NPS (Net Promoter Score)

The percentage of customers who would recommend you, minus the percentage who'd warn others off.

When to use this

You have a product with at least a few hundred users and you want a single number that tracks goodwill over time. NPS is most useful as a trend (this quarter vs last quarter, same segment) and as a way to flag which accounts are at risk before they churn.

When NOT to use this

Very early products with under 100 users. The sample is too small to mean anything. As the sole input to a retention strategy. NPS tells you something is wrong, not what to fix. As a customer satisfaction score. NPS asks about recommendation intent, which is a different thing.

Inputs

Survey responses on a 0-10 scale to "How likely are you to recommend us?"
Segmentation tags: plan tier, account size, tenure. Without these, the aggregate hides everything that matters.
Account ACV (optional but recommended): so you can weight detractors by dollar risk, not headcount.

Classification:

Score	Bucket	What it means
9-10	Promoter	Will actively recommend
7-8	Passive	Satisfied but unenthusiastic
0-6	Detractor	Will warn others off

The math

NPS = % Promoters - % Detractors

Passives count toward the denominator but not the score. The range is -100 to +100. Anything positive is more promoters than detractors. Anything above 30 is strong for most B2B contexts (illustrative).

A worked example

A B2B SaaS surveys 500 customers. Results: 220 promoters (44%), 180 passives (36%), 100 detractors (20%).

NPS = 44 - 20 = 24

A 24 is below the B2B SaaS average of ~30 (illustrative). Now layer in revenue. If the average ACV is $12k and detractors churn at roughly 2x the base rate, the 100 detractors represent about $1.2M of ARR at elevated risk over the next year. That number is the one you take to your CS leader, not the 24.

How pmtoolkit does it differently

We pair the score with the dollar value of the detractor bucket. A 5-point drop in NPS means nothing until you know which $1M of ARR just got more fragile. We also flag sample size. If you surveyed 47 people, the margin of error on the score is roughly +/- 14 points, which makes any quarter-over-quarter move noise.

Common mistakes

Reading a 5-point move as signal. Below ~400 respondents, that's inside the margin of error.
Surveying happy-path users only. If you only ask the customers who logged in this week, your detractors are already gone.
Quarterly comparison without year-over-year. Many products have seasonal NPS. Compare Q2 to Q2.
Treating NPS as CSAT. Recommendation intent is a stronger and rarer signal than satisfaction. A passive isn't unhappy; they just won't sell for you.