So you have decided to conduct some customer or employee research, but are not sure what type of research to choose in order to achieve the understanding you are looking for. There are so many types of surveys and interviews you could use, but which would help you the most? This article aims to help answer that question, by defining both Net Promoter Score and customer satisfaction, outlining their differences and explaining why your NPS and customer satisfaction scores might be different.
Net Promoter Score (NPS) is a measurement of customer/employee experience and loyalty. An NPS question will ask "How likely would you be to recommend ___ to a friend or colleague", with a 10-point scale for responses (where 0 is "highly unlikely", and 10 is "highly likely"). Those who score between 0 and 6 are considered "detractors", meaning they are likely to talk negatively about the company and their products or services, and deter potential customers. Respondents who rate the company at a 7 or 8 are labelled "passive" as they are unlikely to either recommend or oppose the brand, while those who provide a score of either 9 or 10 are considered "promoters", being likely to advocate for the brand.
To calculate the NPS the percentage of detractors is subtracted from the percentage of promoters, which provides a score anywhere between -100 (everyone is a detractor) and 100 (everyone is a promoter). Positive scores are considered good, while scores over 50 are excellent. Calculating the NPS can be done either manually, through use of a spreadsheet, or through an NPS calculator tool.
If you would like to calculate your NPS in an Excel spreadsheet, and have the NPS responses in a column, you can use the following formula (replace N1:N2 with the range containing your scores).
Alternatively, you can use the calculator below to work out your Net Promoter Score.
Net Promoter Score can be a quick and convenient way to measure your customer or employee loyalty over time. NPS surveys can be conducted in a short time period, making them ideal for businesses looking for a way to monitor how their employees and customers feel about any changes made to the company or its products and services. For example, a brand may wish to conduct a quarterly NPS survey to keep close track of whether their customers' loyalty to the brand is changing; the faster an issue can be identified, the quicker it can be dealt with. In this situation, if the brand's NPS were to drop unexpectedly, it would provide an opportunity for the brand to conduct more in-depth research to identify the cause and make appropriate changes.
While using Net Promoter Score can provide a general indication of how loyal your customers are, as well as a benchmark for comparison over time, it is flawed in the same way as any quantitative research method. Responses are influenced by multiple factors; some types of people may be more cynical and likely to put a 6 or 7 even if they would recommend the business because they see room for improvement, which could impact some businesses more than others. The type of business can also influence the sort of responses they get, as customers of a very niche business may be unlikely to recommend it due to its irrelevance for the majority of people they know.
For this reason, it is better to use NPS as a source of comparison within your own business, to identify changes over time and areas of improvement, rather than getting too hung up on the number itself. It is also more effective to use NPS alongside qualitative methodology, such as providing an open-ended question for customers to outline the reasoning behind their NPS rating. You can read more about using mixed methodology to get the most benefit out of your research here.
Customer satisfaction is a measure of how happy your customers are with the products and services they have received. You can measure customer satisfaction using a couple of potential methods.
Customer Satisfaction Score, or CSAT, is usually calculated through a single question, along the lines of "How would you rate your overall satisfaction with ___". Responses will usually sit on a 5-point scale and can range from "very unsatisfied" to "very satisfied". The score would then be the percentage of satisfied customers, which can be calculated in Excel using the following formula.
You can also use our simple CSAT calculator below.
CSAT can help you to gain a general idea of whether or not the majority of your customers are satisfied with the products and services they have received. If you are looking to understand how satisfied your customers are specifically with your customer service, then you can instead utilise the Customer Effort Score (CES) method. Instead of asking customers to rate their satisfaction, CES asks customers to rate how much effort it took them to have their issue resolved. It most commonly utilises a 7-point scale, and we recommend asking the question "on a scale of 1-7, how easy was it for you to ___?", where 1 is "very difficult" and 7 is "very easy". The traditional CES questions asks how much effort a task took, but those accustomed to NPS and CSAT would expect a high score to be good; hence, we recommend asking how easy a task is, instead. The CES is the mean of all responses (7 is a perfect score). The theory behind CES is that companies do not need to go above and beyond with their customer service, but simply need to fulfill the customer's needs as efficiently as possible.
The key difference between customer satisfaction and NPS is that the latter specifically aims to measure customer loyalty and the likelihood that a customer would recommend a brand, not necessarily how happy they are with the company's products and services. While this may sound counter-intuitive (why would someone choose not to recommend a product they are very satisfied with?), it becomes a lot clearer when you put it into context.
Think about a large corporation with whom you have had experience in the past. Perhaps you shop through an online store frequently, and you have been very happy with their service. Your purchases usually arrive the next day, in good condition. Whenever there has been a problem with your purchase, you have been able to easily return it and received a quick refund to your bank account. This is what we would call high customer satisfaction; you are very content with the service you have been provided, and you've never encountered a problem.
However, you may be aware of some of the unethical activity the online store has been known for in the past. For this reason, you may not wish to associate with them - even though you are very satisfied with their service, you would not recommend the company because you do not want to be known to support their actions. This would mean your customer satisfaction score is high, but you would be categorised as a detractor in the NPS calculation.
This demonstrates a very key element of research and statistical data, that is so frequently overlooked: statistics are not meant to be taken out of context. Net Promoter Scores are intended to act as a figure that quantifies and compliments your other research findings. It is convenient to be able to say that your customer loyalty sits at 67 on a scale of -100 to 100, but it does not tell you the details of why your customers are so loyal, or if there is anything you could be doing better. Looking at your NPS of 67 alongside comments from your customers can help you understand the motivations and reasons behind the figure, allowing you to really drill down into the most important factors of your brand identity. Conducting a customer satisfaction survey alongside your NPS survey can help you to truly understand the customer experience associated with your brand.
If you are looking to conduct customer or employee research and would like support in choosing your methodology and asking the right questions, you can contact Mackman Research here to find out what we can do for you.
Research and Insight Junior
Jess has a Masters degree in Cybercrime Investigation, and a Bachelors in Sociology and Criminology. She loved the research and statistics aspects of her degrees and now enjoys experiencing the practical applications of research, alongside writing content and experimenting with new software. Her favourite part of research is finding meaningful answers hidden within data.More About Jess
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