dbt_cloud/models/marts/reporting/rep_shipping__rfm.sql

-- AVAILABLE FILTER VALUE 
-- Alot of companies do not have 
{% set custom_one_year_from_date = modules.datetime.datetime.now(modules.pytz.timezone("Asia/Kuala_Lumpur")).date() - modules.datetime.timedelta(365) %}
{% set custom_one_year_to_date = modules.datetime.datetime.now(modules.pytz.timezone("Asia/Kuala_Lumpur")).date() %}

-- RFM list values defined using percentile from dashboard [SHIPPING] rfm
{% set recency_list_lifetime = [120,240,360,480] %}
{% set frequency_list_lifetime = [1,2,8,24] %}
{% set monetary_list_lifetime = [0.74,3.01,7.87,27.27] %}

{% set recency_list_one_year = [120,240,360,480] %}
{% set frequency_list_one_year = [1,2,7,16] %}
{% set monetary_list_one_year = [0.76,3.00,7.36,22.80] %}


-- IMPORT
WITH origin_warehouse_shipping_packing_lists AS (
    SELECT * FROM {{ ref('fct_shipping__origin_warehouse_shipping_packing_lists') }}
),

companies AS (
    SELECT * FROM {{ ref('dim_shipping__companies') }}
),


-- LOGIC
company_shipping_order_one_year AS(

    SELECT
        origin_warehouse_shipping_packing_lists.sub_company_id,
        companies.sub_company_marking_id,
        COUNT(origin_warehouse_shipping_packing_lists.origin_warehouse_shipping_packing_list_id)            AS number_of_packing_list_one_year,
        MAX(origin_warehouse_shipping_packing_lists.origin_warehouse_shipping_order_created_datetime)       AS last_packing_list_created_datetime_one_year,
        DATEDIFF(day, last_packing_list_created_datetime_one_year, CURRENT_DATE())                          AS day_after_last_packing_list_one_year, 
        SUM(origin_warehouse_shipping_packing_lists.total_package_cbm)                                      AS total_package_cbm_one_year
    
    FROM origin_warehouse_shipping_packing_lists

    LEFT JOIN companies
        ON (origin_warehouse_shipping_packing_lists.sub_company_id = companies.sub_company_id)

    WHERE 
        origin_warehouse_shipping_order_status IN ('COMPLETED','APPROVED')
        AND
        origin_warehouse_shipping_order_created_datetime >= '{{ custom_one_year_from_date }}'
        AND
        origin_warehouse_shipping_order_created_datetime < '{{ custom_one_year_to_date }}'
    
    GROUP BY
        origin_warehouse_shipping_packing_lists.sub_company_id,
        companies.sub_company_marking_id
 
),

company_rfm AS (

    SELECT
        origin_warehouse_shipping_packing_lists.sub_company_id,
        companies.sub_company_marking_id,

        MAX(origin_warehouse_shipping_packing_lists.origin_warehouse_shipping_order_created_datetime)   AS last_packing_list_created_datetime,
        
        DATEDIFF(day, last_packing_list_created_datetime, CURRENT_DATE() )                              AS day_after_last_packing_list_lifetime,
        MAX(company_shipping_order_one_year.day_after_last_packing_list_one_year)                       AS day_after_last_packing_list_one_year,

        COUNT(origin_warehouse_shipping_packing_lists.origin_warehouse_shipping_packing_list_id)        AS number_of_packing_list_lifetime,
        MAX(company_shipping_order_one_year.number_of_packing_list_one_year)                            AS number_of_packing_list_one_year,

        SUM(origin_warehouse_shipping_packing_lists.total_package_cbm)                                  AS total_package_cbm_lifetime,
        MAX(company_shipping_order_one_year.total_package_cbm_one_year)                                 AS total_package_cbm_one_year

    FROM origin_warehouse_shipping_packing_lists

    LEFT JOIN company_shipping_order_one_year
        ON (origin_warehouse_shipping_packing_lists.sub_company_id = company_shipping_order_one_year.sub_company_id)
    
    LEFT JOIN companies
        ON (origin_warehouse_shipping_packing_lists.sub_company_id = companies.sub_company_id)

    WHERE
        origin_warehouse_shipping_packing_lists.origin_warehouse_shipping_order_status IN ('COMPLETED','APPROVED')

    GROUP BY
        origin_warehouse_shipping_packing_lists.sub_company_id,
        companies.sub_company_marking_id

