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Happy customers are one of the most important assets a business can have, and it’s no secret that we think using the Net Promoter System is a great way to ensure you have them. While deceptively simple, when used right it yields brilliant results.
That’s why we’d like to take this opportunity to talk a little about the origins of Net Promoter, why it became so popular, and how it looks across a variety of industries.
First conceived as primarily a loyalty metric, Net Promoter Score was developed by Fred Reichheld along with Bain & Company. Much of the relevant research which went into the system was presented in the 2003 Harvard Business Review article, “The One Number You Need to Grow”.
Frustrated by feedback systems that involved long and unwieldy questionnaires, had low response rates, and often yielded results too complex to be easily actionable, they began looking for an alternative method.
Searching for a single question which would best correlate with concrete loyalty behaviors such as repurchases and referrals, they conducted thorough case studies of 14 industries. Of these it was found in 11 that “What is the likelihood that you would recommend Company X to a friend or colleague?” was the most effective in predicting behavior, and in a further two industries very similar questions came out on top.
This was a somewhat novel approach, as rather than looking at metrics which would directly predict profit, loyalty was the factor being measured. While this might seem a convoluted way to go about things, those companies scoring high on loyalty did exhibit the healthiest growth overall. In addition it allowed for a feedback method and results which were simple both for consumer and company.
Reichheld argued that by focusing on a single, comprehensible metric, whole teams could adapt their work to simple focused goals, and the success of changes would always be easily verifiable.
Furthermore, by looking at loyalty they discovered they could to a greater extent predict growth despite marketplace changes. While a happy customer might not hesitate in changing to a new cheaper service, a genuinely loyal customer is more likely to stay.
The division of customers into three groups also derived from this research, after strong correlation was found between referrals and repeat purchases only among the most enthusiastic ratings of 9 or 10. While traditional feedback methods would often conclude that anyone rating above 5 was satisfied, Net Promoter Score leaves these respondents out of its calculations.
Results strongly suggested that growth was predicted not by looking at those who might be passively satisfied, but looking at the number of detractors as opposed to promoters. Hence the calculation for NPS being % Promoters - % Detractors.
As Reichheld put it “A customer feedback program should be viewed not as market research but as an operating management tool”. By using a simple metric with clear goals, NPS makes this possible.
Everything he argued about what was a bold new metric still applies today, though if anything the uses for NPS have only multiplied. As we’ve laid out in our 5 Steps to Become a Customer Success Hero, the benefits and applications of the system are manifold.
Even during the initial research which led to NPS, sweeping statements about all industries was avoided. As mentioned, 14 case studies throughout different industries were conducted, and the varying results taken into account.
For example, while the NPS question was the best at predicting loyalty behavior almost everywhere, the extent to which this correlated with growth was variable. Within those industries which had high swapping costs, or were semi-monopolistic, such as utilities, Net Promoter Score was found to have a smaller correlation with growth. In addition, these industries on average had far lower scores.
It is of course, not surprising that different industries will vary in terms of their NPS results. This might in part due to customer success culture present within their field, or simply naturally divergent modes of doing business. It goes without saying that a B2B operation with a small number of large contracts will have a different customer approach to that of a supermarket.
We compiled the data above by sampling our own customers from various industries. The result is somewhat focused on web and software businesses, as we provide primarily in-app NPS. However we hope that an in-depth look at benchmarks for certain industries is still helpful.
As you can see from these graphs, response rates do not necessarily correlate with average scores for a given industry. While averages such as these can be helpful, it is important to keep in mind the specificity of any given business and their customer relations. Furthermore, the method of administering a survey will alter the response rates dramatically.
We find that in-app surveys complemented with email reminders yield by far the best response rates, with some companies achieving as high as 70%. This kind of surveying can really supercharge a campaign, and provide massive insight on your customers.
While NPS as a metric continues to expand in use and scope, the basics from which it came remain the same: don’t overcomplicate, trust metrics which reflect behavior, and set yourself up for success by collecting actionable customer feedback.
