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Shipping data model - rfm

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CIEF ACC1
2023-12-29 09:42:53 +00:00
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models/marts/reporting/rep_shipping__rfm.sql
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-- 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