Skari

Data Analysis

From statistics and modeling to finance and marketing analytics — all in one place.

StatisticsFrom hypothesis testing to time series and clustering — a wide range of statistical methods.SEMType the research topic — the model, the survey and a report in thesis order follow.Auto ModelingTrains and compares several machine-learning models automatically, and explains why they predicted what they did.

Specialized Analysis

Quality

Survey

Go beyond standard surveys with Conjoint, AHP, and Price Sensitivity — plus CSAT, NPS, and more.

Explore Survey

ConjointEstimates preference share and market share by attribute combination.AHP PriorityDerives priority ranking for each item through pairwise comparison.Price Sensitivity (PSM)Analyzes the optimal price point and resistance range from responses.

Other Methods

Gabor-Granger Kano Model Driver Analysis MaxDiff TURF Usability (SUS)NPS Brand Tracking View All Methods

Net Promoter Score (NPS)

Understand the customers behind NPS.

Start with one recommendation question, then see who your promoters and detractors are, what is shaping their scores, and how recommendation intent relates to real customer behavior.

NPS ScoreScore DistributionSegment AnalysisScore DriversReal BehaviorAuto Conclusions

Try Free See Brand Tracking

−100…+100

NPS Scale

Groups Tracked

20+

Segment Support

Auto Interpretation

One score is not enough

01You track the NPS score, but not which customers sit behind it.

02The score changed, but the reason for the change is unclear.

03You cannot tell whether recommendation intent is reflected in real behavior.

04Detractors are visible as a group, but their specific risks and experiences are not.

Skari connects the score to customer groups, experiences, and actual behavior.

FROM SETUP TO FIELDWORK

The 0-10 score is built in. See exactly what respondents answer.

Edit the labels, add a follow-up — the Detractor/Passive/Promoter breakdown updates automatically.

createsurvey · csat

NPS score

RequiredSensitive

How likely are you to recommend us to a friend or colleague?

Required

Left label

e.g. Not at all likely

Right label

e.g. Extremely likely

Preview

012345678910

Short textQ2

What is the main reason for your score?

Description

Optional description for this question

Allow multi-line input

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Question 1 of 8

How likely are you to recommend us to a friend or colleague? *

Not at all likely0-6
Detractor7-8
Passive9-10
PromoterExtremely likely

‹ Previous

* Required

Next ›

Left: the standard NPS question, ready to customize. Right: exactly what respondents see — the color-coded 0-10 scale, updated as you edit the labels.

FROM RESPONSES TO RESULTS

Customers and experiences behind NPS

Every figure below comes from one real example study — 220 respondents, run through the same engine your own data runs on.

NPS in context

The summary combines NPS with the promoter, passive, and detractor split and a concise interpretation of the main findings.

Executive Summaryn=40

NPS

Average

Promoters

29.5%

n=65

Passives

44.5%

n=98

Detractors

25.9%

n=57

This study surveyed 220 respondents. Critically, it tracks real behavior: Promoters report 100% repurchase intent versus 19.3% among Detractors — NPS is not just sentiment, it predicts what customers actually do next.

Full score distribution

The full 0–10 distribution shows how responses are divided across promoter, passive, and detractor groups.

Score Distribution (0–10)

Detractors (0–6)Passives (7–8)Promoters (9–10)

At-risk customer groups

Compare NPS by tenure and usage frequency to identify customer groups with higher churn risk.

NPS by Segment

By Tenure

< 6 months n=60

+33

6–12 months n=55

+24

1–2 years n=45

-4

3–5 years n=30

-23

> 5 years n=30

-53

By Usage

Daily n=41

+22

Weekly n=62

+26

Monthly n=57

-23

Rarely n=60

-7

Experiences influencing NPS

Respondents identify the aspect that most influenced their score, and the results rank those factors by response share.

What Drives the Score

Product quality

35%

Reliability

23.6%

Ease of use

14.1%

Price / value for money

11.4%

Customer support

10%

Other

5.9%

NPS and customer behavior

Repurchase intent, actual recommendations, and negative reviews by group — not inferred, asked directly as follow-up questions.

NPS & Real Behavior

Key finding

Promoters n=65

100%

Passives n=98

84.7%

Detractors n=57

19.3%

GroupRecommendedNeg. review

Promoters86.2%10.8%

Passives49%20.4%

Detractors28.1%56.1%

Recommended actions

The overview table states the facts; the conclusions are generated directly from the analysis results above them.

Overview & Conclusions

Respondents220

NPS+4

Estimate range-5.8 — +13.8

Promoters65 (29.5%)

Passives98 (44.5%)

Detractors57 (25.9%)

1The score is +4, but its estimate range runs from -5.8 to +13.8 — it contains zero, so read it as "around break-even", not as positive.

2More than 5 years customers have the lowest NPS (-53) — the segment most at risk of churn.

3"Product quality" is the most-cited driver of scores (35%), while the people who cite price (-44) and support (-36) score far below everyone else.

4Promoters’ repurchase intent (100%) is far higher than Detractors’ (19.3%).

556.1% of Detractors have actually written a negative review, against 10.8% of Promoters — a direct reputational risk.

A COMPLETE REPORT

See the full report from summary to conclusion.

The six cards above are fragments of this. Scroll the real output end to end, right here on the page.

NPS example — 220 simulated respondents

Analysis Settings

220 responses.

Executive Summary

220 respondents · NPS +4

This NPS study surveyed 220 respondents, yielding an overall score of +4 (Average) — 29.5% Promoters, 44.5% Passives, and 25.9% Detractors. Critically, this tracks real behavior: Promoters report 100% repurchase intent versus only 19.3% among Detractors — the NPS score is not just sentiment, it predicts what customers actually do next.

