MM-42949: Creating Scripts for LTV for EMEA APAC and ROW (mattermost#…

…1124)

* Creating Scripts for LTV for EMEA APAC and ROW

Extending LTV analyses to the other regions EMEA APAC and ROW

* Update schema.yml

Adding models recently added for ltv amer, emea, apac, row

transform/snowflake-dbt/models/finance/arr_ltv_apac.sql

@@ -0,0 +1,122 @@
+{{config({
+    "materialized": "table",
+    "schema": "finance",
+    "tags":'nightly'
+  })
+}}
+
+--QUERY FOR CALCULATING LTV BASED ON CONTRIBUTION MARGIN OF 0.97 AND 
+--THIS IS THE SUBQUERY FOR COMPANY_TYPES
+with a as (
+  select
+        geo,
+        company_type,
+        cohort_yr,
+        report_mo,
+        datediff('month',cohort_yr,report_mo) as month_after,
+        sum(arr_os) as end_arr,
+        sum(active_cnt) as end_customers,
+        round(div0(end_arr,end_customers),0) as avg_arr
+  from {{ref('arr_vintages')}}
+  --from analytics.finance.arr_vintages
+  where cohort_yr > date '2017-01-31'
+    and geo = 'APAC'
+  group by 1,2,3,4,5
+  order by 1,2,3,4
+)
+--THIS IS THE SUBQUERY FOR THE FIRST YEAR DENOMINATOR OF COMPANY_TYPES
+,b as (
+  select
+        geo,
+        company_type,
+        cohort_yr,
+        end_arr as max_arr,
+        avg_arr as start_avg_arr,
+        end_customers as max_customers
+  from a
+  where month_after = 0
+)
+--THIS IS THE SUBQUERY FOR ALL COMPANY TYPES
+,c as (
+  select
+      geo,
+      'ALL' as company_type,
+      cohort_yr,
+      report_mo,
+      datediff('month',cohort_yr,report_mo) as month_after,
+      sum(arr_os) as end_arr,
+      sum(active_cnt) as end_customers,
+      round(div0(end_arr,end_customers),0) as avg_arr
+from {{ref('arr_vintages')}}
+--from analytics.finance.arr_vintages
+where cohort_yr > date '2017-01-31'
+  and geo = 'APAC'
+group by 1,2,3,4,5
+order by 1,2,3,4,5
+)
+--THIS IS THE SUBQUERY FOR ALL COMPANY TYPES DENOMINATOR
+,d as (
+  select
+        geo,
+        company_type,
+        cohort_yr,
+        end_arr as max_arr,
+        avg_arr as start_avg_arr,
+        end_customers as max_customers
+  from c
+  where month_after = 0
+)
+
+--CONSOLIDATING REPORT
+,consol as (
+--SPECIFIC COMPANY TYPES
+select
+        a.geo,
+        a.company_type,
+        a.cohort_yr,
+        a.month_after,
+        a.end_arr,
+        round(div0(a.avg_arr,b.start_avg_arr),2) as expand_rate,
+        round(div0(a.end_arr,max_arr),2) as ndr_pcnt,
+        a.end_customers,
+        round(div0(a.end_customers,max_customers),2) as cust_retention,
+        a.avg_arr,
+        round(div0(a.end_arr,a.end_customers)*cust_retention,0) as retained_ltv_arr,
+        round(retained_ltv_arr * 0.97,0) as cmargin_ltv_cashflow,
+        sum(cmargin_ltv_cashflow) over (partition by a.geo||a.company_type||a.cohort_yr order by a.month_after) as cum_ltv
+from a
+left join b on b.cohort_yr = a.cohort_yr and b.geo = a.geo and b.company_type = a.company_type
+where month_after in (0,12,24,36,48,60,72,84)
+
+union
+--ALL COMPANY TYPES
+select
+        c.geo,
+        c.company_type,
+        c.cohort_yr,
+        c.month_after,
+        c.end_arr,
+        round(div0(c.avg_arr,d.start_avg_arr),2) as expand_rate,
+        round(div0(c.end_arr,d.max_arr),2) as ndr_pcnt,
+        c.end_customers,
+        round(div0(c.end_customers,max_customers),2) as cust_retention,
+        c.avg_arr,
+        round(div0(c.end_arr,c.end_customers)*cust_retention,2) as retained_ltv_arr,
+        round(retained_ltv_arr * 0.97,2) as cmargin_ltv_cashflow,
+        sum(cmargin_ltv_cashflow) over (partition by c.geo||c.company_type||c.cohort_yr order by c.month_after) as cum_ltv
+from c
+left join d on d.cohort_yr = c.cohort_yr and d.geo = c.geo and d.company_type = c.company_type
+where month_after in (0,12,24,36,48,60,72,84)
+)
+
+--ADDING UNIQUE KEY AND YEAR END MARKERS
+select
+        *,
+        geo||'-'||company_type||'-'||cohort_yr||'-'||month_after as unique_key,
+        dateadd('month',month_after,cohort_yr) as fiscal_qtr
+from consol
+order by geo, company_type, cohort_yr, month_after
+
+
+
+

