nps openmet

Improving an NPS Survey

The use of the Net Promoter Score (NPS) in surveys and studies on customer satisfaction, loyalty and experience is widespread and becoming increasingly popular. As discussed in another blog post, it has both advantages and disadvantages.

In this post, we are going to give you some simple strategies to include in NPS surveys, allowing for a better analysis of the results and a more effective action plan for improvement.

How can we improve NPS surveys?

NPS surveys have limited reliability and do not allow for a powerful analysis of customer satisfaction, loyalty and customer experience. Indicators based on averages of several questions have been shown to be more reliable and accurate than NPS and give a better insight into the reasons for customer satisfaction and loyalty.

So an easy way to improve our NPS survey is to include some additional questions on satisfaction with basic attributes of the product or service (e.g. customer service, price, appearance, etc.). We don’t have to add a lot (maybe 4 or 5 initially) and we can randomly rotate them so that, for example, only one is shown. This keeps the size of the survey small and means that we don’t overwhelm customers. These additional questions will be a goldmine because they will allow us to:

  • Find out the satisfaction with each attribute, so we can learn exactly where we need to improve.
  • Calculate aggregate indicators from averages of the answers to questions on attributes, ensuring greater accuracy and reliability.
  • Understand how the NPS relates to each attribute and its relative importance. If we create Importance-Satisfaction decision charts with the NPS question, we will know which “key” or attribute we need to act on as a priority to improve our NPS.

A second strategy for improving the analysis of results of NPS surveys is to segment customers. This can be done with data that we have before the customer responds (data stored in our CRM or customer database), or by including another additional question. This segmentation data will allow us to:

  • Filter and compare customers by segment to find out, for example, if customers in the north have a higher NPS than in the south. The plan of action will then be more accurate and hit “where it hurts”.
  • Statistically analyze the results and learn which segmentation variables have more variation and can therefore be a priority target for action.
  • Weight the results so that the opinions of some customers (for example, type A, with higher revenues) “weigh” more than others (type C, for example, with lower revenues). A weighted analysis can give us a more accurate and reliable picture of the actions needed to improve company performance.


NPS surveys are a popular and effective system for measuring customer satisfaction and customer loyalty but they are not a magic bullet. By including a few additional questions in the survey, we can alleviate some of its shortcomings and obtain more relevant data for an improved analysis of the results and a more effective plan of action for improvement.

More information on Customer Satisfaction.

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