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N.P.S. scam
It’s extremely disturbing when I walk into clients meeting rooms to
hear about N.P.S. and this, while we discuss serious matters such
as customer service performance.
Who said” you cannot fool all the people all the time”?
Nevertheless, more neck breaking is the fact that many” business
people” fool themselves, with utter conviction, by singing praises
to N.P.S. when any smart person knows that N.P.S is nothing but
a form of intellectual mafia. An invention based on nothing, talks
about nothing and delivers nothing.
I have swum in data lakes and statistics for over 30 years, my
customers receive actionable marketing statistics and many
statistical tools have been successfully launched to gain even more
strategic insights. It can be different.
.
Today I am very interested to know why so many people still want
to glorify this N.P.S. nonsense. For the hardliners who still see
N.P.S. as the golden calf, here are the main reasons why this
measurement should not exist; something people believe it is but it
isn’t.
1. N.P.S. is not a measurement of customer service
performance. It’s not even a measurement of loyalty but a
simple figure of recommendation. A useless score from a
question that customers don’t even understand. A score for
which we can’t find correlations with satisfaction, re-purchase
or other measurements. What’s the meaning of
recommendation? As an example, in the Middle-East, a client
who is satisfied with a product will recommend the same
product to his competitors. Recommendation, as a
measurement, has never been a corner stone of client’s
evaluation, behavior or prediction. The client is more
complex than an N.P.S. score. The marketing variables need
sophisticated statistics before we can really understand them.
N.P.S. is a mockery of robust statistics.
2. The use of a basic 11-point numerical Likert scale doesn’t
allow for international comparison, as with this type of
scaling we neglect important cultural differences. Some good
examples of the limitations of this type of scaling are
comparisons between Italian and German satisfaction scores,
European and Asian satisfaction scores. This means that the
N.P.S. calculations, as such, are missing statistical validation.
Moreover when doing some mathematics on this type of
N.P.S. calculations all statistical coherences disappears, and of
course, using such a broad numerical scaling, in this context,
means hiding clear results.
3. The output of N.P.S. supplies no information, impossible to
read, to interpret or to elaborate action plans based on the
results. As the N.P.S. propaganda declares “change over
time” as the main outcome for analysis, what do you do
when, during 8 quarters, your company’s turnover declines
while your N.P.S. stays at good levels? An interesting test for
those top 500 companies using N.P.S. would be to correlate
2017-2018 revenues with their N.P.S. scores.
4. The N.P.S. way of data collection and data handling is
probably the most harmful part because each company can
set out their own rules and procedures e.g. data collection,
per month or per quarter dependent on the sample size or the
response rate. It is rare for a client to respond twice during
the same year to the same survey. Moreover nearly half of
your clients prefer that the information given stays
confidential as they want to preserve their good relationship
with the sales rep. or the customer service department. A lot
of clients find this N.P.S. scale scoring childish. The overall
concern is about response, which response rates are
acceptable? When a company wants to track this
recommendation for their 100 most important clients and for
the first wave the response rate is 10% and the second wave
5%, what do you do with the non-responses? How can you
measure evolution over time? When are the differences in
scores significant and with which sample size? Which margins
of error are acceptable? Here, we have a critical situation in
data collection and data handling; both become, for the
companies involved with N.P.S., an excellent playground for
internal manipulation of results. The data are not only useless,
they can’t be trusted either.
The promoters of the N.P.S. want us to believe that their
measurement is the Holy Grail for predicting turnover; this is the
biggest lie of the century. We tested this for many years and the
results are negative and totally inconsistent.
So, why are companies using N.P.S.?
- Self-fulfilling prophecy: a false definition of the situation
evoking a new behavior which makes the original false
conception become reality
- Simplicity: you don’t need to think
- Financial: spending low budgets for Fata Morgana’s
- Political: the truth hurts
- Easily manipulative: keep bonuses
- Community: be a member of a club
Serving more than 150 international corporations, we observe in
B2B industries, a severe under spending in strategic marketing and
market research. Most of the financial groups, ultimate owners
behind a lot of these corporations, are squeezing budgets and
don’t show interest at all in marketing analysis. A ridiculous N.P.S.
measurement perfectly suits this short term thinking.
Another reason why N.P.S. still exists is the hard will to cover up
the reality of business situations. To avoid real discussions about
what’s going on and to demotivate those who want change
management. Moreover N.P.S. fits perfectly with postponing
decisions and keeping everybody in a comfortable warm bed.
Using N.P.S. is promoting status quo and is for people who want
to fool everybody. It is basically one of the biggest fraudulent lies
we ever met in marketing. Finally those who sway with N.P.S. do
not respect their customers; they make their customers look
ridiculous.
Can it been done differently?
