DATE | DAU | NEW_USERS | EXISTING_USERS | Share of New Users (%) | |
|---|---|---|---|---|---|
1 | 2024-08-25 00:00:00.000 | 22 | 22 | 0 | 100 |
2 | 2024-08-26 00:00:00.000 | 32 | 28 | 4 | 87.5 |
3 | 2024-08-27 00:00:00.000 | 83 | 76 | 7 | 91.5663 |
4 | 2024-08-28 00:00:00.000 | 56 | 53 | 3 | 94.6429 |
5 | 2024-08-29 00:00:00.000 | 33 | 26 | 7 | 78.7879 |
6 | 2024-08-30 00:00:00.000 | 30 | 27 | 3 | 90 |
7 | 2024-08-31 00:00:00.000 | 36 | 29 | 7 | 80.5556 |
8 | 2024-09-01 00:00:00.000 | 29 | 22 | 7 | 75.8621 |
9 | 2024-09-02 00:00:00.000 | 22 | 11 | 11 | 50 |
10 | 2024-09-03 00:00:00.000 | 132 | 121 | 11 | 91.6667 |
11 | 2024-09-04 00:00:00.000 | 9 | 5 | 4 | 55.5556 |
12 | 2024-09-05 00:00:00.000 | 15 | 6 | 9 | 40 |
13 | 2024-09-06 00:00:00.000 | 17 | 6 | 11 | 35.2941 |
14 | 2024-09-07 00:00:00.000 | 14 | 8 | 6 | 57.1429 |
15 | 2024-09-08 00:00:00.000 | 20 | 16 | 4 | 80 |
16 | 2024-09-09 00:00:00.000 | 28 | 19 | 9 | 67.8571 |
17 | 2024-09-10 00:00:00.000 | 41 | 17 | 24 | 41.4634 |
18 | 2024-09-11 00:00:00.000 | 31 | 21 | 10 | 67.7419 |
19 | 2024-09-12 00:00:00.000 | 32 | 18 | 14 | 56.25 |
20 | 2024-09-13 00:00:00.000 | 38 | 22 | 16 | 57.8947 |
Flipside Teamnew user over time
Updated 2 hours ago
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with daily_new as (
select
date_trunc('day', first_tx_date) as date,
count(1) as new_users
from datascience_public_misc.eclipse_analytics.signer_first_timestamp
group by 1
)
select
d.day_ as date,
d.dau,
coalesce(n.new_users, 0) as new_users,
d.dau - coalesce(n.new_users, 0) as existing_users,
(coalesce(n.new_users, 0) / nullif(d.dau, 0)) * 100 as "Share of New Users (%)"
from datascience_public_misc.eclipse_analytics.daily_n_signers d
left join daily_new n on d.day_ = n.date
order by d.day_;
Last run: about 2 hours agoAuto-refreshes every 3 hours
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