SignalQL

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Canonical SignalQL examples ​

Each example lists the product question, SignalQL, logical output shape, and a compiled Postgres SQL pattern summary. For exact generated SQL text + params, run the query through the CLI or MCP run_signalql.

Dataset assumptions match fixtures/seed.sql.

Funnel — signup to activation ​

Question: What share of signups reach activated within the window?

SignalQL:

FUNNEL "signup" THEN "activated" FROM events DURING LAST 28 DAYS

Shape: One row with step_1, step_2, … counts and conversion_rate.

SQL pattern: Filtered aggregate with COUNT(DISTINCT CASE WHEN event_name = $k …) (see compiler output).

Retention starter — active vs signup volume ​

Question: How many users fired signup vs activated recently?

Use two queries (v0.1 keeps retention algebra minimal):

COUNT users FROM events WHERE event_name = "signup" DURING LAST 28 DAYS
COUNT users FROM events WHERE event_name = "activated" DURING LAST 28 DAYS

Shape: Single-row count each.

SQL pattern: Two parameterized COUNT(DISTINCT user_id) queries over events filtered by event_name and time window.

Growth — daily signups ​

Question: How many signup events per day?

COUNT events FROM events WHERE event_name = "signup" DURING LAST 30 DAYS GROUP BY DAY

Shape: Rows (day, count) ordered by day.

SQL pattern: SELECT date_trunc('day', timestamp) AS day, COUNT(*) ... GROUP BY day ORDER BY day.

Onboarding dropoff — funnel slice ​

Question: Where do users drop between onboarding completion and activation?

FUNNEL "onboarding_complete" THEN "activated" FROM events DURING LAST 14 DAYS

Shape: Step counts + conversion_rate.

SQL pattern: Distinct-user conditional counts per funnel step with derived conversion ratio.

Feature usage — view items ​

Question: How often was view_item tracked?

COUNT events FROM events WHERE event_name = "view_item" DURING LAST 14 DAYS GROUP BY DAY

Shape: (day, count) rows.

SQL pattern: Day-bucketed aggregate over events filtered by event_name and bounded timestamp.

Segmentation — pro plan purchases ​

Question: Among purchases tagged plan=pro on the event, how many distinct users?

COUNT users FROM events WHERE properties.plan = "pro" AND event_name = "purchase" DURING LAST 28 DAYS

Shape: Single-row count.

SQL pattern: COUNT(DISTINCT user_id) with predicates on properties.plan, event_name, and timestamp window.

These examples are mirrored in fixtures/query-fixtures.json and the playground presets.