i_danKaia: New Vs Returning Users
    Updated 2025-02-26
    WITH first_tx AS (
    SELECT
    from_address
    , MIN(block_timestamp) AS first_quarter
    FROM kaia.core.fact_transactions
    GROUP BY 1
    ),
    user_activity AS (
    SELECT
    t.from_address
    , DATE_TRUNC('quarter', t.block_timestamp) AS activity_quarter
    , DATE_TRUNC('quarter', f.first_quarter) AS first_tx_quarter
    FROM kaia.core.fact_transactions t
    JOIN first_tx f ON t.from_address = f.from_address
    )
    SELECT
    activity_quarter AS "Quarter"
    , COUNT(DISTINCT CASE WHEN activity_quarter = first_tx_quarter THEN from_address END) AS "New Users"
    , COUNT(DISTINCT CASE WHEN activity_quarter > first_tx_quarter THEN from_address END) AS "Returning Users"
    , COUNT(DISTINCT from_address) AS "Quarterly Users" --
    FROM user_activity
    GROUP BY 1
    ORDER BY 1


    Last run: about 1 month ago
    Quarter
    New Users
    Returning Users
    Quarterly Users
    1
    2019-04-01 00:00:00.0004950495
    2
    2019-07-01 00:00:00.000631002276631278
    3
    2019-10-01 00:00:00.0004189834188944208728
    4
    2020-01-01 00:00:00.00028021031213022923405
    5
    2020-04-01 00:00:00.0001700407969061797313
    6
    2020-07-01 00:00:00.00071539665391780787
    7
    2020-10-01 00:00:00.00057482868202643030
    8
    2021-01-01 00:00:00.000401986127865529851
    9
    2021-04-01 00:00:00.00053413980906615045
    10
    2021-07-01 00:00:00.00050088997045597934
    11
    2021-10-01 00:00:00.00024261792884182714597
    12
    2022-01-01 00:00:00.00015826057345482317153
    13
    2022-04-01 00:00:00.00018563506533362509686
    14
    2022-07-01 00:00:00.0007703444010081171352
    15
    2022-10-01 00:00:00.000744665247207991872
    16
    2023-01-01 00:00:00.0009978642710911268955
    17
    2023-04-01 00:00:00.00038162422778004094042
    18
    2023-07-01 00:00:00.00020238423675302391372
    19
    2023-10-01 00:00:00.00020575813052642362845
    20
    2024-01-01 00:00:00.00049910232838985274921
    24
    1KB
    201s