NPS scores are calculated by averaging customers’ likelihood of recommending a brand in the future on a 1-10 scale. They can then be used to inform you where your brand stacks up against your direct competitors.
But, it is important to note that your NPS score is heavily influenced by a number of factors starting with the industry you are in – we will get into this later on.
First, we’ll show you how to calculate your brand’s NPS score, shed light on what’s considered a good NPS score for your industry, and share some practical methods to improve your score.
Feel free to click through to the section most useful to you.
Time for some numbers.
NPS scores are calculated by asking customers about their ‘referral intention’ i.e., how likely they are to suggest your product to others going forward.
NPS takes this data (gathered on a scale of 1-not likely to 10-extremely likely) and groups customers into three categories:
Promoters (9-10) Customers who are pleased and passionate about your product and are very likely to spread the word about you.
Passives (7-8) Indifferent customers who are at risk of switching to another product. This is a key group whose NPS survey responses can be further analyzed to prevent customer churn.
Detractors (1-6) Unhappy customers who might share negative feedback about your product. While unfortunate, unpacking their issues and seeking out and taking in their feedback is invaluable for finding solutions to their problems and improving your product overall.
Once you’ve sorted customer responses into these three groups, you can plug results into this handy-dandy NPS formula:
So, say 60% of your responses are Promoters and 20% are detractors, 60 - 20 = 40, so your NPS would be 40, a positive rating!
With this knowledge, you’re ready to delve into what makes up a good NPS score versus a bad one.
A “good” NPS score is anything above 0. Exceeding the score of zero indicates overall customer loyalty to your brand. Per Doter, in 2021 on average, anything above 50 can be considered “Excellent” and anything above 75 “World-class”.
Here is a graphic to help visualize this NPS spectrum:
As you can see, anything below zero indicates a need for improvement – meaning there are more Detractors than Promoters, whereas the closer we get to an NPS of 100, the higher level of customer loyalty (100 meaning all promoters and 0 detractors).
However, when reflecting on what your NPS score means for your brand in particular, it is important to note that an NPS is just a single metric (useful when comparing to competitor’s scores) not a holistic reflection of your total customer experience (CX).
Other metrics, such as CSAT (Customer Satisfaction Score), exist to provide additional context for measuring customer satisfaction at each stage of the customer journey.
NPS score and CSAT score are closely related but serve different functions. As opposed to your NPS score, your CSAT score measures customer satisfaction with your product or service after each touchpoint (purchase, onboarding customer support interactions, etc) not just at the end of their experience.
So you’ve calculated your NPS score and it’s not what you expected. Not to worry – this is very common as NPS varies greatly from industry to industry depending on the product or service provided.
Let’s dig into the below graph for greater context.
As you can see, when we take the average benchmarks of each industry, there is a huge gap between, say, Ecommerce and SaaS. It follows that customers shopping for pleasure online tend to have a more positive experience than people in great need of software solutions.
For this reason, it is important to view your NPS score in context, meaning relative to competition in your industry rather than simply as an absolute on the -100 to 100 scale.
Industry average isn’t the only outlying factor affecting your NPS score. location, timing, survey channel, and customer tolerance level must also be taken into account when considering your NPS Score’s significance.
Let’s get into why.
Where customers live tends to skew NPS due to different and diverse cultural practices and standards worldwide. Europeans, for example, tend to rate more conservatively (clustering in the middle) whereas feedback from customers in the United States tends to be extreme (lots of 1’s and 10’s).
Modern attitudes and expectations also play a factor. The average NPS score of customer responses has dropped in value in recent years – likely due to increased competition driving customer standards higher.
For example, during Covid online sales have skyrocketed increasing competition and, as a result, so has the demand for a great customer experience.
The time and manner by which the survey is delivered can also affect your NPS score. When the survey is provided and at what time in the process can play a part in the customers’ NPS responses or lack thereof.
If the survey is presented too soon, the customer may be annoyed, if it is too late, they may have moved on to another task and/or have forgotten their view on the experience.
Your customer complaint tolerance level indicates how much your customers’ lives and/or businesses depend on your product.
This can also be calculated by simply asking your customers, “On a scale of 1-10, 1 being not likely and 10 being very likely, how likely are you to become angry if our service can’t address your needs”.
If your average is closer to 10, your business is in a low-tolerance industry, meaning customers have low tolerance if your service doesn’t meet their needs, if you are closer to 1, you are in a high-tolerance industry, meaning the opposite.
Despite existing in low-tolerance industries, brands such as Uber, Southwest and Netflix have achieved higher tolerance levels by emphasizing greater transparency, improving accessibility, and listening to their customers’ voices at a greater number of touchpoints.
Having weighed all of those factors, you might wonder what the next step is – improvement of customer satisfaction is always the goal but exactly how and what should you change about your service? Luckily, your NPS survey doesn’t exist in a vacuum – it can also gather qualitative, actionable responses by the simple addition of an open-ended question following the numerical scale response.
By gathering responses to open-ended questions you can collect insightful, qualitative customer data that can generate actionable information with the goal of locating specific areas for product or service improvement.
So, let’s get up and do something with those open-ended responses!
Unlocking and acting on your customer’s qualitative feedback following the survey is the surest way to raise your NPS score.
Your score, good or bad, is by its nature a quantitative metric and primarily useful for measuring yourself against brands similar to yours. But, as mentioned previously, it is only a metric and exists to be improved upon.
This is where understanding your customers’ qualitative responses is an absolutely essential step towards improving your brand and thus your customer satisfaction.
So how exactly do you know what to improve from your written customer responses?
The best (and simplest) approach to improving your brand's NPS score is to address what drove your customers to leave their previous scores in the first place. By digging into the qualitative, written responses following your NPS survey you can further understand your company's voice of the customer and unpack their motivations.
Of course, this qualitative data, which comes in the form of text responses, might seem daunting to sort through. Here is where text analysis tools and services can help.
Rather than parsing the data by hand, you can use automated text analysis models, like MonkeyLearn’s NPS classifier. Through custom and case-tailored machine learning, this tool can be put to work on your survey response data and reveal which aspects of your product customers are having problems with (Customer Support, Ease of Use, Features, and Pricing). Combined with MonkeyLearn’s sentiment analyzer, you can find out how customers feel about each of those aspects.
Text analysis tools allow you to save time and resources by analyzing your open-ended NPS responses in real time.
After analyzing your survey data using machine learning, you’ll have a more accurate idea of what is and isn’t working for your customers.
Now you can make informed adjustments and likely raise that pesky NPS score!
Once you’ve defined what a good NPS score is for your industry and what a given score means by delving into open-ended responses, you’ll be able to effectively improve upon your products and services.
Furthermore, by understanding the impact of environmental and survey delivery-related factors you can seek to improve your process for collecting NPS feedback.
Looking for tools to help improve your NPS score? Sign up to try out MonkeyLearn’s suite of tools for free.
May 6th, 2021