Understanding your survey’s Net Promoter Score calculation

Net Promoter Score (NPS) is a popular customer loyalty tracking metric that is frequently included within consumer surveys.

NPS is based upon on a simple premise; growth of your business is directly related to your customer’s willingness to “promote” or recommend your product or services to others.  Think of NPS as a “bottom line” tracking metric that summarizes your customer’s experiences and loyalty into one understandable and explainable measure.

The NPS calculation starts with a survey data containing the question “On a scale of 0 to 10, what is the likelihood that you would recommend this (product or service) to a friend or relative?”

The score behind the NPS is calculated by subtracting the percentage of the bottom 7 box responses, in other words those indicating they would be very unlikely to recommend, from the percentage of the top 2 box responses, or respondents that would be very likely to recommend, as depicted within the illustration below.

NPS scores can take on any value within the range of 100% to -100%, with 100% being the desired or objective NPS.

The point of collecting and tracking NPS metric is to take action when the NPS data suggests room for improvement.   An NPS score in isolation has limited value; perspective is required to bring meaning to the data.   Perspective can be obtained by tracking of the NPS score over time, by comparing the NPS score with NPS scores of similar products or services, or by segmenting the survey data by respondent subgroups and comparing the NPS scores of the subgroups.

Segmenting of the respondent data is made possible through secondary data that can be linked to the respondent (example: receipt transaction number linking to CRM data) or through additional structured and unstructured data presented to the respondent within the survey questionnaire.   It is extremely important to include the appropriate survey questions that will provide for a meaningful segmentation of the NPS results.

For example, you would want to know the NPS differences between heavy user and light user segments, especially if heavy users comprise the vast majority of your current sales volume.   If you don’t have a way of determining segmentation from your survey or secondary data sources, then you may be missing out on a key opportunity to gain additional insight from your NPS data.

There are many other factors that direct relate to the value of NPS metric such as sampling, sample size, and the percentage answering the NPS survey question.

PAI would welcome the opportunity to demonstrate how PAI’s mTAB™ service would benefit your understanding of the meaning implications of your NPS metrics.  Please visit the PAI website to schedule a no-obligation review of your current NPS program.

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