The Net Promoter Score (NPS) question lets you measure customer loyalty. Your score represents the net percentage of your customers who are promoters of your company or brand.

The NPS methodology is based on the following question:

How likely is it that you would recommend this company to a friend or colleague?
(Not at all likely) 0 1 2 3 4 5 6 7 8 9 10 (Extremely likely)

Based on the respondent’s answer, they’ll fall into one of three groups:

Promoters9–10Loyal enthusiasts who will stay with your company and urge their friends and colleagues to do the same.
Passives7–8Satisfied but unenthusiastic customers who can be easily wooed by the competition.
Detractors0–6Unhappy customers who have the potential to damage your brand.

To calculate your score, we subtract the percentage of Detractors from the percentage of Promoters. A positive score indicates that your promoters outweigh your detractors.

When you use our pre-built NPS template or question type, we automatically calculate your score. Simply add an NPS question into your survey or choose from several survey templates that include the NPS question.

  • Adding and Editing NPS Questions
  • Using NPS Templates

Start from a template! Many of our expert survey templates include the NPS question. Browse templates »

If you send your survey via Email Invitation, you can embed the NPS question in your email so customers can respond to your survey with just one click in their email.

You can also send an NPS survey using any of our collector types.

We automatically calculate your NPS in the Analyze Results section of your survey. Your NPS can range from -100 (all Detractors) to 100 (all Promoters). Any positive number score means that the percentage of customers who are Promoters outweighs the percentage of your customers who are Detractors.

By default, your score will be expressed in an easy-to-use Gauge Chart. Below the chart in the data table, you can see the exact number of Detractors, Passives, and Promoters.

  • Calculating NPS
  • Customizing NPS Charts
  • Benchmarks
  • Filter Rules
  • Data Trends