Marketing Metrics

Net Promoter Score

A customer-loyalty index, from −100 to +100, based on how likely customers are to recommend a brand.

Definition

Net Promoter Score (NPS) is a customer-loyalty metric — developed by Fred Reichheld with Bain & Company and Satmetrix and introduced in the 2003 Harvard Business Review article 'The One Number You Need to Grow' — that gauges loyalty from a single question: 'How likely is it that you would recommend [company/product] to a friend or colleague?' on a 0–10 scale. Respondents are grouped into Promoters (9–10), Passives (7–8), and Detractors (0–6), and the score is the percentage of Promoters minus the percentage of Detractors, yielding a number from −100 to +100.

Examples

100 responses: 60 promoters, 10 detractors, 30 passives → NPS = 60% − 10% = +50

A score above 0 is positive; above 50 is excellent; above 70 is world-class

A −20 NPS means detractors outnumber promoters and word-of-mouth is working against the brand

Calculation

How to Calculate

Survey customers with the single likelihood-to-recommend question (0–10). Calculate the percentage of Promoters (9–10) and the percentage of Detractors (0–6); Passives (7–8) are counted in the total but not in the subtraction. Subtract the Detractor percentage from the Promoter percentage. The result ranges from −100 (all detractors) to +100 (all promoters).

Formula

NPS = % Promoters − % Detractors

Operation Type

subtract

Formula Variables

% PromotersShare of respondents scoring 9–10
% DetractorsShare of respondents scoring 0–6

Industry Benchmarks for Net Promoter Score

Typical performance ranges by industry segment. Benchmarks vary by platform, audience maturity, and attribution window — treat these as starting points, not targets.

  • All industries (median)

    Typical range
    Positive (>0); industry medians ~30–45
    Median
    ~42 (2025)

    Benchmarks vary widely by sector; compare within your industry, not across. Interpretation bands (directional): >0 is good, >50 excellent, >70 world-class — trend over time matters more than a single absolute score. Bain finds NPS leaders grow at more than ~2x the rate of competitors over time.

Sources: Retently NPS Benchmarks 2025

Comparison

Related Metrics

Return on Ad Spend (ROAS)

Return on Ad Spend (ROAS) is a marketing performance metric that measures the revenue generated per dollar of advertising spend. Unlike ROI which considers all business costs, ROAS specifically evaluates advertising efficiency by comparing directly attributable revenue to ad spend. This metric is crucial for optimizing campaign performance, budget allocation, and overall marketing strategy.

Conversion Rate

Conversion rate measures the percentage of users who complete a defined conversion action relative to the total number who had the opportunity to convert. This metric evaluates the effectiveness of marketing efforts, user experience, and overall funnel efficiency in driving desired outcomes. Conversion actions can range from purchases and form submissions to content downloads and subscription signups.

Customer Lifetime Value (CLV)

Customer Lifetime Value predicts the total revenue a business can expect from a single customer account throughout the entire business relationship. This metric is crucial for determining sustainable customer acquisition costs, optimizing marketing spend, and identifying high-value customer segments. CLV helps businesses make informed decisions about customer acquisition and retention investments.

Marketing Efficiency Ratio (MER)

Marketing Efficiency Ratio measures the overall effectiveness of marketing spend by comparing total revenue to total marketing costs. It provides a holistic view of marketing performance across all channels and customer types, including both direct and indirect revenue attribution. Also known as 'blended MER' since it considers all revenue rather than just attributed revenue.

Churn Rate (CR)

Churn rate measures the proportion of customers who discontinue their relationship with a company during a specific timeframe. For subscription businesses, this means cancellations or non-renewals. For non-subscription businesses, churn is often defined as no purchase activity within a set period. It's a critical metric for evaluating customer retention and business health.

Customer Retention Rate (CRR)

Customer Retention Rate measures the proportion of customers who remain active with a company during a specific timeframe. For subscription businesses, this means continued subscriptions. For non-subscription businesses, retention is often defined as repeat purchase activity within a set period. It's a key metric for evaluating customer loyalty, satisfaction, and the effectiveness of retention strategies.

Return on Investment (ROI)

Return on Investment measures the profitability of an investment by comparing the net profit (revenue minus all costs) to the total investment cost. In marketing, it considers all costs including media spend, creative production, technology, overhead, and operational expenses, making it a more comprehensive metric than ROAS which focuses specifically on ad spend.

Moving Average

A moving average is a statistical calculation that creates a series of averages from different subsets of data over time. It helps identify trends by smoothing out short-term fluctuations and random outliers in metrics like CPC, CTR, or ROAS.

Exponential Moving Average (EMA)

An exponential moving average is a type of moving average that places greater weight on more recent data points, making it more responsive to recent changes while still smoothing out noise. This is particularly useful for metrics that require faster reaction to changes.

Statistical Significance

Statistical significance indicates whether an observed difference between variants in an experiment is likely to be due to random chance or represents a genuine effect. In advertising, it helps determine if differences in key metrics like CTR, conversion rate, or ROAS between ad variants or campaigns represent real performance differences rather than random fluctuations. This is crucial for making data-driven optimization decisions and avoiding false conclusions based on temporary variations.

