Afrika
Re-Evaluating The Net Promoter Score
December 2007
Fred Reichheld, an American loyalty guru, has argued that the days of customer satisfaction surveys are over (Reichheld, 2003). Instead we should only be measuring customer loyalty. According to Reichheld all that is necessary is a single question, which he labels ‘The Ultimate Question’.
The Ultimate Question is simply “How likely are you to recommend company X to friends and colleagues?” Respondents are asked to rate the likelihood of recommending on a scale from 0, meaning extremely unlikely, to 10 meaning very likely. Promoters are those who give a rating of 9 or 10. Promoters are important not only because they are more likely to promote your brand to friends and family, they also tend to spend more than non-Promoters (Reichheld, 2003).
According to Reichheld you need to take it a step further if you want to relate the rating to future corporate growth, by calculating a Net Promoter Score. The Net Promoter Score is simply the percentage of respondents who give your brand a 9 or 10 rating on a 0 to 10 recommendation scale, minus the percentage who give you a rating of 0 to 6 on the scale (Reichheld, 2003).
Popularity
On the back of Reichheld’s finding that the Net Promoter Score correlates with future corporate growth across a number of sectors (Satmetrix, 2004), the measure has gained broad support from executives across a variety of industries. Some, such as GE’s CEO Jef Immelt, have taken the unusual step of publicly praising the approach (General Electric, 2005).
Besides the claimed relationship with corporate growth and customer behaviour, an additional attraction is simplicity, something very appealing to time pressured executives.
Along the way Reichheld has popularized various ideas in tandem with the loyalty measure – such as his controversial claim that retaining 5% more customers equals 100% more profits. Of particular concern to those who have invested heavily in customer satisfaction measurement, is the claim that customer satisfaction measurement is redundant.
Reichheld pitches satisfaction measurement against loyalty measurement and proclaims the death of satisfaction measurement. He claims that customer satisfaction measures are overly complicated, a heresy to some in the boardroom, and that they also fail to explain corporate growth differences in a sector.
He also laments the long windedness of the questionnaires typically employed to measure customer satisfaction.
The Ultimate Question?
There is nothing terribly wrong with the Ultimate Question – other than that it is far from being ‘ultimate’. Reichheld claims that of the 20 different measures he tested, it was the best predictor of customer behavior and future corporate growth (Reichheld, 2003).
Not the Best Predictor of Customer Retention
You don’t need a degree in statistics to figure out that there is something intuitively wrong with the claim, that whether a customer says he will recommend your company or not is the best predictor of whether he will stay with your company.
Differences in the tendency to recommend don’t automatically mean there will be differences in loyalty behavior – whether retention or increased spend. Results from an analysis I conducted using data collected by Ask Afrika, of a number of different markets ranging from short term insurance to cars made this clear. Using an approach which has been established as a reliable predictor of the percentage of customers switching away from a company, I compared the results to the Net Promoter Score (this approach is discussed in a related article “The One Number You Need to Measure Loyalty”).
Clearly the Net Promoter Score does not relate to the percentage of customers switching away from each institution.
A survey of 8000 customers in the banking, retail and ISP industries, conducted by Keiningham et al. (2007) lends support to this. Keiningham et al. (2007) asked customers the likelihood of recommending question along with a rival set of questions, and then followed up with questions about retention a year later. The results showed that the Ultimate Question barely improves on a conventional satisfaction measure as predictor of retention, and was outperformed by a simple repeat purchase intention question.
Doesn’t Identify Those Who Are Truly Loyal
Reichheld (2003) states that some clients buy out of habit, which means that retention measurement (i.e. did they stay or did they go) is not a good measure of true loyalty. He suggests that the Net Promoter approach is able to identify true loyalty. This suggests that Net Promoters should be more resistant to competing offers than those who just buy out of ‘habit’.
However, using cell phone data collected by Ask Afrika, I found hidden differences amongst consumers who were identified as ‘Promoters’. Far from being uniformly loyal, some were far more prone to being tempted by competitor offers than others. The key difference was the customer’s level of involvement with cell phones.
