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2026-02-01_churn/2026-01-02_query-03-sms-appts-checklist.sql
2026-02-02 16:26:10 -05:00

152 lines
7.2 KiB
SQL

-- 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
),
-- Messages sent by era
sms_counts AS (
SELECT texts.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_texts.user_id, sent_texts.created_at::date - users.created_at::date AS created_age
FROM config, sent_texts JOIN users ON sent_texts.user_id = users.id
WHERE sent_texts.created_at >= config.date_cutoff
AND users.created_at >= config.date_cutoff
) texts
GROUP BY texts.user_id
),
-- Appointments by era
appointment_counts AS (
SELECT appts.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 appointments.user_id, appointments.created_at::date - users.created_at::date AS created_age
FROM config, appointments JOIN users ON appointments.user_id = users.id
WHERE appointments.created_at >= config.date_cutoff
AND users.created_at >= config.date_cutoff
) appts
GROUP BY appts.user_id
),
-- Checklists created by era
checklist_counts AS (
SELECT checks.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 checklist_templates.user_id, checklists.created_at::date - users.created_at::date AS created_age
FROM config, checklist_templates
JOIN users ON checklist_templates.user_id = users.id
JOIN checklists ON checklists.checklist_template_id = checklist_templates.id
WHERE checklist_templates.created_at >= config.date_cutoff
AND checklists.created_at >= config.date_cutoff
AND users.created_at >= config.date_cutoff
) checks
GROUP BY checks.user_id
),
-- Checklist events created by era
checklist_filled_counts AS (
SELECT events.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 employees.user_id, checklist_item_events.created_at::date - users.created_at::date AS created_age
FROM config, employees
JOIN users ON employees.user_id = users.id
JOIN checklist_item_events ON checklist_item_events.employee_id = employees.id
WHERE checklist_item_events.created_at >= config.date_cutoff
AND checklist_item_events.created_at >= config.date_cutoff
AND users.created_at >= config.date_cutoff
) events
GROUP BY events.user_id
)
-- Finally, we'll flatten it all out into a repurposable flat table
SELECT users_to_examine.id,
users_to_examine.category,
users_to_examine.month_created,
users_to_examine.lifespan,
COALESCE(sms_counts.short_term, 0) AS sms_short_term,
COALESCE(sms_counts.medium_term, 0) AS sms_medium_term,
COALESCE(sms_counts.long_term, 0) AS sms_long_term,
COALESCE(sms_counts.total, 0) AS sms,
COALESCE(appointment_counts.short_term, 0) AS appointments_short_term,
COALESCE(appointment_counts.medium_term, 0) AS appointments_medium_term,
COALESCE(appointment_counts.long_term, 0) AS appointments_long_term,
COALESCE(appointment_counts.total, 0) AS appointments,
COALESCE(checklist_counts.short_term, 0) AS checklists_short_term,
COALESCE(checklist_counts.medium_term, 0) AS checklists_medium_term,
COALESCE(checklist_counts.long_term, 0) AS checklists_long_term,
COALESCE(checklist_counts.total, 0) AS checklists,
COALESCE(checklist_filled_counts.short_term, 0) AS checklists_filled_short_term,
COALESCE(checklist_filled_counts.medium_term, 0) AS checklists_filled_medium_term,
COALESCE(checklist_filled_counts.long_term, 0) AS checklists_filled_long_term,
COALESCE(checklist_filled_counts.total, 0) AS checklists_filled
FROM users_to_examine
LEFT OUTER JOIN sms_counts ON sms_counts.user_id = users_to_examine.id
LEFT OUTER JOIN appointment_counts ON appointment_counts.user_id = users_to_examine.id
LEFT OUTER JOIN checklist_counts ON checklist_counts.user_id = users_to_examine.id
LEFT OUTER JOIN checklist_filled_counts ON checklist_filled_counts.user_id = users_to_examine.id
;