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‎COHORT ANALYSIS REPORT.sql‎

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-- Project Name :- Analyzing Customer Retention and Lifetime Value Through Cohort Analysis
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-- DEVIKA AGARWAL
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/*
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The goal of this project is to perform cohort analysis to understand and
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improve customer retention on Gameflix using SQL. Here's how we can approach it:
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1. Data Preparation
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2. Creating Customer Cohorts & Analyzing Customer Retention
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3. Customer Lifetime Value (CLTV)
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*/
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-- 1. Data Preparation
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-- step (1) - Checking for data quality and consistency.
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-- Checking for missing values in the ORDER table
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SELECT
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SUM(CASE WHEN o."ORDER_ID" IS NULL THEN 1 ELSE 0 END) AS missing_order_id,
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SUM(CASE WHEN o."USER_ID" IS NULL THEN 1 ELSE 0 END) AS missing_user_id,
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SUM(CASE WHEN o."PROMO_ID" IS NULL THEN 1 ELSE 0 END) AS missing_promo_id,
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SUM(CASE WHEN o."ORDER_DATE" IS NULL THEN 1 ELSE 0 END) AS missing_order_date,
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SUM(CASE WHEN o."ORDER_SEQ" IS NULL THEN 1 ELSE 0 END) AS missing_order_seq,
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SUM(CASE WHEN o."REDEMPTION_DATE" IS NULL THEN 1 ELSE 0 END) AS missing_redemption_date,
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SUM(CASE WHEN o."REDEMPTION_DATE" IS NULL THEN 1 ELSE 0 END) AS missing_validity_till_date,
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SUM(CASE WHEN o."ORDER_STAUS" IS NULL THEN 1 ELSE 0 END) AS missing_order_status
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FROM "ORDER" o
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-- zero missing values in the orders table
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-- Checking for missing values in the promotional_plan table
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SELECT
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SUM(CASE WHEN pp."PROMO_ID" IS NULL THEN 1 ELSE 0 END) AS missing_promo_id,
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SUM(CASE WHEN pp."PROMO_PLAN" IS NULL THEN 1 ELSE 0 END) AS missing_promo_plan,
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SUM(CASE WHEN pp."PROMO_OFFER_TYPE" IS NULL THEN 1 ELSE 0 END) AS missing_promo_offer_type,
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SUM(CASE WHEN pp."SUBSCRIPTION_TYPE" IS NULL THEN 1 ELSE 0 END) AS missing_subscription_type,
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SUM(CASE WHEN pp."BASE PRICE" IS NULL THEN 1 ELSE 0 END) AS missing_base_price,
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SUM(CASE WHEN pp."DISCOUNT_PERCENTAGE" IS NULL THEN 1 ELSE 0 END) AS missing_discount_percentage,
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SUM(CASE WHEN pp."EFFECTIVE_PRICE" IS NULL THEN 1 ELSE 0 END) AS missing_effective_price
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FROM promotional_plan pp ;
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-- zero missing values in the promotion_plan table
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-- Checking for missing values in the user_registration table
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SELECT
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SUM(CASE WHEN ur."User Id" IS NULL THEN 1 ELSE 0 END) AS missing_user_id,
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SUM(CASE WHEN ur."Full Name" IS NULL THEN 1 ELSE 0 END) AS missing_full_name,
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SUM(CASE WHEN ur."Age" IS NULL THEN 1 ELSE 0 END) AS missing_age,
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SUM(CASE WHEN ur."Gender" IS NULL THEN 1 ELSE 0 END) AS missing_gender,
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SUM(CASE WHEN ur."Country" IS NULL THEN 1 ELSE 0 END) AS missing_country,
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SUM(CASE WHEN ur."City" IS NULL THEN 1 ELSE 0 END) AS missing_city
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FROM user_registration ur ;
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-- zero missing values in the user_registration table
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-- Checking for duplicate order_id in the ORDER table
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SELECT
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o."ORDER_ID" ,
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COUNT(*) AS count
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FROM "ORDER" o
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GROUP BY o."ORDER_ID"
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HAVING COUNT(*) > 1;
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-- zero duplicate values in order table
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-- Checking for duplicate promo_id in the promotional_plan table
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SELECT
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pp."PROMO_ID" ,
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COUNT(*) AS count
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FROM promotional_plan pp
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GROUP BY pp."PROMO_ID"
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HAVING COUNT(*) > 1;
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--zero duplicate values in promotional_plan table
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-- Checking for duplicate user_id in the USER_REGISTRATION table
