NPS (Marketing context): Net Promoter Score for prospects/market (vs customers).
Also known as: NPS
Computable definition
The canonical formula in the GASP formula grammar. The MCP server compiles it to SQL over the datasets listed below.
(count(field.nps_score where field.survey_type = 'prospect' and field.nps_score >= 9) - count(field.nps_score where field.survey_type = 'prospect' and field.nps_score <= 6)) / count(field.nps_score where field.survey_type = 'prospect') * 100Unit: score
Notes: Same NPS arithmetic applied to prospect and market respondents rather than customers.
Data requirements
Grain: Per survey response · Frequency: Per response · Aggregation: event · Staged: no · Main source: Survey Tool.
| Field | Dataset | Type |
|---|---|---|
nps_score | survey_response | integer |
survey_date | survey_response | date |
survey_type | survey_response | string |
Example SQL (Postgres)
SELECT ((CAST(((SELECT COUNT(nps_score) FROM survey_response WHERE survey_date >= :period_start AND survey_date <= :period_end AND (survey_type = 'prospect' AND nps_score >= 9)) - (SELECT COUNT(nps_score) FROM survey_response WHERE survey_date >= :period_start AND survey_date <= :period_end AND (survey_type = 'prospect' AND nps_score <= 6))) AS DOUBLE PRECISION) / NULLIF((SELECT COUNT(nps_score) FROM survey_response WHERE survey_date >= :period_start AND survey_date <= :period_end AND survey_type = 'prospect'), 0)) * 100) AS nps_marketing_context From an agent: with the GASP MCP server, call
lookup_metric({ "name": "NPS (Marketing context)" }) or generate_query({ "metric": "NPS (Marketing context)", "adapter": "<your adapter JSON>" }).
What It Tells You
Brand perception in broader market.