),

calculate_rfm AS (

    SELECT
        *,

        CASE
            WHEN day_after_last_packing_list_lifetime <= {{recency_list_lifetime[0]}} THEN 5
            WHEN (day_after_last_packing_list_lifetime > {{recency_list_lifetime[0]}} AND day_after_last_packing_list_lifetime <= {{recency_list_lifetime[1]}}) THEN 4
            WHEN (day_after_last_packing_list_lifetime > {{recency_list_lifetime[1]}} AND day_after_last_packing_list_lifetime <= {{recency_list_lifetime[2]}}) THEN 3
            WHEN (day_after_last_packing_list_lifetime > {{recency_list_lifetime[2]}} AND day_after_last_packing_list_lifetime <= {{recency_list_lifetime[3]}}) THEN 2
            WHEN day_after_last_packing_list_lifetime > {{recency_list_lifetime[3]}} THEN 1
            ELSE -999
        END AS r_score_lifetime,

        CASE
            WHEN number_of_packing_list_lifetime <= {{frequency_list_lifetime[0]}} THEN 1
            WHEN (number_of_packing_list_lifetime > {{frequency_list_lifetime[0]}} AND number_of_packing_list_lifetime <= {{frequency_list_lifetime[1]}}) THEN 2
            WHEN (number_of_packing_list_lifetime > {{frequency_list_lifetime[1]}} AND number_of_packing_list_lifetime <= {{frequency_list_lifetime[2]}}) THEN 3
            WHEN (number_of_packing_list_lifetime > {{frequency_list_lifetime[2]}} AND number_of_packing_list_lifetime <= {{frequency_list_lifetime[3]}}) THEN 4
            WHEN number_of_packing_list_lifetime > {{frequency_list_lifetime[3]}} THEN 5
            ELSE -999
        END AS f_score_lifetime,

        CASE
            WHEN total_package_cbm_lifetime <= {{monetary_list_lifetime[0]}} THEN 1
            WHEN (total_package_cbm_lifetime > {{monetary_list_lifetime[0]}} AND total_package_cbm_lifetime <= {{monetary_list_lifetime[1]}}) THEN 2
            WHEN (total_package_cbm_lifetime > {{monetary_list_lifetime[1]}} AND total_package_cbm_lifetime <= {{monetary_list_lifetime[2]}}) THEN 3
            WHEN (total_package_cbm_lifetime > {{monetary_list_lifetime[2]}} AND total_package_cbm_lifetime <= {{monetary_list_lifetime[3]}}) THEN 4
            WHEN total_package_cbm_lifetime > {{monetary_list_lifetime[3]}} THEN 5
            ELSE -999
        END AS m_score_lifetime,

        CASE
            WHEN (r_score_lifetime = 5) AND (f_score_lifetime = 5) AND (m_score_lifetime = 5) 
                THEN '1_King'

            WHEN (r_score_lifetime BETWEEN 2 AND 3) AND (f_score_lifetime = 1) AND (m_score_lifetime = 1) 
                THEN '10_At Cheap Risk'

            WHEN (r_score_lifetime = 1) AND (f_score_lifetime = 1) AND (m_score_lifetime = 1) 
                THEN '13_Cheap Lost' 

            WHEN (r_score_lifetime BETWEEN 4 AND 5) AND (f_score_lifetime BETWEEN 1 AND 2) AND (m_score_lifetime BETWEEN 4 AND 5) 
                THEN '4_Whale'  

            WHEN (r_score_lifetime BETWEEN 4 AND 5) AND (f_score_lifetime BETWEEN 4 AND 5) AND (m_score_lifetime BETWEEN 1 AND 2) 
                THEN '3_Sardine' 

            WHEN (r_score_lifetime BETWEEN 4 AND 5) AND (f_score_lifetime BETWEEN 3 AND 5) AND (m_score_lifetime BETWEEN 3 AND 5) 
                THEN '2_Loyal Customer'

            WHEN (r_score_lifetime BETWEEN 4 AND 5) AND (f_score_lifetime BETWEEN 2 AND 5) AND (m_score_lifetime BETWEEN 2 AND 5) 
                THEN '5_Potention Loyal'

            WHEN (r_score_lifetime = 5) AND (f_score_lifetime = 1) AND (m_score_lifetime BETWEEN 1 AND 2) 
                THEN '7_New Customer'

            WHEN (r_score_lifetime BETWEEN 2 AND 3) AND (f_score_lifetime BETWEEN 4 AND 5) AND (m_score_lifetime BETWEEN 4 AND 5) 
                THEN '8_At High Risk'

            WHEN (r_score_lifetime BETWEEN 2 AND 3) AND (f_score_lifetime BETWEEN 1 AND 5) AND (m_score_lifetime BETWEEN 1 AND 5) 
                THEN '9_At Risk'  
            WHEN (r_score_lifetime BETWEEN 2 AND 3) AND (f_score_lifetime = 1) AND (m_score_lifetime BETWEEN 1 AND 2) 
                THEN '9_At Risk'
            WHEN (r_score_lifetime BETWEEN 2 AND 3) AND (f_score_lifetime BETWEEN 1 AND 2) AND (m_score_lifetime = 1) 
                THEN '9_At Risk'