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SELECT
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ur."User Id" ,
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COUNT(*) AS count
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FROM user_registration ur
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GROUP BY ur."User Id"
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HAVING COUNT(*) > 1;
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-- zero duplicate values
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-- Checking for promo_id in the ORDER table that do not exist in the promotional_plan table
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SELECT DISTINCT o."PROMO_ID"
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FROM "ORDER" o
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WHERE o."PROMO_ID" NOT IN (SELECT pp."PROMO_ID" FROM promotional_plan pp);
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--All promo id present in the order is exist in promotional_plan table
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-- Checking for user_id in the ORDER table that do not exist in the USER_REGISTRATION table
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SELECT DISTINCT o."USER_ID"
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FROM "ORDER" o
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WHERE o."USER_ID" NOT IN (SELECT User Id FROM user_registration ur);
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-- user id are missing in the orders table
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-- we can adjust by excluding records with missing user_id to ensure data consistency.
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-- step (2) - Extracting Required Fields
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ALTER TABLE "ORDER" ADD COLUMN active_month DATE;
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UPDATE "ORDER" o
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SET active_month = DATE_TRUNC('month', o."ORDER_DATE"::timestamp);
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ALTER TABLE "ORDER" ADD COLUMN promo_activation_month DATE;
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UPDATE "ORDER" o
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SET promo_activation_month = DATE_TRUNC('month', TO_TIMESTAMP(o."REDEMPTION_DATE", 'DD-MM-YYYY'));
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ALTER TABLE "ORDER" ADD COLUMN promo_ending_month DATE;
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UPDATE "ORDER" o
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SET promo_ending_month = DATE_TRUNC('month', o."VALIDITY_TILL_DATE"::DATE);
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-- 2. Creating Customer Cohorts & Analyzing Customer Retention
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-- Creating cohorts based on the month of first subscription
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WITH user_cohorts AS (
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SELECT
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o."USER_ID",
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DATE_TRUNC('month', MIN(TO_DATE(o."ORDER_DATE", 'DD-MM-YYYY'))) AS cohort_month
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FROM "ORDER" o
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GROUP BY o."USER_ID"
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)
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-- Calculating the number of users retained in each subsequent month
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, cohort_retention AS (
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SELECT
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uc.cohort_month,
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DATE_TRUNC('month', TO_DATE(o2."ORDER_DATE", 'DD-MM-YYYY')) AS active_month,
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COUNT(DISTINCT o2."USER_ID") AS retained_users
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FROM user_cohorts uc
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JOIN "ORDER" o2 ON uc."USER_ID" = o2."USER_ID"
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GROUP BY uc.cohort_month, DATE_TRUNC('month', TO_DATE(o2."ORDER_DATE", 'DD-MM-YYYY'))
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ORDER BY uc.cohort_month, active_month
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)
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-- Calculating retention rates
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SELECT
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TO_CHAR(cr.cohort_month, 'YYYY-MM') AS cohort_month,
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TO_CHAR(cr.active_month, 'YYYY-MM') AS active_month,
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cr.retained_users,
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(cr.retained_users * 1.0 / cohort_size.cohort_count) AS retention_rate
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FROM cohort_retention cr
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JOIN (
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SELECT
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cohort_month,
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COUNT("USER_ID") AS cohort_count
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FROM user_cohorts
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GROUP BY cohort_month
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) AS cohort_size ON cr.cohort_month = cohort_size.cohort_month
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ORDER BY cr.cohort_month, cr.active_month;
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-- 3. Customer Lifetime Value (CLTV)
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-- step (1) - Calculating Total Revenue Generated by Each Cohort
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-- Calculating monthly revenue generated by each cohort over its lifetime
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WITH user_cohorts AS (
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SELECT
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o."USER_ID",
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DATE_TRUNC('month', MIN(o."ORDER_DATE"::DATE)) AS cohort_month