Original post: http://blog.satismeter.com/post/151334852423/nps-history
That’s why we’d like to take this opportunity to talk a little about the origins of Net Promoter, why it became so popular, and how it looks across a variety of industries.
Loyalty First
First conceived as primarily a loyalty metric, Net Promoter Score was developed by Fred Reichheld along with Bain & Company. Much of the relevant research which went into the system was presented in the 2003 Harvard Business Review article, “The One Number You Need to Grow”.
Frustrated by feedback systems that involved long and unwieldy questionnaires, had low response rates, and often yielded results too complex to be easily actionable, they began looking for an alternative method.
Searching for a single question which would best correlate with concrete loyalty behaviors such as repurchases and referrals, they conducted thorough case studies of 14 industries. Of these it was found in 11 that “What is the likelihood that you would recommend Company X to a friend or colleague?” was the most effective in predicting behavior, and in a further two industries very similar questions came out on top.
This was a somewhat novel approach, as rather than looking at metrics which would directly predict profit, loyalty was the factor being measured. While this might seem a convoluted way to go about things, those companies scoring high on loyalty did exhibit the healthiest growth overall. In addition it allowed for a feedback method and results which were simple both for consumer and company.
The Benefits of One Simple Question
Reichheld argued that by focusing on a single, comprehensible metric, whole teams could adapt their work to simple focused goals, and the success of changes would always be easily verifiable.
Furthermore, by looking at loyalty they discovered they could to a greater extent predict growth despite marketplace changes. While a happy customer might not hesitate in changing to a new cheaper service, a genuinely loyal customer is more likely to stay.
“A customer feedback program should be viewed not as market research but as an operating management tool.” _-Fred Reichheld_
The division of customers into three groups also derived from this research, after strong correlation was found between referrals and repeat purchases only among the most enthusiastic ratings of 9 or 10. While traditional feedback methods would often conclude that anyone rating above 5 was satisfied, Net Promoter Score leaves these respondents out of its calculations.
Results strongly suggested that growth was predicted not by looking at those who might be passively satisfied, but looking at the number of detractors as opposed to promoters. Hence the calculation for NPS being % Promoters - % Detractors.
As Reichheld put it “A customer feedback program should be viewed not as market research but as an operating management tool”. By using a simple metric with clear goals, NPS makes this possible.
Everything he argued about what was a bold new metric still applies today, though if anything the uses for NPS have only multiplied. As we’ve laid out in our 5 Steps to Become a Customer Success Hero, the benefits and applications of the system are manifold.
Variation by Industry
Even during the initial research which led to NPS, sweeping statements about all industries was avoided. As mentioned, 14 case studies throughout different industries were conducted, and the varying results taken into account.
For example, while the NPS question was the best at predicting loyalty behavior almost everywhere, the extent to which this correlated with growth was variable. Within those industries which had high swapping costs, or were semi-monopolistic, such as utilities, Net Promoter Score was found to have a smaller correlation with growth. In addition, these industries on average had far lower scores.
It is of course, not surprising that different industries will vary in terms of their NPS results. This might in part due to customer success culture present within their field, or simply naturally divergent modes of doing business. It goes without saying that a B2B operation with a small number of large contracts will have a different customer approach to that of a supermarket.
We compiled the data above by sampling our own customers from various industries. The result is somewhat focused on web and software businesses, as we provide primarily in-app NPS. However we hope that an in-depth look at benchmarks for certain industries is still helpful.
As you can see from these graphs, response rates do not necessarily correlate with average scores for a given industry. While averages such as these can be helpful, it is important to keep in mind the specificity of any given business and their customer relations. Furthermore, the method of administering a survey will alter the response rates dramatically.
The Best Response Rates
We find that in-app surveys complemented with email reminders yield by far the best response rates, with some companies achieving as high as 70%. This kind of surveying can really supercharge a campaign, and provide massive insight on your customers.
While NPS as a metric continues to expand in use and scope, the basics from which it came remain the same: don’t overcomplicate, trust metrics which reflect behavior, and set yourself up for success by collecting actionable customer feedback.
Original post: http://blog.satismeter.com/post/151334852423/nps-history