            WHEN (r_score_lifetime = 1) AND (f_score_lifetime BETWEEN 4 AND 5) AND (m_score_lifetime BETWEEN 1 AND 5) 
                THEN '11_Cant Lose Them'
            WHEN (r_score_lifetime = 1) AND (f_score_lifetime BETWEEN 1 AND 5) AND (m_score_lifetime BETWEEN 4 AND 5) 
                THEN '11_Cant Lose Them'
            WHEN (r_score_lifetime = 1) AND (f_score_lifetime BETWEEN 3 AND 5) AND (m_score_lifetime BETWEEN 3 AND 5) 
                THEN '11_Cant Lose Them'

            WHEN (r_score_lifetime = 1) AND (f_score_lifetime BETWEEN 1 AND 3) AND (m_score_lifetime BETWEEN 1 AND 3) 
                THEN '12_Lost' 

            WHEN (r_score_lifetime BETWEEN 4 AND 5) AND (f_score_lifetime = 1) AND (m_score_lifetime BETWEEN 1 AND 3)
                THEN '6_Normal Customer'
            WHEN (r_score_lifetime BETWEEN 4 AND 5) AND (f_score_lifetime BETWEEN 1 AND 3) AND (m_score_lifetime = 1)
                THEN '6_Normal Customer'

            ELSE 'ERROR Please Contact DATA Team'
        END AS segment_lifetime,

        CASE
            WHEN day_after_last_packing_list_one_year IS NULL THEN NULL
            WHEN day_after_last_packing_list_one_year <= {{recency_list_one_year[0]}} THEN 5
            WHEN (day_after_last_packing_list_one_year > {{recency_list_one_year[0]}} AND day_after_last_packing_list_one_year <= {{recency_list_one_year[1]}}) THEN 4
            WHEN (day_after_last_packing_list_one_year > {{recency_list_one_year[1]}} AND day_after_last_packing_list_one_year <= {{recency_list_one_year[2]}}) THEN 3
            WHEN (day_after_last_packing_list_one_year > {{recency_list_one_year[2]}} AND day_after_last_packing_list_one_year <= {{recency_list_one_year[3]}}) THEN 2
            WHEN day_after_last_packing_list_one_year > {{recency_list_one_year[3]}} THEN 1
            ELSE -999
        END AS r_score_one_year,

        CASE
            WHEN number_of_packing_list_one_year IS NULL THEN NULL
            WHEN number_of_packing_list_one_year <= {{frequency_list_one_year[0]}} THEN 1
            WHEN (number_of_packing_list_one_year > {{frequency_list_one_year[0]}} AND number_of_packing_list_one_year <= {{frequency_list_one_year[1]}}) THEN 2
            WHEN (number_of_packing_list_one_year > {{frequency_list_one_year[1]}} AND number_of_packing_list_one_year <= {{frequency_list_one_year[2]}}) THEN 3
            WHEN (number_of_packing_list_one_year > {{frequency_list_one_year[2]}} AND number_of_packing_list_one_year <= {{frequency_list_one_year[3]}}) THEN 4
            WHEN number_of_packing_list_one_year > {{frequency_list_one_year[3]}} THEN 5
            ELSE -999
        END AS f_score_one_year,

        CASE
            WHEN total_package_cbm_one_year IS NULL THEN NULL
            WHEN total_package_cbm_one_year <= {{monetary_list_one_year[0]}} THEN 1
            WHEN (total_package_cbm_one_year > {{monetary_list_one_year[0]}} AND total_package_cbm_one_year <= {{monetary_list_one_year[1]}}) THEN 2
            WHEN (total_package_cbm_one_year > {{monetary_list_one_year[1]}} AND total_package_cbm_one_year <= {{monetary_list_one_year[2]}}) THEN 3
            WHEN (total_package_cbm_one_year > {{monetary_list_one_year[2]}} AND total_package_cbm_one_year <= {{monetary_list_one_year[3]}}) THEN 4
            WHEN total_package_cbm_one_year > {{monetary_list_one_year[3]}} THEN 5
            ELSE -999
        END AS m_score_one_year,

        CASE
            WHEN (r_score_one_year IS NULL) AND (f_score_one_year IS NULL) AND (m_score_one_year IS NULL) 
                THEN '14_Not Active Between 1 year'

            WHEN (r_score_one_year = 5) AND (f_score_one_year = 5) AND (m_score_one_year = 5) 
                THEN '1_King'