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FROM "ORDER" o
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GROUP BY o."USER_ID"
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),
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-- Calculating total cohort revenue and average revenue per customer
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cohort_revenue AS (
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SELECT
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uc.cohort_month,
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DATE_TRUNC('month', o."ORDER_DATE"::DATE) AS revenue_month,
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SUM(pp."EFFECTIVE_PRICE") AS monthly_revenue
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FROM user_cohorts uc
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JOIN "ORDER" o ON uc."USER_ID" = o."USER_ID"
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JOIN promotional_plan pp ON o."PROMO_ID" = pp."PROMO_ID"
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GROUP BY uc.cohort_month, DATE_TRUNC('month', o."ORDER_DATE"::DATE)
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)
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-- Calculating total cohort revenue and average revenue per customer
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SELECT
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cr.cohort_month,
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SUM(cr.monthly_revenue) AS total_cohort_revenue,
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(SUM(cr.monthly_revenue) * 1.0 / cohort_size.cohort_count) AS avg_revenue_per_customer
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FROM cohort_revenue cr
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JOIN (
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SELECT
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cohort_month,
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COUNT("USER_ID") AS cohort_count
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FROM user_cohorts
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GROUP BY cohort_month
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) AS cohort_size ON cr.cohort_month = cohort_size.cohort_month
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GROUP BY cr.cohort_month, cohort_size.cohort_count
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ORDER BY cr.cohort_month;
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-- step (3) - Calculating Gross Margin
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-- Step 1: Defining User Cohorts based on the month of first subscription
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WITH user_cohorts AS (
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SELECT
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o."USER_ID",
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DATE_TRUNC('month', MIN(o."ORDER_DATE"::DATE)) AS cohort_month
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FROM "ORDER" o
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GROUP BY o."USER_ID"
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),
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-- Step 2: Calculating monthly revenue for each cohort
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cohort_revenue AS (
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SELECT
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uc.cohort_month,
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DATE_TRUNC('month', o."ORDER_DATE"::DATE) AS revenue_month,
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SUM(pp."EFFECTIVE_PRICE") AS monthly_revenue
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FROM user_cohorts uc
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JOIN "ORDER" o ON uc."USER_ID" = o."USER_ID"
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JOIN promotional_plan pp ON o."PROMO_ID" = pp."PROMO_ID"
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GROUP BY uc.cohort_month, DATE_TRUNC('month', o."ORDER_DATE"::DATE)
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),
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-- Step 3: Aggregating cohort revenue and calculating average revenue per customer
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cohort_revenue_analysis AS (
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SELECT
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cr.cohort_month,
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SUM(cr.monthly_revenue) AS total_cohort_revenue,
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(SUM(cr.monthly_revenue) * 1.0 / cohort_size.cohort_count) AS avg_revenue_per_customer
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FROM cohort_revenue cr
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JOIN (
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SELECT
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cohort_month,
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COUNT("USER_ID") AS cohort_count
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FROM user_cohorts
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GROUP BY cohort_month
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) AS cohort_size ON cr.cohort_month = cohort_size.cohort_month
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GROUP BY cr.cohort_month, cohort_size.cohort_count
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)
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-- Step 4: Calculating CLTV with gross margin
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SELECT
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TO_CHAR(cohort_month, 'YYYY-MM') AS cohort_month,
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total_cohort_revenue,
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avg_revenue_per_customer,
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(total_cohort_revenue * 0.65) AS cltv_with_gross_margin -- Calculating CLTV with gross margin
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FROM cohort_revenue_analysis
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ORDER BY cohort_month;

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