COHORT_DATE | MONTHS | RETENTION_RATE | |
|---|---|---|---|
1 | 2025-03 | 1 | 32.85 |
2 | 2025-02 | 1 | 25.94 |
3 | 2025-02 | 2 | 21.81 |
4 | 2025-01 | 1 | 26.22 |
5 | 2025-01 | 2 | 21.47 |
6 | 2025-01 | 3 | 18.63 |
7 | 2024-12 | 1 | 19.92 |
8 | 2024-12 | 2 | 13 |
9 | 2024-12 | 3 | 11.53 |
10 | 2024-12 | 4 | 11.1 |
11 | 2024-11 | 1 | 25.39 |
12 | 2024-11 | 2 | 19.76 |
13 | 2024-11 | 3 | 15.12 |
14 | 2024-11 | 4 | 13.62 |
15 | 2024-11 | 5 | 12.95 |
16 | 2024-10 | 1 | 25.54 |
17 | 2024-10 | 2 | 20.5 |
18 | 2024-10 | 3 | 17.22 |
19 | 2024-10 | 4 | 14.25 |
20 | 2024-10 | 5 | 13.99 |
Flipside Axelar Analyststot RETENTION
Updated 2025-04-30
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with base as (
select
TX_FROM as TX_SIGNER,
min(date_trunc('month', BLOCK_TIMESTAMP)) over (partition by TX_SIGNER) as signup_date,
date_trunc('month', BLOCK_TIMESTAMP) as activity_date,
datediff('month', signup_date, activity_date) as difference
from axelar.core.fact_transactions
),
unp as (
select
TO_VARCHAR(signup_date, 'yyyy-MM') as cohort_date,
difference as months,
count (distinct TX_SIGNER) as users
from
base
where
datediff('month', signup_date, current_date()) <= 12
group by
1,2
order by
1
),
fine as (
select
u.*,
p.USERS as user0
from
unp u
left join unp p on u.COHORT_DATE = p.COHORT_DATE
where
p.MONTHS = 0
)
select
COHORT_DATE,
MONTHS,
round(100 * users / user0 , 2 ) as retention_rate
Last run: about 1 month ago
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