Confidence Interval

A confidence interval provides a range of values that likely contains the true value of a metric, given a certain confidence level. In digital advertising, it helps marketers understand the reliability of their performance measurements and make more informed decisions about campaign optimization. Wider intervals suggest more uncertainty, while narrower intervals indicate more precise estimates of true performance.

Margin of Error

Margin of error represents the maximum expected difference between a sample-based estimate and the true population value, given a specific confidence level. In advertising, it helps quantify the reliability of metrics and determines required sample sizes for meaningful testing.

Sample Size

Sample size refers to the number of observations or data points collected in a sample, and is a crucial factor in determining the precision of statistical estimates. In advertising, it directly impacts the confidence, reliability, and validity of metrics such as conversion rates, click-through rates, and return on ad spend (ROAS). The larger the sample size, the more reliable the results, as smaller samples can lead to more variability and less confidence in the conclusions drawn from the data.

Population Mean

The population mean is the average value of a variable calculated using all members of a population, rather than just a sample. In digital advertising, it represents the true average value of metrics like conversion rate, CTR, or CPC across the entire audience or campaign. Unlike sample means which contain sampling error, the population mean is the actual parameter being estimated in statistical analysis, though it's often impossible to measure directly due to resource constraints.

Standard Deviation

Standard deviation quantifies the amount of variation in advertising metrics, helping marketers understand performance volatility and set appropriate monitoring thresholds. In digital advertising, it's crucial for identifying abnormal performance, setting realistic expectations, and creating robust optimization rules that account for natural performance fluctuations.

Net Revenue Retention (NRR)

Net Revenue Retention (NRR), also called Net Dollar Retention (NDR), measures how much recurring revenue a business retains and grows from its existing customer base over a period — including expansion (upsell, cross-sell, price increases) and net of contraction and churn — while excluding revenue from net-new customers. An NRR above 100% means the existing base grows on its own even before any new sales, which is why it is widely regarded as the single most important growth and durability metric for modern SaaS.

Viral Coefficient (K-Factor)

The Viral Coefficient — also called the K-factor — measures how many new users, on average, each existing user generates through invitations or referrals. It is the product of the average number of invitations sent per user and the conversion rate of those invitations. A K-factor above 1.0 produces self-sustaining exponential growth (each user more than replaces themselves); a K-factor below 1.0 amplifies but does not replace paid acquisition. It is a core measure of built-in virality and the strength of referral growth loops.

How AdSights helps you track Net Promoter Score

Promoters are the engine of organic, word-of-mouth acquisition — and the stories they tell are the raw material of high-performing social proof creative. AdSights helps teams identify which testimonial angles, proof points, and customer narratives actually move ad performance, turning the loyalty that NPS measures into creative that compounds. It also surfaces when acquisition is attracting poor-fit customers likely to become detractors, before they erode the score.

Want AI to track Net Promoter Score across your creative automatically?

Request early access

Frequently asked questions

Common questions about Net Promoter Score, answered.

What is Net Promoter Score (NPS)?
NPS is a customer-loyalty metric based on a single question — how likely you are to recommend a company or product on a 0–10 scale. Customers are grouped into Promoters (9–10), Passives (7–8), and Detractors (0–6), and the score is the percentage of Promoters minus the percentage of Detractors, ranging from −100 to +100. It was introduced by Fred Reichheld and Bain & Company in a 2003 Harvard Business Review article.
How is NPS calculated?
Survey customers with the likelihood-to-recommend question, then compute the percentage who are Promoters (scored 9–10) and the percentage who are Detractors (scored 0–6). Subtract the Detractor percentage from the Promoter percentage. Passives (7–8) count toward the total response base but are not added or subtracted. A company with 60% promoters and 10% detractors has an NPS of +50.
What is a good NPS score?
Any score above 0 means you have more promoters than detractors. Broadly, above 50 is considered excellent and above 70 world-class, while the all-industry median sits around 42 in recent benchmarks. Because expectations differ enormously by sector, the most useful comparison is against your own industry benchmark and your own trend over time, not a universal threshold.
Why does NPS matter for growth?
Because the willingness to recommend predicts both retention and referral — the two forces behind efficient growth. Bain's research finds NPS leaders grow at more than twice the rate of competitors over time, as promoters stay longer, spend more, and bring in new customers through word-of-mouth. NPS turns the diffuse idea of loyalty into a trackable number you can act on.
What are the limitations of NPS?
It's a single, lagging, stated-intent measure — people don't always act on their stated likelihood to recommend, and a lone number hides the 'why.' Sample bias, cultural differences in scoring, and survey timing all skew results. NPS is most useful when paired with the open-ended follow-up ('what's the primary reason for your score?') and with behavioral metrics like actual referrals, retention, and expansion rather than treated as a target to be gamed.

Related Terms

Customer Retention Rate

Related term

metrics, similar

Word-of-Mouth

Related term

general, component

Viral Coefficient (K-Factor)

Related term

metrics, similar

Net Revenue Retention (NRR)

Related term

metrics, similar