Home » NPS

Tag: NPS

Your customer survey is bad, and you should feel bad.

Your Customer Survey is Bad, and You Should Feel Bad

Rob Markey
is a loyalty rock star.

Not just because he’s the co-author of The Ultimate Question 2.0, one of my favorite business books of all time.

Not just because he heads up the Customer Strategy Practice at Bain and is one of the most important thinkers in the customer loyalty field.

All of these things are great, but what pushes Rob from pretty cool guy to loyalty rock star is the fact that he maintains a database of real customer surveys used by real companies. You can check it out by visiting http://www.robmarkey.com/survey-files/ (quick and painless registration required).

As you peruse through Rob’s collection of surveys, you will likely come to the same conclusion as I did – most customer surveys are awful.

Even companies that otherwise excel at customer experience have terrible surveys.

Five Guys asks customers for their receipt number, but then asks you for the time of your visit, order total, and 34 pages of other data that they should easily be able derive from information given on the first page.

It takes longer to complete the Starbucks survey than it does to drink a venti caramel macchiato.

Marriott, a company I love, asks over 80 questions, including an absurd matrix that asks you to rate on a scale of 1 to 10 whether the hotel was luxurious, sophisticated, or engaging (amongst a dozen more marketing words that mean nothing to the consumer).

And in the height of “do as I say, not as I do”, Forrester sent a 20 page survey to all attendees of a customer feedback management conference.

Overly long surveys tell your customers that you don’t value their time. This is especially true for surveys that ask questions to which you already know the answer. Don’t ask for my receipt number and then ask me whether or not I ordered breadsticks (looking at you, Pizza Hut).

The good news is that there is hope. And it starts with us, customer loyalty practioners.

We need to stress out about the length of our customer feedback surveys. It needs to keep us up at night. We should take it as a sign of professional failure if it takes longer to take our survey than it does to purchase, assemble, and use our products. Any time we are even considering adding another question to our survey, we should ask ourselves the following questions:

  • Do we really need to ask this?
  • Will we do anything with this information, or are we asking just to ask?
  • Can we answer this question ourselves with data we already have?
  • What can we remove to make room for this question?
  • OK, seriously – do we really need to ask this?

And it’s not enough to simply prevent new questions from being added. We need to critically evaluate existing questions to determine if they are truly needed.

I once read that you should turn all of your clothes hangers backwards, turning them the correct way when you’ve worn the garment at least once. At the end of a year, any item of clothing that is still on a backwards hanger should be donated to a worthy cause because you’ve demonstrated that you don’t wear it.

Likewise, you should turn a critical eye towards every question on your survey at least once a year (if not quarterly) and ask your team a simple question: “When was the last time someone used the data that this question collects?”. If no one can offer up a concrete instance in the past 12 months, you should seriously consider removing the question from your survey.

Customer surveys don’t have to suck. Companies like Rackspace, Logitech, Intuit and Domino’s all manage to collect meaningful, actionable customer feedback without torturing their customers with page after page of needless questions.

If you remain diligent about what you are asking and why, your reward will be increased response rate, more actionable data, and clearer line-of-site for employees.

And then you’ll be a loyalty rock star too.

Performing Driver Analysis in Microsoft Excel

Many Net Promoter programs start as small pilot programs without large investments in systems and infrastructure. This can put Net Promoter novices into a catch-22 situation – they can’t obtain the budget for more robust tools until they demonstrate results, but it is easier to demonstrate results with more robust tools.

The good news is that many of the most important analytical exercises needed for a successful Net Promoter pilot can be performed using software that you probably already own – Microsoft Excel.


What is Driver Analysis?

Driver Analysis is a powerful tool that can help you understand the factors that influence loyalty. Driver Analysis attempts to identify the attributes that are most correlated with loyalty (as measured by NPS), and illustrates areas where you are under (or over) delivering. This information can then be used to prioritize the investment of capital, time, and resources into areas that will yield the highest return in customer loyalty.


