First round of fiddling

2026-01-02_query-02-email.sql

@@ -0,0 +1,83 @@
+-- First establish some base parameters for our users
+WITH config AS (
+    SELECT
+        14 AS short_term,
+        90 AS medium_term,
+        360 AS long_term,
+        CAST('2023-01-01' AS timestamp) AS date_cutoff
+),
+-- Then establish a standard core set of user data
+users_with_churn_stats AS (
+    SELECT id, active, billing_state,
+           DATE_TRUNC('month', created_at) AS month_created,
+           created_at, free_trial_ends_at, updated_at,
+           updated_at::date - created_at::date AS lifespan
+    FROM users, config
+    -- We'll only look at newish users.
+    WHERE created_at >= config.date_cutoff
+),
+-- Next use that core data to extract the records we want to analyze
+-- and categorize them by date and status
+users_to_examine AS (
+    -- First the users who exited just after the trial
+    SELECT 'quick-exit' AS category, uwcs.*
+    FROM users_with_churn_stats uwcs, config
+    WHERE billing_state = 'CHURNED'
+      AND lifespan <= config.short_term
+
+    UNION
+
+    -- Next, users who gave the tools some time but still left
+    SELECT 'fair-trial' AS category, uwcs.*
+    FROM users_with_churn_stats uwcs, config
+    WHERE billing_state = 'CHURNED'
+      AND lifespan < config.medium_term
+      AND lifespan > config.short_term
+
+    UNION
+
+    -- Then some longer-time users who still churned.
+    -- We'll cut this off after 6 months since afterwards
+    -- company closures, etc. could factor in.
+
+    SELECT 'short-termer' AS category, uwcs.*
+    FROM users_with_churn_stats uwcs, config
+    WHERE billing_state = 'CHURNED'
+      AND lifespan >= config.medium_term
+      AND lifespan < config.long_term
+
+    UNION
+
+    -- Finally, people who are still kicking.
+    -- This cohort is going to be a little wrong for older
+    -- dates since it only includes those who are STILL around.
+    SELECT 'active-user' AS category, uwcs.*
+    FROM users_with_churn_stats uwcs, config
+    WHERE BILLING_STATE != 'CHURNED'
+		AND lifespan >= config.long_term
+),
+-- Emails sent by era
+email_counts AS (
+    SELECT email.user_id,
+           SUM(CASE WHEN created_age < config.short_term THEN 1 ELSE 0 END) AS short_term,
+           SUM(CASE WHEN created_age >= config.short_term AND created_age < config.medium_term THEN 1 ELSE 0 END) AS medium_term,
+           SUM(CASE WHEN created_age >= config.medium_term AND created_age < config.long_term THEN 1 ELSE 0 END) AS long_term,
+           COUNT(*) AS total
+    FROM config, (
+        SELECT sent_emails.user_id,  sent_emails.created_at::date - users.created_at::date AS created_age
+        FROM config, sent_emails JOIN users ON sent_emails.user_id = users.id
+        WHERE sent_emails.created_at >= config.date_cutoff
+            AND users.created_at >= config.date_cutoff
+    ) email
+    GROUP BY email.user_id
+)
+-- Finally, we'll flatten it all out into a repurposable flat table
+SELECT users_to_examine.id,
+       users_to_examine.category,
+       COALESCE(email_counts.short_term, 0) AS emails_short_term,
+       COALESCE(email_counts.medium_term, 0) AS emails_medium_term,
+       COALESCE(email_counts.long_term, 0) AS emails_long_term,
+       COALESCE(email_counts.total, 0) AS emails
+FROM users_to_examine
+    LEFT OUTER JOIN email_counts ON email_counts.user_id = users_to_examine.id
+;