bobby_daniel02_Sei User Segment Monthly
    Updated 10 days ago
    WITH user_initial_activity AS (
    SELECT
    FROM_ADDRESS,
    COUNT(*) AS tx_count,
    COUNT(DISTINCT DATE_TRUNC('day', block_timestamp)) AS active_days,
    SUM(VALUE) as total_value,
    MIN(block_timestamp) AS first_activity
    FROM sei.core_evm.fact_transactions
    WHERE block_timestamp >= DATEADD(MONTH, -{{Month_interval}}, CURRENT_DATE())
    GROUP BY FROM_ADDRESS
    ),

    -- Implement engagement-level classifications for user segmentation
    user_segments AS (
    SELECT
    FROM_ADDRESS AS address,
    CASE
    -- Premium Segment: Power users with strong activity retention
    WHEN (tx_count >= 5 AND active_days >= 2 AND total_value >= 500) THEN '🌟 High Value'
    -- Standard Segment: Users with balanced activity
    WHEN (tx_count >= 5 AND active_days >= 2 AND total_value >= 50) THEN '❇️ Medium Value'
    -- Inactive Segment: Little to no on-chain activity
    ELSE '⚠️ Low Value'
    END AS segment,
    first_activity
    FROM user_initial_activity
    WHERE first_activity >= DATEADD(MONTH, -{{Month_interval}}, CURRENT_DATE())
    ),

    -- Monitor individual user engagement on a monthly basis
    monthly_activity AS (
    SELECT
    us.address,
    us.segment,
    Last run: 10 days ago
    SEGMENT
    MONTH_NUM
    ACTIVE_ADDRESSES
    INITIAL_ADDRESSES
    RETENTION_PERCENTAGE
    1
    🌟 High Value12890128901100
    2
    🌟 High Value2177022890161.3
    3
    🌟 High Value380312890127.8
    4
    🌟 High Value443392890115
    5
    🌟 High Value51091289013.8
    6
    ❇️ Medium Value15857058570100
    7
    ❇️ Medium Value2284675857048.6
    8
    ❇️ Medium Value3117835857020.1
    9
    ❇️ Medium Value463085857010.8
    10
    ❇️ Medium Value52632585704.5
    11
    ⚠️ Low Value198071949807194100
    12
    ⚠️ Low Value294863298071949.7
    13
    ⚠️ Low Value383883298071948.6
    14
    ⚠️ Low Value461664498071946.3
    15
    ⚠️ Low Value524533398071942.5
    15
    611B
    58s