In our company, and for customer experience, we work with real
statistics and have, for every survey, five rules:
1. To work with semantic scales
2. To define 10 KPI’s
3. To leave the decision to the client to define the 50 most
important service attributes to them
4. To deliver actionable data based on robust statistics
5. To ensure anonymity of the responder which, can be given
up should the respondent choose to
Dominique Deserrano
Managing Director
Sweeney International Ltd.
d.deserrano@sweeney-int.com

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Net promoter score (N.P.S) SCAM

  • 1. N.P.S. scam It’s extremely disturbing when I walk into clients meeting rooms to hear about N.P.S. and this, while we discuss serious matters such as customer service performance. Who said” you cannot fool all the people all the time”? Nevertheless, more neck breaking is the fact that many” business people” fool themselves, with utter conviction, by singing praises to N.P.S. when any smart person knows that N.P.S is nothing but a form of intellectual mafia. An invention based on nothing, talks about nothing and delivers nothing. I have swum in data lakes and statistics for over 30 years, my customers receive actionable marketing statistics and many statistical tools have been successfully launched to gain even more strategic insights. It can be different. . Today I am very interested to know why so many people still want to glorify this N.P.S. nonsense. For the hardliners who still see N.P.S. as the golden calf, here are the main reasons why this measurement should not exist; something people believe it is but it isn’t. 1. N.P.S. is not a measurement of customer service performance. It’s not even a measurement of loyalty but a simple figure of recommendation. A useless score from a question that customers don’t even understand. A score for which we can’t find correlations with satisfaction, re-purchase or other measurements. What’s the meaning of recommendation? As an example, in the Middle-East, a client who is satisfied with a product will recommend the same product to his competitors. Recommendation, as a measurement, has never been a corner stone of client’s
  • 2. evaluation, behavior or prediction. The client is more complex than an N.P.S. score. The marketing variables need sophisticated statistics before we can really understand them. N.P.S. is a mockery of robust statistics. 2. The use of a basic 11-point numerical Likert scale doesn’t allow for international comparison, as with this type of scaling we neglect important cultural differences. Some good examples of the limitations of this type of scaling are comparisons between Italian and German satisfaction scores, European and Asian satisfaction scores. This means that the N.P.S. calculations, as such, are missing statistical validation. Moreover when doing some mathematics on this type of N.P.S. calculations all statistical coherences disappears, and of course, using such a broad numerical scaling, in this context, means hiding clear results. 3. The output of N.P.S. supplies no information, impossible to read, to interpret or to elaborate action plans based on the results. As the N.P.S. propaganda declares “change over time” as the main outcome for analysis, what do you do when, during 8 quarters, your company’s turnover declines while your N.P.S. stays at good levels? An interesting test for those top 500 companies using N.P.S. would be to correlate 2017-2018 revenues with their N.P.S. scores. 4. The N.P.S. way of data collection and data handling is probably the most harmful part because each company can set out their own rules and procedures e.g. data collection, per month or per quarter dependent on the sample size or the response rate. It is rare for a client to respond twice during the same year to the same survey. Moreover nearly half of your clients prefer that the information given stays confidential as they want to preserve their good relationship with the sales rep. or the customer service department. A lot
  • 3. of clients find this N.P.S. scale scoring childish. The overall concern is about response, which response rates are acceptable? When a company wants to track this recommendation for their 100 most important clients and for the first wave the response rate is 10% and the second wave 5%, what do you do with the non-responses? How can you measure evolution over time? When are the differences in scores significant and with which sample size? Which margins of error are acceptable? Here, we have a critical situation in data collection and data handling; both become, for the companies involved with N.P.S., an excellent playground for internal manipulation of results. The data are not only useless, they can’t be trusted either. The promoters of the N.P.S. want us to believe that their measurement is the Holy Grail for predicting turnover; this is the biggest lie of the century. We tested this for many years and the results are negative and totally inconsistent. So, why are companies using N.P.S.? - Self-fulfilling prophecy: a false definition of the situation evoking a new behavior which makes the original false conception become reality - Simplicity: you don’t need to think - Financial: spending low budgets for Fata Morgana’s - Political: the truth hurts - Easily manipulative: keep bonuses - Community: be a member of a club Serving more than 150 international corporations, we observe in B2B industries, a severe under spending in strategic marketing and market research. Most of the financial groups, ultimate owners
  • 4. behind a lot of these corporations, are squeezing budgets and don’t show interest at all in marketing analysis. A ridiculous N.P.S. measurement perfectly suits this short term thinking. Another reason why N.P.S. still exists is the hard will to cover up the reality of business situations. To avoid real discussions about what’s going on and to demotivate those who want change management. Moreover N.P.S. fits perfectly with postponing decisions and keeping everybody in a comfortable warm bed. Using N.P.S. is promoting status quo and is for people who want to fool everybody. It is basically one of the biggest fraudulent lies we ever met in marketing. Finally those who sway with N.P.S. do not respect their customers; they make their customers look ridiculous. Can it been done differently? In our company, and for customer experience, we work with real statistics and have, for every survey, five rules: 1. To work with semantic scales 2. To define 10 KPI’s 3. To leave the decision to the client to define the 50 most important service attributes to them 4. To deliver actionable data based on robust statistics 5. To ensure anonymity of the responder which, can be given up should the respondent choose to Dominique Deserrano Managing Director Sweeney International Ltd. d.deserrano@sweeney-int.com