In SQL, net Promoter Score for the whole period is ROUND(100.0 * (SUM(nps_promoters) - SUM(nps_detractors)) / (SUM(nps_promoters) + SUM(nps_passives) + SUM(nps_detractors)), 2) over the monthly table. On the sample data it returns 43.02.
NPS = (Promoters − Detractors) ÷ All respondents × 100
What you need
Net Promoter Score (NPS) is the percentage of survey respondents who are promoters (score 9–10) minus the percentage who are detractors (0–6), on the question "how likely are you to recommend us?". You need these columns, here from the sample file monthly.csv:
- nps_promoters: NPS promoters (9–10)
- nps_passives: NPS passives (7–8)
- nps_detractors: NPS detractors (0–6)
CREATE TABLE monthly (
month TEXT, -- 'YYYY-MM'
nps_promoters INTEGER,
nps_passives INTEGER,
nps_detractors INTEGER
);Step by step
- Load monthly.csv into a table called monthly. The table only needs the month column and the columns below.
- Run the first query to get one row per month.
- Run the whole-period query. It adds up each column first and divides once; averaging the monthly results gives a different, usually wrong, answer.
The queries
SELECT
month,
ROUND(100.0 * (nps_promoters - nps_detractors) / NULLIF(nps_promoters + nps_passives + nps_detractors, 0), 2) AS nps
FROM monthly
ORDER BY month;SELECT ROUND(100.0 * (SUM(nps_promoters) - SUM(nps_detractors)) / NULLIF(SUM(nps_promoters) + SUM(nps_passives) + SUM(nps_detractors), 0), 2) AS nps
FROM monthly;What you should get
Run against the sample data, the code above returns these values:
| Month | nps_promoters | nps_passives | nps_detractors | nps |
|---|---|---|---|---|
| 2026-01 | 142 | 61 | 37 | 43.75 |
| 2026-02 | 150 | 66 | 42 | 41.86 |
| 2026-03 | 161 | 70 | 39 | 45.19 |
| 2026-04 | 148 | 72 | 48 | 37.31 |
| 2026-05 | 170 | 75 | 41 | 45.10 |
| 2026-06 | 181 | 79 | 45 | 44.59 |
| Whole period | 952 | 423 | 252 | 43.02 |
(952 − 252) ÷ (952 + 423 + 252) × 100 = 43.02
Notes for SQL
- Integer columns divide as integers in PostgreSQL, SQLite and SQL Server, so 3 / 4 gives 0. Multiplying by 1.0 (or 100.0) first makes the division decimal.
- NULLIF(x, 0) turns a zero denominator into NULL, so the query returns NULL for that row instead of failing with a division-by-zero error.
- Tested on SQLite and DuckDB. SUM, NULLIF and ROUND work the same in PostgreSQL, MySQL and BigQuery; SQL Server uses TOP instead of LIMIT where a query has one.
Where net Promoter Score misleads
- Passives (7–8) count in the denominator even though they are not in the numerator.
- Small samples swing a lot; one more detractor among 40 replies moves NPS by several points.
- Who answers matters. Surveys sent right after delivery and surveys sent after a support ticket give different scores.
The full explanation, with a calculator, is on the Net Promoter Score (NPS) page.
Same metric, other tools
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About the data on this page
The figures come from a small made-up dataset, printed above in full so you can check every number by hand. Download it as monthly.csv. The results are computed from those rows when the page is built, and the Excel formulas, SQL and Python on these pages are run against the same rows before publishing, so the code and the answers agree.
To get these numbers from your own data without writing formulas, try AnalyzeIt: ask in plain words and it shows the working behind every figure.
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