transform/snowflake-dbt/models/finance/arr_ltv_emea.sql

@@ -0,0 +1,122 @@
+{{config({
+    "materialized": "table",
+    "schema": "finance",
+    "tags":'nightly'
+  })
+}}
+
+--QUERY FOR CALCULATING LTV BASED ON CONTRIBUTION MARGIN OF 0.97 AND 
+--THIS IS THE SUBQUERY FOR COMPANY_TYPES
+with a as (
+  select
+        geo,
+        company_type,
+        cohort_yr,
+        report_mo,
+        datediff('month',cohort_yr,report_mo) as month_after,
+        sum(arr_os) as end_arr,
+        sum(active_cnt) as end_customers,
+        round(div0(end_arr,end_customers),0) as avg_arr
+  from {{ref('arr_vintages')}}
+  --from analytics.finance.arr_vintages
+  where cohort_yr > date '2017-01-31'
+    and geo = 'EMEA'
+  group by 1,2,3,4,5
+  order by 1,2,3,4
+)
+--THIS IS THE SUBQUERY FOR THE FIRST YEAR DENOMINATOR OF COMPANY_TYPES
+,b as (
+  select
+        geo,
+        company_type,
+        cohort_yr,
+        end_arr as max_arr,
+        avg_arr as start_avg_arr,
+        end_customers as max_customers
+  from a
+  where month_after = 0
+)
+--THIS IS THE SUBQUERY FOR ALL COMPANY TYPES
+,c as (
+  select
+      geo,
+      'ALL' as company_type,
+      cohort_yr,
+      report_mo,
+      datediff('month',cohort_yr,report_mo) as month_after,
+      sum(arr_os) as end_arr,
+      sum(active_cnt) as end_customers,
+      round(div0(end_arr,end_customers),0) as avg_arr
+from {{ref('arr_vintages')}}
+--from analytics.finance.arr_vintages
+where cohort_yr > date '2017-01-31'
+  and geo = 'EMEA'
+group by 1,2,3,4,5
+order by 1,2,3,4,5
+)
+--THIS IS THE SUBQUERY FOR ALL COMPANY TYPES DENOMINATOR
+,d as (
+  select
+        geo,
+        company_type,
+        cohort_yr,
+        end_arr as max_arr,
+        avg_arr as start_avg_arr,
+        end_customers as max_customers
+  from c
+  where month_after = 0
+)
+
+--CONSOLIDATING REPORT
+,consol as (
+--SPECIFIC COMPANY TYPES
+select
+        a.geo,
+        a.company_type,
+        a.cohort_yr,
+        a.month_after,
+        a.end_arr,
+        round(div0(a.avg_arr,b.start_avg_arr),2) as expand_rate,
+        round(div0(a.end_arr,max_arr),2) as ndr_pcnt,
+        a.end_customers,
+        round(div0(a.end_customers,max_customers),2) as cust_retention,
+        a.avg_arr,
+        round(div0(a.end_arr,a.end_customers)*cust_retention,0) as retained_ltv_arr,
+        round(retained_ltv_arr * 0.97,0) as cmargin_ltv_cashflow,
+        sum(cmargin_ltv_cashflow) over (partition by a.geo||a.company_type||a.cohort_yr order by a.month_after) as cum_ltv
+from a
+left join b on b.cohort_yr = a.cohort_yr and b.geo = a.geo and b.company_type = a.company_type
+where month_after in (0,12,24,36,48,60,72,84)
+
+union
+--ALL COMPANY TYPES
+select
+        c.geo,
+        c.company_type,
+        c.cohort_yr,
+        c.month_after,
+        c.end_arr,
+        round(div0(c.avg_arr,d.start_avg_arr),2) as expand_rate,
+        round(div0(c.end_arr,d.max_arr),2) as ndr_pcnt,
+        c.end_customers,
+        round(div0(c.end_customers,max_customers),2) as cust_retention,
+        c.avg_arr,
+        round(div0(c.end_arr,c.end_customers)*cust_retention,2) as retained_ltv_arr,
+        round(retained_ltv_arr * 0.97,2) as cmargin_ltv_cashflow,
+        sum(cmargin_ltv_cashflow) over (partition by c.geo||c.company_type||c.cohort_yr order by c.month_after) as cum_ltv
+from c
+left join d on d.cohort_yr = c.cohort_yr and d.geo = c.geo and d.company_type = c.company_type
+where month_after in (0,12,24,36,48,60,72,84)
+)
+
+--ADDING UNIQUE KEY AND YEAR END MARKERS
+select
+        *,
+        geo||'-'||company_type||'-'||cohort_yr||'-'||month_after as unique_key,
+        dateadd('month',month_after,cohort_yr) as fiscal_qtr
+from consol
+order by geo, company_type, cohort_yr, month_after
+
+
+
+