I found that amongst the Promoters who were psychologically involved with cell phones, competitors offering 20% discounts would create a smaller increase in the switch rate than amongst those Promoters who were not involved. Intriguingly those who were involved, although being an asset in that they were more resistant, spent less on their cell phones every month than those who were involved.
In essence, ‘Promoters’ are not equally loyal.
Relationship With Growth Not Clear
One of the foundational claims which undergirds the value of the Net Promoter Score, is the claim that the Net Promoter Score relates to corporate growth. However this is questionable. In a study of 80 companies over a 7 year period, the researchers Morgan & Rego (2006) found that the Net Promoter Score was not predictive of company growth rates. In fact, customer satisfaction outperformed the Net Promoter Score as a predictor.
Weighing-up the Positives and Negatives of the Net Promoter Score
Reichheld has brought up some valid points about satisfaction and loyalty measurement. Simplicity is not only appealing to high-level decision makers, it also appeals to customers who don’t want to answer long questionnaires. The measure also lends itself to standardization, to the point where it may be a useful number to include on the balance sheet.
That is one side of the story. The other is that the ‘Ultimate Question’ is far from being the most accurate measure of loyalty, and so will more often mislead than help.
It can also prove frustrating when it comes time to understand how to resolve a loyalty problem. Perhaps the highest-level decision makers are not overly concerned about tactical level problem solving, however someone in the company will have to be; and a single question won’t give the answers needed.
Another issue is the delay before loyalty changes. If executives wait until loyalty has been affected, it is sometimes too late. Satisfaction with service quality will often drop long before it affects loyalty.
So Where to Now?
Reichheld has confused satisfaction with loyalty. Satisfaction and loyalty are two different issues. While you would naturally expect loyalty measures to relate more closely to customer behaviour and future growth than satisfaction and service quality perceptions, claiming that you should drop these measures in favour of loyalty measurement makes no sense at all.
Customer satisfaction with the service quality delivered, is only one amongst a number of loyalty drivers, but that doesn’t mean it should be ignored.
Measuring loyalty alone, may tell you how many loyal customers there are, but it doesn’t tell you how to fix the problem if there is one.
It is still necessary to measure customer satisfaction, along with service quality perceptions in order to flag issues and tackle the root causes of loyalty failures. Throwing out satisfaction in favor of loyalty is like deciding that you only need to report net profits on an income statement and can dispense with all the rest of it.
Lastly, looking beyond the hype, it is clear that willingness to recommend is a sub-optimal loyalty measure. There are far more accurate loyalty measures in existence which have benefited from years of development by professional marketing researchers. They offer better accuracy in predicting loyalty behaviors, and are typically coupled with diagnostics which aid in gaining an understanding of what creates loyalty.
Copyright reserved (2007). The author gives permission for the article to be re-published, however the article may not be altered or shortened and must be re-published in its entirety.
References:
General Electric, (2005), “GE annual outlook meeting – final”, Fair Disclosure Wire (Quarterly Earnings Reports), Dec 13.
Keiningham, T.L., Cooil, B., Aksoy, L., Andreassen, T.W., Weiner, J.W., (2007)”The value of different customer satisfaction and loyalty metrics in predicting customer retention, recommendation, and share-of-wallet”, Managing Service Quality Vol. 17 No. 4, 2007 pp. 361-384.
Morgan, N. & Rego, L. (2006) “The value of different customer satisfaction and loyalty metrics in predicting business performance”, Marketing Science, September/ October.
Reichheld, FF., (2003), The one number you need to grow, Harvard Business Review, December, Vol. 81, Issue 12.
Satmetrix, (2004), The power behind a single number: Growing your business with Net Promoter, Satmetrix Systems.
*Note: Net Promoter is a registered trademark of Satmetrix Systems, Inc., Bain & Company and Fred Reichheld.
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