Example Scenario

In the scenario below, I will take you through a quick exercise in which we will create a Driver Analysis table for a fictional business.

You are the Vice President of Customer Experience for Acme Pizza Company. You ran a pilot Net Promoter survey that asked customers four questions: (1) Likelihood to Recommend [aka “the Net Promoter question”], (2) Satisfaction with Speed of Delivery, (3) Satisfaction with Quality of Pizza, and (4) Satisfaction with Customer Service. Each question had a response scale that ranged from 0 to 10. As a result of the survey, you see that Acme Pizza’s Net Promoter Score is 10%.

You have a limited budget to spend, and want to know which of the three areas (Speed, Quality, or Service) you should focus on improving. You have an excel spreadsheet with your survey responses that looks like this:



Step One: Calculating Satisfaction

To create a Driver Analysis table, you first need to calculate the average satisfaction for each attribute. This is relatively straightforward – for example, to calculate the average satisfaction for Speed (found in Column C), you would use the following formula:


Once you repeated this step for all three attributes, the end result would look like this:




Step Two: Calculating Correlation

Unfortunately, many people stop at the previous step. Looking at the information generated, they would make the decision to direct their efforts towards improving the quality of the pizza – after all, that is the attribute for which customers are expressing the greatest amount of dissatisfaction.

In order to make a more informed decision, it’s not enough to know how satisfied our customers are with each attribute – we need to understand how strongly each attribute is correlated with loyalty. This is done by calculating the correlation between the Net Promoter question (likelihood to recommend), and each individual attribute.

Calculating correlation in Microsoft Excel is much easier than you might expect. The formula is simply:


To create our Driver Analysis table, we’d first calculate the correlation between NPS (Column B) and Speed (Column C) like so:


We would then repeat this step with the other two attributes – Quality (Column D) and Service (Column E) – using the following formulae:


Our finished product would look like this:



The result of this formula is called the correlation coefficient (or r value for short) with can range from -1.0 to +1.0. This rating can be interpreted using the following guide:

  • An r value close to 1 indicates that there is a strong relationship between the two variables
  • An r value close to 0 indicates that there is a weak relationship between the two variables
  • A positive r value means that as one variable increases in value, the other variable will increase in value. Likewise, as one variable decreases in value, the other variable decreases in value.
  • A negative r value means that as one variable increases in value, the other variable will decrease in value.


Step Three: Analyze the Data

We now have a table that tells us how satisfied our customers are with our speed, quality, and service, and how strongly each of those attributes are correlated with overall NPS.  Looking at our Driver Analysis for Acme Pizza, we can make the following observations:

  • Customers are very satisfied with our speed of delivery, which has very little correlation with loyalty
  • Customers are dissatisfied with the quality of our food, which has very little correlation with loyalty
  • Customers are mildly satisfied with our customer service, which is highly correlated with loyalty

Using Excel’s built-in graphing functionality, we might choose to display this information visually like so:


Now that we have completed the analysis, we are able to see that we should focus on improving Acme Pizza’s customer service. Of the three attributes, customer service represents the best opportunity for positively impacting Acme Pizza’s customer loyalty.


Driver Analysis is a powerful tool that can help ensure that you are focusing your time and energy on the items that will have the biggest impact on customer loyalty. By performing Driver Analysis using Microsoft Excel, you can now generate actionable data without making large investments into additional systems and tools.


The Net Promoter System on a Napkin

Therefore, since brevity is the soul of wit,
And tediousness the limbs and outward flourishes,
I will be brief

– William Shakespeare, Hamlet

If brevity is the soul of wit, then simplicity is the soul of inspiring others. It has been my experience that creating a customer-centric revolution within an organization requires the ability to convey your vision as simply as possible. To that end, I thought it would be a fun exercise to attempt to explain the Net Promoter System on a single napkin.