transform/snowflake-dbt/models/finance/arr_ltv_row.sql

@@ -0,0 +1,122 @@
+{{config({
+    "materialized": "table",
+    "schema": "finance",
+    "tags":'nightly'
+  })
+}}
+
+--QUERY FOR CALCULATING LTV BASED ON CONTRIBUTION MARGIN OF 0.97 AND 
+--THIS IS THE SUBQUERY FOR COMPANY_TYPES
+with a as (
+  select
+        geo,
+        company_type,
+        cohort_yr,
+        report_mo,
+        datediff('month',cohort_yr,report_mo) as month_after,
+        sum(arr_os) as end_arr,
+        sum(active_cnt) as end_customers,
+        round(div0(end_arr,end_customers),0) as avg_arr
+  from {{ref('arr_vintages')}}
+  --from analytics.finance.arr_vintages
+  where cohort_yr > date '2017-01-31'
+    and geo = 'ROW'
+  group by 1,2,3,4,5
+  order by 1,2,3,4
+)
+--THIS IS THE SUBQUERY FOR THE FIRST YEAR DENOMINATOR OF COMPANY_TYPES
+,b as (
+  select
+        geo,
+        company_type,
+        cohort_yr,
+        end_arr as max_arr,
+        avg_arr as start_avg_arr,
+        end_customers as max_customers
+  from a
+  where month_after = 0
+)
+--THIS IS THE SUBQUERY FOR ALL COMPANY TYPES
+,c as (
+  select
+      geo,
+      'ALL' as company_type,
+      cohort_yr,
+      report_mo,
+      datediff('month',cohort_yr,report_mo) as month_after,
+      sum(arr_os) as end_arr,
+      sum(active_cnt) as end_customers,
+      round(div0(end_arr,end_customers),0) as avg_arr
+from {{ref('arr_vintages')}}
+--from analytics.finance.arr_vintages
+where cohort_yr > date '2017-01-31'
+  and geo = 'ROW'
+group by 1,2,3,4,5
+order by 1,2,3,4,5
+)
+--THIS IS THE SUBQUERY FOR ALL COMPANY TYPES DENOMINATOR
+,d as (
+  select
+        geo,
+        company_type,
+        cohort_yr,
+        end_arr as max_arr,
+        avg_arr as start_avg_arr,
+        end_customers as max_customers
+  from c
+  where month_after = 0
+)
+
+--CONSOLIDATING REPORT
+,consol as (
+--SPECIFIC COMPANY TYPES
+select
+        a.geo,
+        a.company_type,
+        a.cohort_yr,
+        a.month_after,
+        a.end_arr,
+        round(div0(a.avg_arr,b.start_avg_arr),2) as expand_rate,
+        round(div0(a.end_arr,max_arr),2) as ndr_pcnt,
+        a.end_customers,
+        round(div0(a.end_customers,max_customers),2) as cust_retention,
+        a.avg_arr,
+        round(div0(a.end_arr,a.end_customers)*cust_retention,0) as retained_ltv_arr,