            WHEN (r_score_one_year BETWEEN 2 AND 3) AND (f_score_one_year = 1) AND (m_score_one_year = 1) 
                THEN '10_At Cheap Risk'

            WHEN (r_score_one_year = 1) AND (f_score_one_year = 1) AND (m_score_one_year = 1) 
                THEN '13_Cheap Lost' 

            WHEN (r_score_one_year BETWEEN 4 AND 5) AND (f_score_one_year BETWEEN 1 AND 2) AND (m_score_one_year BETWEEN 4 AND 5) 
                THEN '4_Whale'  

            WHEN (r_score_one_year BETWEEN 4 AND 5) AND (f_score_one_year BETWEEN 4 AND 5) AND (m_score_one_year BETWEEN 1 AND 2) 
                THEN '3_Sardine' 

            WHEN (r_score_one_year BETWEEN 4 AND 5) AND (f_score_one_year BETWEEN 3 AND 5) AND (m_score_one_year BETWEEN 3 AND 5) 
                THEN '2_Loyal Customer'

            WHEN (r_score_one_year BETWEEN 4 AND 5) AND (f_score_one_year BETWEEN 2 AND 5) AND (m_score_one_year BETWEEN 2 AND 5) 
                THEN '5_Potention Loyal'

            WHEN (r_score_one_year = 5) AND (f_score_one_year = 1) AND (m_score_one_year BETWEEN 1 AND 2) 
                THEN '7_New Customer'

            WHEN (r_score_one_year BETWEEN 2 AND 3) AND (f_score_one_year BETWEEN 4 AND 5) AND (m_score_one_year BETWEEN 4 AND 5) 
                THEN '8_At High Risk'

            WHEN (r_score_one_year BETWEEN 2 AND 3) AND (f_score_one_year BETWEEN 1 AND 5) AND (m_score_one_year BETWEEN 1 AND 5) 
                THEN '9_At Risk'  
            WHEN (r_score_one_year BETWEEN 2 AND 3) AND (f_score_one_year = 1) AND (m_score_one_year BETWEEN 1 AND 2) 
                THEN '9_At Risk'
            WHEN (r_score_one_year BETWEEN 2 AND 3) AND (f_score_one_year BETWEEN 1 AND 2) AND (m_score_one_year = 1) 
                THEN '9_At Risk'

            WHEN (r_score_one_year = 1) AND (f_score_one_year BETWEEN 4 AND 5) AND (m_score_one_year BETWEEN 1 AND 5) 
                THEN '11_Cant Lose Them'
            WHEN (r_score_one_year = 1) AND (f_score_one_year BETWEEN 1 AND 5) AND (m_score_one_year BETWEEN 4 AND 5) 
                THEN '11_Cant Lose Them'
            WHEN (r_score_one_year = 1) AND (f_score_one_year BETWEEN 3 AND 5) AND (m_score_one_year BETWEEN 3 AND 5) 
                THEN '11_Cant Lose Them'

            WHEN (r_score_one_year = 1) AND (f_score_one_year BETWEEN 1 AND 3) AND (m_score_one_year BETWEEN 1 AND 3) 
                THEN '12_Lost' 

            WHEN (r_score_one_year BETWEEN 4 AND 5) AND (f_score_one_year = 1) AND (m_score_one_year BETWEEN 1 AND 3)
                THEN '6_Normal Customer'
            WHEN (r_score_one_year BETWEEN 4 AND 5) AND (f_score_one_year BETWEEN 1 AND 3) AND (m_score_one_year = 1)
                THEN '6_Normal Customer'

            ELSE 'ERROR Please Contact DATA Team'
        END AS segment_one_year,

        '{{ modules.datetime.datetime.now(modules.pytz.timezone("Asia/Kuala_Lumpur")) }}' AS _dbt_ran_datetime

    FROM company_rfm

),


-- FINAL
final__rep_shipping__rfm AS (

    SELECT
        -- ids
        sub_company_id,
        sub_company_marking_id,

        -- dimensions
        segment_lifetime,
        segment_one_year,

        -- measures
        day_after_last_packing_list_lifetime,
        number_of_packing_list_lifetime,
        total_package_cbm_lifetime,
        r_score_lifetime,
        f_score_lifetime,
        m_score_lifetime,
        day_after_last_packing_list_one_year,
        number_of_packing_list_one_year,
        total_package_cbm_one_year,
        r_score_one_year,
        f_score_one_year,
        m_score_one_year,

        -- date/times
        last_packing_list_created_datetime,

        -- metadata
        _dbt_ran_datetime

    FROM calculate_rfm

)

SELECT * FROM final__rep_shipping__rfm