Net Promoter on a Napkin

The end result of this exercise is posted above. Obviously, this illustration is overly simplistic, leaves out some key concepts, and is limited by my poor artistic ability. With all of those caveats, I still found this to be an incredibly worthwhile exercise. The next time you have a complex idea that you must communicate to a broad group, try drawing it out on a napkin first. The limited space will force you to ruthlessly edit out the fluff to let the essence of your idea shine through.

Key elements for a succesful Net Promoter survey invitation

Elements of a Successful Net Promoter Survey Invitation

One of the keys to success for your Net Promoter Score program is generating a high response rate. Unlike many other customer feedback frameworks, Net Promoter is designed to emulate a census, with target response rates of 50% of more.

The are many factors that contribute to your overall response rate, one of which is the execution of your survey invitation. Many new NPS practitioners don’t know where to start when creating a survey invitation. The chart below lists some of the factors that I have used in my survey invitations to generate response rates of up to 68%.

Click on the image to enlarge

Key elements for a succesful Net Promoter survey invitation

Once your Net Promoter program evolves, you will no doubt develop your own best practices that work for your particular business and customer type. This chart is intended to give you a place to start.

Calculating Net Promoter Score with Microsoft Excel

If your Microsoft Excel kung-fu is a little rusty, calculating your Net Promoter Score can seem intimidating. But worry not … it’s a lot easier than you might think!

Let’s say you have an Excel spreadsheet containing all of your survey responses. Each row in your spreadsheet contains a unique response. To make things easy, let’s assume that the answer to the ‘likelihood to recommend’ question is contained in Column A. Your spreadsheet should look a little bit like this example:

Net Promoter Formula for Excel
Sample Spreadsheet

To calculate your Net Promoter Score, simply paste the following formula into any cell (one caveat: you cannot paste this formula into the same column that contains the answer to your ‘likelihood to recommend’ question or else you will get a circular reference error.)

Net Promoter Score Excel Formula
NPS formula is pasted into cell B&

If the answer to your ‘likelihood to recommend’ question appears in a different column, simply change all instances of A:A the formula above to reference the appropriate column name. So, for example, if the answer to your ‘likelihood to recommend’ question is in Column E, replace all three instances of A:A with E:E as illustrated below:


What is Net Promoter?

What is Net Promoter?

Net Promoter is a methodology for measuring customer loyalty. It was developed jointly by Fred Reichheld, Bain Consulting and Satmetrix. Net Promoter was first introduced by Reichheld in an HBR article entitled “The One Number You Need to Grow“, and was later the topic of his book “The Ultimate Question“.

At the heart of the methodology is the idea that customer loyalty can best be predicted by the answer to a single question – “How likely are you to recommend (company name) to a friend or colleague?“. Respondents answer on a scale of 0 (not at all likely) to 10 (extremely likely). Based on the response to this question, respondents are categorized as Promoters (9-10), Passives (7-8) or Detractors (0-6). A company’s Net Promoter Score is simply the percentage of Promoters minus the percentage of Detractors.

Net Promoter is unique amongst loyalty measurement systems in several respects:

  • Net Promoter calls for a census-approach, advocating sending the survey out to all customers with the ultimate goal being an obscene response rate of >60%. This differs from traditional thinking, which advocates sampling the customer population.
  • Net Promoter surveys tend to be very sparse. Reichheld argues that loyalty surveys should consist of just two questions – the “ultimate question”, and a single text response field to capture additional customer comments.
  • Proponents of Net Promoter view it as a holistic framework. It is not just a survey – it is a set of business processes that surround the survey. “Closing the loop” with respondents and engaging the entire organization are considered vital components of a successful Net Promoter program.

There is considerable controversy around Net Promoter, much of it based on valid criticism. There is substantial data that indicated that the Ultimate Question may not, in fact, be the ultimate question when it comes to predicting customer loyalty. That said, I’ve found it to be a good-enough metric coupled with an exceptional framework that makes it easy to kickstart a customer-centric revolution within most organizations.

Further Reading

The Ultimate Question by Fred Reichheld

Answering the Ultimate Question by Richard Owen and Laura Brooks, PhD.