+        round(retained_ltv_arr * 0.97,0) as cmargin_ltv_cashflow,
+        sum(cmargin_ltv_cashflow) over (partition by a.geo||a.company_type||a.cohort_yr order by a.month_after) as cum_ltv
+from a
+left join b on b.cohort_yr = a.cohort_yr and b.geo = a.geo and b.company_type = a.company_type
+where month_after in (0,12,24,36,48,60,72,84)
+
+union
+--ALL COMPANY TYPES
+select
+        c.geo,
+        c.company_type,
+        c.cohort_yr,
+        c.month_after,
+        c.end_arr,
+        round(div0(c.avg_arr,d.start_avg_arr),2) as expand_rate,
+        round(div0(c.end_arr,d.max_arr),2) as ndr_pcnt,
+        c.end_customers,
+        round(div0(c.end_customers,max_customers),2) as cust_retention,
+        c.avg_arr,
+        round(div0(c.end_arr,c.end_customers)*cust_retention,2) as retained_ltv_arr,
+        round(retained_ltv_arr * 0.97,2) as cmargin_ltv_cashflow,
+        sum(cmargin_ltv_cashflow) over (partition by c.geo||c.company_type||c.cohort_yr order by c.month_after) as cum_ltv
+from c
+left join d on d.cohort_yr = c.cohort_yr and d.geo = c.geo and d.company_type = c.company_type
+where month_after in (0,12,24,36,48,60,72,84)
+)
+
+--ADDING UNIQUE KEY AND YEAR END MARKERS
+select
+        *,
+        geo||'-'||company_type||'-'||cohort_yr||'-'||month_after as unique_key,
+        dateadd('month',month_after,cohort_yr) as fiscal_qtr
+from consol
+order by geo, company_type, cohort_yr, month_after
+
+
+
+

transform/snowflake-dbt/models/finance/schema.yml

@@ -53,5 +53,30 @@ models:
       - name: unique_key
         tests:
           - not_null
+  - name: arr_ltv_amer
+    description: For Americas grouping of arr_vintages into shape friendly for ltv calculations
+    columns:
+      - name: unique_key
+        tests:
+          - not_null
+  - name: arr_ltv_emea
+    description: For EMEA grouping of arr_vintages into shape friendly for ltv calculations
+    columns:
+      - name: unique_key
+        tests:
+          - not_null
+  - name: arr_ltv_apac
+    description: For APAC grouping of arr_vintages into shape friendly for ltv calculations
+    columns:
+      - name: unique_key
+        tests:
+          - not_null
+  - name: arr_ltv_row
+    description: For ROW grouping of arr_vintages into shape friendly for ltv calculations
+    columns:
+      - name: unique_key
+        tests:
+          - not_null
+