.png)
Net Promoter Score (NPS) is a metric that measures customer satisfaction. Simply said, it is about how likely customers are to recommend a given service or product. But is it enough to analyze just quantitative data to reach your customer experience?
Of course, no!
It is needed to be able to reach qualitative data from your customers. An NPS survey must have open-ended questions since they encourage respondents to provide detailed responses about their experiences or feedback. Detailed customer feedback enables a company to understand the customer perspective and adjust its actions.
In this article, we'll explain in detail how to make NPS answers useful and how to interpret the findings. Then, we'll look at how to use NPS data to expand your company and enhance customer satisfaction.
It allows you to quantify how loyal your customers are to your company. To assess NPS, customers are asked how likely they are to recommend your company on a scale of 1-10, a higher score is desirable.
The collected scores are categorized into three groups:
Promoters are those who respond with a score of 9 or 10 and are typically loyal and enthusiastic customers.
Passives are those who respond with a 7 or 8. They are pleased with a company’s product or service. However, they are unenthusiastic in general and can buy from competitors in the future.
Detractors are those who choose between 0 and 6. They are remarkably unhappy customers who perceive negatively a company or its relationship with customers. It can cause customer churn but more importantly, they tend to share their bad experiences.
A business growth strategy needs to take distinct approaches for each of these customer categories.
The percentage of detractors (customers who wouldn't suggest you) must be subtracted from the percentage of promoters to determine your net promoter score (customers who would recommend you).
How to calculate a net promoter score:
Let’s think that you have 100 customers. 30% of them are detractors and 50% of them are promoters. Your NPS will be (50%-30%=20). It represents a 20% chance your customers will suggest you to potential customers. It is basic and countable, right? But are you able to reach potential customers just by reaching quantitative data?
We recommend you give your customers a space to comment. In this way, you have qualitative feedback about how you can improve your product or service. Qualitative feedback comes from open-ended questions after the customer ratings.
Customers typically find it challenging to express their honest ideas while posting reviews. However, an open-ended question in an NPS survey gives respondents the confidence to express their concerns in-depth.
According to the low rating, a standard open-ended question for a detractor would look like this:
What was the disappointing experience that we encountered with us?
In this way, unsatisfied customers can express themselves and you can take action accordingly. But, how?
So, even if using NPS for your company is a good way of assessing customer satisfaction, you need a tool to analyze answers coming to open-ended questions collected with NPS.
A survey analytics tool will help you in this case. A survey analytics tool can catch valuable insights from text data and verbatim comments. These insights will provide you with a deeper understanding of your customers’ scores on your company.
Calculation of the NPS score is simple but the difficult one is answering the question ‘is this a good NPS score?’
Absolute NPS:
It's "poor" if your score is less than 0. The majority of your customers aren't satisfied with your brand, aren't likely to recommend you, and are willing to switch to a rival at any time.
A score between 0 and 30 is considered "acceptable." Although the experiences of many of your consumers could be better, you must be doing something right.
A score of 30 to 50 is considered "very solid". It's no small achievement when your product consistently lives up to expectations and the majority of your consumers are so pleased they'd refer you to a friend.
The top brands for Customer Experience typically fall into this category if your score is 50 or higher. You're on the verge of being unattainable, and customers may think that your brand is amazing!
Relative NPS
The relative NPS approach compares your score to those of other businesses in your sector. You can run a google search to compare your brand NPS with other brands. It is a way to do a competitive analysis in terms of customer satisfaction. Just show them “being the best” with your solid net promoter score!
Identify Your NPS score: Is it good or bad?
The traditional approach is to compare the NPS scores on a yearly basis. However, we're living in a fast-evolving world, which means that yearly comparisons no longer make any sense. Instead, observing the daily/weekly/yearly evolution of NPS scores on very precise areas of your business will help you understand deeper and act quicker. Also, the numbers are meaningless without improvements.
It is necessary to use qualitative data to improve your score. In that way, you will be able to know “signal NPS” which means highlighting consumers that appear to be pleased or unhappy, but understanding the "why" of customer behavior.
NPS offers you an analysis of quantitative data. However, there are other steps in NPS analysis. With these scores, some open-ended questions and answers are indicating the reason for the dissatisfaction or satisfaction.
But reading whole answers manually takes a lot of time. So, their analysis by Artificial Intelligence will help you to understand the reasons behind customers’ ideas and sentiments.
Pivony, in this regard, offers a platform that can show valuable insights about your customers.
Specific topics that are spoken by customers generated by AI enable you to detect issues easily without the need for manual effort.
These topics come with sentimental value. You see an example below, that shows the bubble views of topics generated by AI. So, topics are classified according to their sentiment. Green bubbles mean positive sentiment, while red bubbles indicate a negative sentiment.
Besides, Pivony AI engine can understand the intent of the customer and categorizes it as
So, you can do more than a sentiment analysis with Pivony. By going directly to the intent section, you can categorize your customers’ needs and demands in a few clicks.
After analyzing it, it is a crucial question of how you can act. With a built-in email marketing feature, you can directly contact your target customers. Besides, Slack and Trello integrations allow you to contact related departments that will take action about target customers and assign tasks to them.
Guides, Tutorials, and Comparative Studies and more...
