Add conversions

.gitignore

@@ -4,4 +4,7 @@ dbt_modules/
 logs/
 package-lock.yml
 dbt_packages/
-.DS_Store
+.DS_store
+integration_tests/.DS_store
+.buildkite/.DS_store
+.github/.DS_store

CHANGELOG.md

@@ -1,3 +1,25 @@
+# dbt_microsoft_ads v0.9.0
+[PR #34](https://github.com/fivetran/dbt_microsoft_ads/pull/34) includes the following updates:
+
+## Feature Updates: Conversion Metrics
+- We have added the following source fields to each `microsoft_ads` end model:
+  - `conversions`: Number of conversions, measured by completion of an action by a customer after viewing your ad.
+  - `conversions_value`: The revenue reported by the advertiser as a result of the `conversions` figure.
+  - `all_conversions`: Number of *[all](https://learn.microsoft.com/en-us/advertising/reporting-service/conversionperformancereportcolumn?view=bingads-13#allconversions)* conversions, measured by completion of an action by a customer after viewing your ad. This field differs from `conversions` in that it includes conversions associated with a conversion goal in which the [ExcludeFromBidding](https://learn.microsoft.com/en-us/advertising/campaign-management-service/conversiongoal?view=bingads-13#excludefrombidding) Microsoft Ads property is set to `true`.
+  - `all_conversions_value` (except `microsoft_ads__account_report`): The revenue reported by the advertiser as a result of the `all_conversions` figure. This field differs from the default `conversions_value` field in that it includes revenue associated with a conversion goal in which the [ExcludeFromBidding](https://learn.microsoft.com/en-us/advertising/campaign-management-service/conversiongoal?view=bingads-13#excludefrombidding) Microsoft Ads property is set to `true`.
+> The above new field additions are **breaking changes**.
+
+## Under the Hood
+- Created `microsoft_ads_persist_pass_through_columns` macro to ensure that the new conversion fields are backwards compatible for users who have already included them via passthrough fields.
+- Added integrity and consistency validation tests within `integration_tests` folder for the transformation models (to be used by maintainers only).
+- Updated seed files with new fields to test and validate on local data, provided specific casting to numeric (for currency) and integers.
+
+## Documentation Update
+- Updated `microsoft_ads.yml` with new fields mentioned above. 
+
+## Contributors
+- [Seer Interactive](https://www.seerinteractive.com/?utm_campaign=Fivetran%20%7C%20Models&utm_source=Fivetran&utm_medium=Fivetran%20Documentation)
+
 # dbt_microsoft_ads v0.8.0
 
 [PR #32](https://github.com/fivetran/dbt_microsoft_ads/pull/32) includes the following updates:

README.md

@@ -58,7 +58,7 @@ If you are NOT using the [Ad Reporting combination package](https://github.com/f
 ```yaml
 packages:
   - package: fivetran/microsoft_ads
-    version: [">=0.8.0", "<0.9.0"]
+    version: [">=0.9.0", "<0.10.0"]
 ```
 
