START_MONTH | NEW_USERS | ONE_MONTH_LATER | TWO_MONTHS_LATER | THREE_MONTHS_LATER | FOUR_MONTHS_LATER | FIVE_MONTHS_LATER | SIX_MONTHS_LATER | |
|---|---|---|---|---|---|---|---|---|
1 | 2023-10 | 3,266,885 | 63.00% | 55.00% | 51.00% | 47.00% | 45.00% | 43.00% |
2 | 2023-11 | 1,369,730 | 50.00% | 40.00% | 35.00% | 33.00% | 32.00% | 30.00% |
3 | 2023-12 | 12,652,371 | 13.00% | 10.00% | 8.00% | 7.00% | 6.00% | 3.00% |
4 | 2024-01 | 7,040,655 | 49.00% | 26.00% | 20.00% | 18.00% | 15.00% | 12.00% |
5 | 2024-02 | 4,313,819 | 40.00% | 31.00% | 28.00% | 23.00% | 20.00% | 12.00% |
6 | 2024-03 | 4,584,825 | 44.00% | 37.00% | 29.00% | 24.00% | 11.00% | 14.00% |
7 | 2024-04 | 5,166,495 | 33.00% | 23.00% | 18.00% | 7.00% | 12.00% | 13.00% |
8 | 2024-05 | 4,051,609 | 30.00% | 18.00% | 8.00% | 11.00% | 12.00% | 11.00% |
9 | 2024-06 | 9,302,268 | 66.00% | 27.00% | 15.00% | 17.00% | 15.00% | 16.00% |
10 | 2024-07 | 7,890,977 | 20.00% | 17.00% | 18.00% | 15.00% | 17.00% | 18.00% |
11 | 2024-08 | 2,744,289 | 15.00% | 27.00% | 14.00% | 15.00% | 16.00% | 10.00% |
12 | 2024-09 | 869,449 | 24.00% | 35.00% | 11.00% | 10.00% | 9.00% | 8.00% |
13 | 2024-10 | 623,938 | 15.00% | 36.00% | 11.00% | 9.00% | 8.00% | |
14 | 2024-11 | 449,674 | 15.00% | 20.00% | 10.00% | 9.00% | ||
15 | 2024-12 | 621,435 | 14.00% | 7.00% | 7.00% | |||
16 | 2025-01 | 535,460 | 4.00% | 3.00% | ||||
17 | 2025-02 | 462,198 | 4.00% | |||||
18 | 2025-03 | 622,743 |
feyikemiNEAR Users Retention Rate
Updated 2024-10-05
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⌄
WITH Users_data AS(
SELECT
Block_timestamp,
tx_signer
FROM near.core.fact_transactions
),
Users_activity AS (
SELECT
tx_signer AS Users_address,
Date_trunc('month', Block_timestamp) AS Activity_month,
Min(Date_trunc('month', Block_timestamp)) OVER (PARTITION BY tx_signer) AS First_activity_month,
DATEDIFF(
'month',
MIN(Date_trunc('month', Block_timestamp)) OVER (PARTITION BY tx_signer),
Date_trunc('month', Block_timestamp)
) AS Month_difference
FROM Users_data
WHERE Block_timestamp >= '2023-10-01'
),
new_users AS (
SELECT
first_activity_month,
COUNT(DISTINCT users_address) AS new_user_count
FROM Users_activity
GROUP BY 1
),
returning_users AS (
SELECT
first_activity_month,
month_difference,
COUNT(DISTINCT users_address) AS returning_user_count
FROM Users_activity
WHERE month_difference <> 0
Last run: 2 months ago
18
1KB
350s