This round’s score

The share who would recommend, minus the share who would not. It sits between −100 and +100.

Metric	Value
Respondents	220
Survey period	2026.05.11 – 2026.06.01
Net Promoter Score	+4 (Average)
Promoters (9–10)	65 (29.5%)
Passives (7–8)	98 (44.5%)
Detractors (0–6)	57 (25.9%)

Interpretation

65 would recommend, 98 are neutral and 57 would not. A higher score means promoters outweigh detractors. Look at what the 44.5% neutral customers experienced too — that is where an improvement can turn into a recommendation.

Responses by score

How many people chose each score from 0 to 10. The colour shows which group it falls into.

Detractors (0–6)Passives (7–8)Promoters (9–10)

Interpretation

NPS of +4 is considered Average. Promoters outnumber Detractors — more customers are likely to recommend than to discourage others.

Customer groups compared

Recommendation intent by how long they've been a customer, how often they use the product, and any other segment picked in the config panel.

By Customer Tenure

Less than 6 months n=60

+33

6–12 months n=55

+24

1–2 years n=45

-4

3–5 years n=30

-23

More than 5 years n=30

-53

By Usage Frequency

Daily n=41

+22

Weekly n=62

+26

Monthly n=57

-23

Rarely n=60

-7

What respondents said drove the score

Which aspect respondents said most influenced their score.

How it relates to the other questions askedkey finding

The other questions in the same survey, split by group. Useful for finding which part of the experience to improve.

Group	Repurchase intent	Actually recommended	Wrote negative review
Promotersn=65	100%	91.8%	11.5%
Passivesn=98	84.7%	64.9%	27%
Detractorsn=57	19.3%	40%	80%

Interpretation

Promoters' repurchase intent (100%) is far higher than Detractors' (19.3%) — NPS is tracking real purchase behavior here, not just sentiment.

How much the score could move

The same customers, asked again, would not give exactly this number. This is the range it would fall in.

Score

Range (± 1.96 SE)

-5.8 ~ 13.8

Range (resampled 2000×)

-6.4 ~ 13.6

One person moves it by

0.455

Interpretation

With 220 responses the score sits in -5.8 to 13.8, a band 19.6 points wide, and a single respondent changing bucket moves it by 0.455. Read a change smaller than that band as not yet separable from who happened to answer.

Conclusions and next steps

Action points generated directly from the analysis results above.

Overall NPS is +4 (Average) — 29.5% Promoters, 44.5% Passives, 25.9% Detractors.

More than 5 years customers have the lowest NPS (-53) — the segment most at risk of churn.

"Product quality" is the most-cited driver of scores (35% of respondents) — the single biggest lever for moving NPS.

Promoters' repurchase intent (100%) is far higher than Detractors' (19.3%) — NPS is tracking real purchase behavior, not just sentiment.

80% of Detractors have actually written a negative review — this is a direct reputational risk, not a hypothetical one.

Track this same survey on a regular cadence (as waves in a Survey Series) to see whether the interventions above actually move the score.

NPS = Promoters% − Detractors%. Promoters: 9–10; Passives: 7–8; Detractors: 0–6. Repurchase intent = top-2-box on the repurchase-likelihood question. n = 220.

Scroll to explore the full report

IN THE REPORT

What is behind your NPS

See the score, the customers behind it, the experiences shaping it, and the behavior associated with each group.

NPS score

Calculate the standard score from a single 0–10 recommendation question.

Promoter/Passive/Detractor split

See the number and share of customers in each NPS group.

Score distribution

Review the full 0–10 distribution, not only the final score.

Tenure & usage segments

Compare NPS by how long and how often customers use the service.

Custom segment picker

Split NPS by any categorical question in the survey.

Score drivers, ranked

Identify the experiences customers say had the greatest influence on their score.

NPS vs. real behavior

Compare repurchase intent, real recommendations, and negative reviews across NPS groups.

Auto-generated conclusions

Turn the main findings into clear statements you can use in a report.

Turn NPS into action

Connect the score to customer groups, experiences, and behavior so you know where to act.

Get Started Free

Analysis Settings

220 responses.

Executive Summary

220 respondents · NPS +4

This round’s score

The share who would recommend, minus the share who would not. It sits between −100 and +100.

Metric	Value
Respondents	220
Survey period	2026.05.11 – 2026.06.01
Net Promoter Score	+4 (Average)
Promoters (9–10)	65 (29.5%)
Passives (7–8)	98 (44.5%)
Detractors (0–6)	57 (25.9%)

Interpretation

Responses by score

How many people chose each score from 0 to 10. The colour shows which group it falls into.

Detractors (0–6)Passives (7–8)Promoters (9–10)

Interpretation

NPS of +4 is considered Average. Promoters outnumber Detractors — more customers are likely to recommend than to discourage others.

Customer groups compared

Recommendation intent by how long they've been a customer, how often they use the product, and any other segment picked in the config panel.

By Customer Tenure

Less than 6 months n=60

+33

6–12 months n=55

+24

1–2 years n=45

-4

3–5 years n=30

-23

More than 5 years n=30

-53

By Usage Frequency

Daily n=41

+22

Weekly n=62

+26

Monthly n=57

-23

Rarely n=60

-7

What respondents said drove the score

Which aspect respondents said most influenced their score.

How it relates to the other questions askedkey finding

The other questions in the same survey, split by group. Useful for finding which part of the experience to improve.

Group	Repurchase intent	Actually recommended	Wrote negative review
Promotersn=65	100%	91.8%	11.5%
Passivesn=98	84.7%	64.9%	27%
Detractorsn=57	19.3%	40%	80%