 ### Step 3: Define database and schema variables
@@ -71,6 +71,8 @@ vars:
 ```
 
 ### (Optional) Step 4: Additional configurations
+<details open><summary>Expand/Collapse details</summary>
+
 #### Union multiple connectors
 If you have multiple microsoft_ads connectors in Fivetran and would like to use this package on all of them simultaneously, we have provided functionality to do so. The package will union all of the data together and pass the unioned table into the transformations. You will be able to see which source it came from in the `source_relation` column of each model. To use this functionality, you will need to set either the `microsoft_ads_union_schemas` OR `microsoft_ads_union_databases` variables (cannot do both) in your root `dbt_project.yml` file:
 
@@ -83,10 +85,10 @@ vars:
 
 To connect your multiple schema/database sources to the package models, follow the steps outlined in the [Union Data Defined Sources Configuration](https://github.com/fivetran/dbt_fivetran_utils/tree/releases/v0.4.latest#union_data-source) section of the Fivetran Utils documentation for the union_data macro. This will ensure a proper configuration and correct visualization of connections in the DAG.
 
-#### Adding passthrough metrics
-By default, this package will select `clicks`, `impressions`, and `cost` from the source reporting tables to store into the staging models. If you would like to pass through additional metrics to the staging models, add the below configurations to your `dbt_project.yml` file. These variables allow for the pass-through fields to be aliased (`alias`) if desired, but not required. Use the below format for declaring the respective pass-through variables:
+### Adding passthrough metrics
+By default, this package will select `clicks`, `impressions`, `spend`, `conversions` (coalesces source `conversions` and `conversions_qualified` fields), `conversions_value` (aliased source `revenue` field), `all_conversions` (coalesces source `all_conversions` and `all_conversions_qualified` fields) and `all_conversions_value` (aliased source `all_revenue` field) from the source reporting tables to store into the staging models. If you would like to pass through additional metrics to the staging models, add the below configurations to your `dbt_project.yml` file. These variables allow for the pass-through fields to be aliased (`alias`) if desired, but not required. Use the below format for declaring the respective pass-through variables:
 
-> IMPORTANT: Make sure to exercise due diligence when adding metrics to these models. The metrics added by default (taps, impressions, and spend) have been vetted by the Fivetran team, maintaining this package for accuracy. There are metrics included within the source reports, such as metric averages, which may be inaccurately represented at the grain for reports created in this package. You must ensure that whichever metrics you pass through are appropriate to aggregate at the respective reporting levels in this package.
+> IMPORTANT: Make sure to exercise due diligence when adding metrics to these models. The metrics added by default have been vetted by the Fivetran team maintaining this package for accuracy. There are metrics included within the source reports, for example metric averages, which may be inaccurately represented at the grain for reports created in this package. You will want to ensure whichever metrics you pass through are indeed appropriate to aggregate at the respective reporting levels provided in this package.
 
 ```yml
 vars:
@@ -98,7 +100,7 @@ vars:
     microsoft_ads__ad_group_passthrough_metrics:
       - name: "unique_string_field"
         alias: "field_id"
-    microsoft_ads__ad_passthrough_metrics: 
+    microsoft_ads__ad_passthrough_metrics: #these metrics are included in both microsoft_ads__ad_report and microsoft_ads__url_report
       - name: "new_custom_field"
         alias: "custom_field"
       - name: "a_second_field"
@@ -109,15 +111,16 @@ vars:
         alias: "field_id"
 ```
 
-#### Enable UTM Auto Tagging
-This package assumes you are manually adding UTM tags to your ads. If you are leveraging the auto-tag feature within Microsoft Ads then you will want to enable the `google_auto_tagging_enabled` variable to correctly populate the UTM fields within the `microsoft_ads__utm_report` model.
+### Enable UTM Auto Tagging
+This package assumes you are manually adding UTM tags to your ads. If you are leveraging the auto-tag feature within Microsoft Ads then you will want to enable the `microsoft_ads_auto_tagging_enabled` variable to correctly populate the UTM fields within the `microsoft_ads__utm_report` model.
+
 ```yml
 vars:
     microsoft_ads_auto_tagging_enabled: true # False by default
 ```
 
 #### Change the build schema
-By default, this package builds the Microsoft Ads staging models within a schema titled (`<target_schema>` + `_microsoft_ads_source`) and your Microsoft Ads modeling models within a schema titled (`<target_schema>` + `_microsoft_ads`) in your destination. If this is not where you would like your Microsoft Ads data to be written to, add the following configuration to your root `dbt_project.yml` file:
+By default, this package builds the Microsoft Ads staging models (11 views, 11 tables) within a schema titled (`<target_schema>` + `_microsoft_ads_source`) and your Microsoft Ads modeling models (7 tables) within a schema titled (`<target_schema>` + `_microsoft_ads`) in your destination. If this is not where you would like your Microsoft Ads data to be written to, add the following configuration to your root `dbt_project.yml` file:
 
