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DBT models for Protocol Labs churn analysis #19

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DBT models for Protocol Labs churn analysis #19

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DBT models for Protocol Labs churn analysis
innoobijr Mar 26, 2024
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popcornylu May 22, 2024
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popcornylu May 22, 2024
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113 changes: 113 additions & 0 deletions warehouse/dbt/models/playground/protocollabs__churn.sql
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WITH queries AS (

SELECT to_name,
year,
month,
contributors,
MAX(lost) AS lost,
MAX(gained) AS gained,
COUNT(DISTINCT(cum_contributors)) AS cum_contributors_count,
lag_contributors,
STRING_AGG(DISTINCT(cum_contributors), ', ') AS cum_contributors,
lag_contributors_count,
contributors_count
FROM (
SELECT to_name,
year,
contributors,
contributors_count,
lag_contributors,
lost,
gained,
month,
cum_contributors,
lag_contributors_count
FROM (
SELECT to_name,
year,
month,
STRING_AGG(contributors, ', ') OVER (PARTITION BY to_name,
year
ORDER BY month rows between unbounded preceding and current row) AS cum_contributors,
contributors,
COUNT(SPLIT(contributors)) AS contributors_count,
COALESCE(SUM(lost), 0) AS lost,
gained,
STRING_AGG(DISTINCT(lag_contributors), ', ') AS lag_contributors,
COUNT(lag_contributors) AS lag_contributors_count
FROM (
SELECT *,
(CASE WHEN strpos(contributors, lag_contributors) > 0 THEN 0
ELSE 1 END) AS lost
FROM (
SELECT to_name,
year,
month,
lag_contributors,
contributors,
gained
FROM (
SELECT to_name,
year,
month,
COALESCE(lag_contributors, '') AS lag_contributors,
COALESCE(SUM(gained), 0) AS gained,
STRING_AGG(contributors, ', ') AS contributors
FROM (
SELECT *,
(CASE WHEN strpos(lag_contributors, contributors) > 0 THEN 0
ELSE 1 END) AS gained
FROM (
SELECT to_name,
year,
month,
contributors,
lag_contributors
FROM (
SELECT *,
STRING_AGG(contributors, ', ') OVER (PARTITION BY to_name, year, month
ORDER BY month rows between unbounded preceding and current row) AS cum_contributors
FROM (
SELECT *,
LAG(month, 1) OVER (PARTITION BY to_name ORDER BY month) lag_month,
LAG(contributors, 1) OVER (PARTITION BY to_name ORDER BY month) lag_contributors
FROM (
SELECT to_name,
year,
month,
STRING_AGG(DISTINCT(from_name), ', ') AS contributors
FROM (
SELECT *,
EXTRACT(isoyear FROM time) AS year,
EXTRACT(week FROM time) AS week,
EXTRACT(day FROM time) AS day,
EXTRACT(month FROM time) AS month
FROM {{ ref("int_events") }} AS q1) AS q2
GROUP BY to_name, year, month
ORDER BY to_name, year, month) AS q3) AS q4) AS q5
CROSS JOIN UNNEST(SPLIT(contributors)) AS contributors ) AS q6 ) AS q7
GROUP BY to_name, year, lag_contributors, month
ORDER BY to_name, year, month ) AS q11
CROSS JOIN UNNEST(SPLIT(lag_contributors)) AS lag_contributors ) AS q12 ) AS q13
GROUP BY to_name, year, gained, contributors, month
ORDER BY to_name, year, month ) AS q14
CROSS JOIN UNNEST(SPLIT(cum_contributors))) AS q15
GROUP BY to_name, year, contributors, lag_contributors, contributors_count, lag_contributors_count, month
ORDER BY to_name, year, month
)


SELECT to_name,
year,
month,
lost,
gained,
cum_contributors,
cum_contributors_count,
lag_contributors,
lag_contributors_count,
contributors,
contributors_count,
(CAST(lost AS FLOAT64)/cum_contributors_count)*100 AS churn_prior,
((CAST(cum_contributors_count AS FLOAT64) - CAST(contributors_count AS FLOAT64))/CAST(cum_contributors_count AS FLOAT64))*100 AS churn_total
FROM queries