MONTH | CURRENT_USERS | PREVIOUS_USERS | CHURNED_USERS | CHURN_RATE | |
---|---|---|---|---|---|
1 | 2024-02-01 00:00:00.000 | 1565952 | |||
2 | 2024-03-01 00:00:00.000 | 2507347 | 1565952 | 1060737 | 67.737517 |
3 | 2024-04-01 00:00:00.000 | 1882774 | 2507347 | 1989070 | 79.329666 |
4 | 2024-05-01 00:00:00.000 | 1607322 | 1882774 | 1573705 | 83.584381 |
5 | 2024-06-01 00:00:00.000 | 3922504 | 1607322 | 1172894 | 72.971937 |
6 | 2024-07-01 00:00:00.000 | 2703760 | 3922504 | 3321300 | 84.672954 |
7 | 2024-08-01 00:00:00.000 | 3043929 | 2703760 | 1983215 | 73.35026 |
8 | 2024-09-01 00:00:00.000 | 4031995 | 3043929 | 2100881 | 69.018725 |
9 | 2024-10-01 00:00:00.000 | 8117692 | 4031995 | 2667513 | 66.158639 |
10 | 2024-11-01 00:00:00.000 | 8263438 | 8117692 | 5195161 | 63.998006 |
11 | 2024-12-01 00:00:00.000 | 10353849 | 8263438 | 4873859 | 58.981008 |
12 | 2025-01-01 00:00:00.000 | 946799 | 10353849 | 9636196 | 93.068732 |
Haisenbergchurn-rate
Updated 2025-03-29
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-- forked from retention-rate @ https://flipsidecrypto.xyz/studio/queries/d3cc3b28-cea5-4d16-af81-478166c17e9e
-- Step 1: Create CTEs to identify active users for each month
WITH monthly_active_users AS (
SELECT DISTINCT
date_trunc('month', block_timestamp) AS month,
sender AS address
FROM
aptos.core.fact_transactions
WHERE
block_timestamp >= DATE_TRUNC('month', CURRENT_DATE) - INTERVAL '13 months'
AND block_timestamp::date >= '{{Start_Date}}' AND block_timestamp::date <= '{{End_Date}}'
),
-- Step 2: Count active users per month
monthly_user_counts AS (
SELECT
month,
COUNT(DISTINCT address) AS active_users
FROM
monthly_active_users
GROUP BY
month
),
-- Step 3: Identify retained users
retained_users AS (
SELECT
a.month,
COUNT(DISTINCT a.address) AS retained_count
FROM
monthly_active_users a
JOIN
monthly_active_users b ON a.address = b.address AND a.month = b.month + INTERVAL '1 month'
GROUP BY
Last run: 2 months ago
12
734B
79s