 ```yml
 models:
@@ -137,6 +140,8 @@ vars:
     microsoft_ads_<default_source_table_name>_identifier: your_table_name 
 ```
 
+</details>
+
 ### (Optional) Step 5: Orchestrate your models with Fivetran Transformations for dbt Core™
 <details><summary>Expand for more details</summary>
 
@@ -151,7 +156,7 @@ This dbt package is dependent on the following dbt packages. These dependencies
 ```yml
 packages:
     - package: fivetran/microsoft_ads_source
-      version: [">=0.9.0", "<0.10.0"]
+      version: [">=0.10.0", "<0.11.0"]
 
     - package: fivetran/fivetran_utils
       version: [">=0.4.0", "<0.5.0"]
@@ -174,6 +179,11 @@ A small team of analytics engineers at Fivetran develops these dbt packages. How
 
 We highly encourage and welcome contributions to this package. Check out [this dbt Discourse article](https://discourse.getdbt.com/t/contributing-to-a-dbt-package/657) on the best workflow for contributing to a package.
 
+#### Contributors
+We thank [everyone](https://github.com/fivetran/dbt_microsoft_ads/graphs/contributors) who has taken the time to contribute. Each PR, bug report, and feature request has made this package better and is truly appreciated.
+
+A special thank you to [Seer Interactive](https://www.seerinteractive.com/?utm_campaign=Fivetran%20%7C%20Models&utm_source=Fivetran&utm_medium=Fivetran%20Documentation), who we closely collaborated with to introduce native conversion support to our Ad packages.
+
 ## Are there any resources available?
 - If you have questions or want to reach out for help, see the [GitHub Issue](https://github.com/fivetran/dbt_microsoft_ads/issues/new/choose) section to find the right avenue of support for you.
 - If you would like to provide feedback to the dbt package team at Fivetran or would like to request a new dbt package, fill out our [Feedback Form](https://www.surveymonkey.com/r/DQ7K7WW).

dbt_project.yml

@@ -1,5 +1,5 @@
 name: 'microsoft_ads'
-version: '0.8.0'
+version: '0.9.0'
 config-version: 2
 require-dbt-version: [">=1.3.0", "<2.0.0"]
 vars:

integration_tests/ci/sample.profiles.yml

@@ -16,13 +16,13 @@ integration_tests:
       pass: "{{ env_var('CI_REDSHIFT_DBT_PASS') }}"
       dbname: "{{ env_var('CI_REDSHIFT_DBT_DBNAME') }}"
       port: 5439
-      schema: microsoft_ads_integration_tests_5
+      schema: microsoft_ads_integration_tests_6
       threads: 8
     bigquery:
       type: bigquery
       method: service-account-json
       project: 'dbt-package-testing'
-      schema: microsoft_ads_integration_tests_5
+      schema: microsoft_ads_integration_tests_6
       threads: 8
       keyfile_json: "{{ env_var('GCLOUD_SERVICE_KEY') | as_native }}"
     snowflake:
@@ -33,7 +33,7 @@ integration_tests:
       role: "{{ env_var('CI_SNOWFLAKE_DBT_ROLE') }}"
       database: "{{ env_var('CI_SNOWFLAKE_DBT_DATABASE') }}"
       warehouse: "{{ env_var('CI_SNOWFLAKE_DBT_WAREHOUSE') }}"
-      schema: microsoft_ads_integration_tests_5
+      schema: microsoft_ads_integration_tests_6
       threads: 8
     postgres:
       type: postgres
@@ -42,13 +42,13 @@ integration_tests:
       pass: "{{ env_var('CI_POSTGRES_DBT_PASS') }}"
       dbname: "{{ env_var('CI_POSTGRES_DBT_DBNAME') }}"
       port: 5432
-      schema: microsoft_ads_integration_tests_5
+      schema: microsoft_ads_integration_tests_6
       threads: 8
     databricks:
       catalog: "{{ env_var('CI_DATABRICKS_DBT_CATALOG') }}"
       host: "{{ env_var('CI_DATABRICKS_DBT_HOST') }}"
       http_path: "{{ env_var('CI_DATABRICKS_DBT_HTTP_PATH') }}"
-      schema: microsoft_ads_integration_tests_5
+      schema: microsoft_ads_integration_tests_6
       threads: 8
       token: "{{ env_var('CI_DATABRICKS_DBT_TOKEN') }}"
       type: databricks

