Use SQL to get monthly churn count and churn rate - sql

Question

Currently using Postgres 9.5
I want to calculate monthly churn_count and churn_rate of the search function.
churn_count: number of users who used the search function last month but not this month
churn_rate: churn_count/total_users_last_month
My dummy data is:
CREATE TABLE yammer_events (
occurred_at TIMESTAMP,
user_id INT,
event_name VARCHAR(50)
);
INSERT INTO yammer_events (occurred_at, user_id, event_name) VALUES
('2014-06-01 00:00:01', 1, 'search_autocomplete'),
('2014-06-01 00:00:01', 2, 'search_autocomplete'),
('2014-07-01 00:00:01', 1, 'search_run'),
('2014-07-01 00:00:02', 1, 'search_run'),
('2014-07-01 00:00:01', 2, 'search_run'),
('2014-07-01 00:00:01', 3, 'search_run'),
('2014-08-01 00:00:01', 1, 'search_run'),
('2014-08-01 00:00:01', 4, 'search_run');
Ideal output should be:
|month |churn_count|churn_rate_percentage|
|--- |--- |--- |
|2014-07-01|0 |0
|2014-08-01|2 |66.6 |
In June: user 1, 2 (2 users)
In July: user 1, 2, 3 (3 users)
In August: user 1, 4 (2 users)
In July, we didn't lose any customer. In August, we lost customer 2 and 3, so the churn_count is 2, and the rate is 2/3*100 = 66.6
I tried the following query to calculate churn_count, but the result is really weird.
WITH monthly_activity AS (
SELECT distinct DATE_TRUNC('month', occurred_at) AS month,
user_id
FROM yammer_events
WHERE event_name LIKE 'search%'
)
SELECT last_month.month+INTERVAL '1 month', COUNT(DISTINCT last_month.user_id)
FROM monthly_activity last_month
LEFT JOIN monthly_activity this_month
ON last_month.user_id = this_month.user_id
AND this_month.month = last_month.month + INTERVAL '1 month'
AND this_month.user_id IS NULL
GROUP BY 1
db<>fiddle
Thank you in advance!

Answer 1

An easy way to do it would be to aggregate the users in an array, and from there extract and count the intersection between the current month and the previous one using the window function LAG(), e.g.
WITH j AS (
SELECT date_trunc('month',occurred_at::date) AS month,
array_agg(distinct user_id) AS users,
count(distinct user_id) AS total_users
FROM yammer_events
GROUP BY 1
ORDER BY 1
)
SELECT month::date,
cardinality(LAG(users) OVER w - users) AS churn_count,
(cardinality(LAG(users) OVER w - users)::numeric /
LAG(total_users) OVER w::numeric) * 100 AS churn_rate_percentage
FROM j
WINDOW w AS (ORDER BY month
ROWS BETWEEN 1 PRECEDING AND CURRENT ROW);
month | churn_count | churn_rate_percentage
------------+-------------+-------------------------
2014-06-01 | |
2014-07-01 | 0 | 0.00000000000000000000
2014-08-01 | 2 | 66.66666666666666666700
(3 rows)
Note: this query relies on the extension intarray. In case you don't have it in your system, just hit:
CREATE EXTENSION intarray;
Demo: db<>fiddle

Answer 2

WITH monthly_activity AS (
SELECT distinct DATE_TRUNC('month', occurred_at) AS month,
user_id
FROM yammer_events
WHERE event_name LIKE 'search%'
)
SELECT
last_month.month+INTERVAL '1 month',
SUM(CASE WHEN this_month.month IS NULL THEN 1 ELSE 0 END) AS churn_count,
SUM(CASE WHEN this_month.month IS NULL THEN 1 ELSE 0 END)*1.00/COUNT(DISTINCT last_month.user_id)*100 AS churn_rate_percentage
FROM monthly_activity last_month
LEFT JOIN monthly_activity this_month
ON last_month.month + INTERVAL '1 month' = this_month.month
AND last_month.user_id = this_month.user_id
GROUP BY 1
ORDER BY 1
LIMIT 2
I think my way is more circuitous but easier for beginners to understand. Just for your reference.