String theory appears to predict the right types of particles and the right types of interactions among them with none of the inconsistencies, which plague other theories. One problem with string theory is the size of the predicted strings is so small that there is no way we will ever observe them.

In the field of customer satisfaction measurement, we face a similar but different set of problems. Our problem is the search for a simple intuitive measure linking customer satisfaction to company profits. While intuitively most believe such a link must exist, the search has yielded mixed results and fostered complex and inelegant methodologies, which lack intuitive appeal. Focusing purely on customer satisfaction yields mixed results in linking customer satisfaction to profitability. For every example of satisfaction and profitability leaders, there is an example such as K-mart, whose CSI score (according to the University of Michigan satisfaction index) led the industry the week it entered bankruptcy. Furthermore, such CSI indexes which consist of sophisticated questions and complicated weighting and scaling lack intuitive appeal, the result of which can be a lack of acceptance by the one stakeholder group who can directly influence customer satisfaction - the employees.

Recently, research has been proposed suggesting that customer satisfaction measurement and analysis can be simplified yielding an elegant and intuitive means of analysis which appears to have a correlation to profitability. In an article published in the December, 2003 issue of the Harvard Business Review, Fredrick Reicheld, a well known customer satisfaction and loyalty researcher proposes a single measurement which he has determined correlates closely to revenue growth in place of the common, more complex customer satisfaction survey instruments.

This research segmented customers according to a "Would Recommend" question, such as "how likely is it that you would recommend [Company X] to a friend or colleague?" Customers with high recommendation likelihood (ratings of 9 or 10 on a ten-point scale) are identified as referrers; customers who gave ratings of 7 and 8 are identified as "passive referrers"; and customers who assigned referral likelihoods of 1-6 are identified as "detractors." The "referrers" segment is made up of the top two units of the scale, while the "detractors" segment is made up of the bottom six units of the scale, due to the common effect of score inflation, where satisfaction ratings are almost always skewed to the top-end of the rating scale. The next step in this analysis is to determine the "net referrers" (the percentage of referrers minus the percentage of detractors).

Net Referrers = % Referrers - % Detractors

By comparing net referrers to revenue growth rates of competing firms across a broad range of industries, research determined that a strong correlation existed between the percentage of net referrers and a company's average growth rate, and propose this measurement as an easy and intuitive satisfaction statistic which correlates closely to the bottom line.

Unlike string theory, the utility of the "Would Recommend" measurement is empirical: we can test and observe it. If Reicheld's conclusions are correct, we should see a relationship over time of a firm's net referrers and revenue growth.


Eric Larse is co-founder of Seattle-based Kinesis, which helps companies plan and execute their customer experience strategies. Mr. Larse can be reached at elarse@kinesis-cem.com.

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