integration_tests/dbt_project.yml

@@ -1,10 +1,10 @@
 name: 'microsoft_ads_integration_tests'
-version: '0.8.0'
+version: '0.9.0'
 profile: 'integration_tests'
 config-version: 2
 
 vars: 
-  microsoft_ads_schema: microsoft_ads_integration_tests_5
+  microsoft_ads_schema: microsoft_ads_integration_tests_6
   microsoft_ads_account_history_identifier: "microsoft_ads_account_history_data"
   microsoft_ads_account_performance_daily_report_identifier: "microsoft_ads_account_performance_daily_report_data"
   microsoft_ads_ad_group_history_identifier: "microsoft_ads_ad_group_history_data"
@@ -17,8 +17,8 @@ vars:
   microsoft_ads_keyword_performance_daily_report_identifier: "microsoft_ads_keyword_performance_daily_report_data"
   microsoft_ads_search_query_performance_daily_report_identifier: "microsoft_ads_search_performance_daily_report_data"
 
-models:
-  +schema: "microsoft_ads_{{ var('directed_schema','dev') }}"
+# models:
+#   +schema: "microsoft_ads_{{ var('directed_schema','dev') }}"
 
 seeds:
   microsoft_ads_integration_tests:
@@ -31,7 +31,15 @@ seeds:
       keyword_id: "{{ 'INT64' if target.type == 'bigquery' else 'bigint' }}"
       last_modified_time: "timestamp"
       modified_time: "timestamp"
-      spend: "float"
+      spend: "numeric"
+      impressions: "integer"
+      clicks: "integer"
+      conversions_qualified: "integer"
+      conversions: "integer"
+      revenue: "numeric"
+      all_conversions_qualified: "integer"
+      all_conversions: "integer"
+      all_revenue: "numeric"
 
 dispatch:
   - macro_namespace: dbt_utils

integration_tests/seeds/microsoft_ads_account_performance_daily_report_data.csv

@@ -1,11 +1,11 @@
-date,account_id,device_os,device_type,network,currency_code,ad_distribution,bid_match_type,delivered_match_type,top_vs_other,clicks,impressions,spend
-2019-04-25,150175881,Android,Smartphone,AOL search,USD,Search,Broad,Broad,AOL search - Top,0,0,0.0
-2019-03-15,150175881,Unknown,Computer,AOL search,USD,Search,Broad,Broad,AOL search - Top,0,0,0.0
-2019-05-11,150175881,Windows,Computer,AOL search,USD,Search,Phrase,Phrase,AOL search - Top,0,0,0.0
-2019-04-21,150175881,Android,Smartphone,AOL search,USD,Search,Broad,Broad,AOL search - Top,0,0,0.0
-2019-04-15,150175881,iOS,Tablet,AOL search,USD,Search,Broad,Broad,AOL search - Top,0,0,0.0
-2019-04-22,150175881,Unknown,Computer,AOL search,USD,Search,Broad,Broad,AOL search - Top,0,0,0.0
-2018-12-06,150175881,Unknown,Computer,AOL search,USD,Search,Phrase,Phrase,AOL search - Top,0,0,0.0
-2019-04-15,150175881,Windows,Computer,AOL search,USD,Search,Broad,Broad,AOL search - Top,0,0,0.0
-2019-04-16,150175881,Unknown,Computer,AOL search,USD,Search,Broad,Broad,AOL search - Top,0,0,0.0
-2018-12-26,150175881,Windows,Computer,AOL search,USD,Search,Broad,Phrase,AOL search - Top,0,0,0.0
+date,account_id,device_os,device_type,network,currency_code,ad_distribution,bid_match_type,delivered_match_type,top_vs_other,clicks,impressions,spend,conversions_qualified,conversions,revenue,all_conversions_qualified
+2019-04-25,150175881,Android,Smartphone,AOL search,USD,Search,Broad,Broad,AOL search - Top,0,0,0.0,0,0,0.0,0
+2019-03-15,150175881,Unknown,Computer,AOL search,USD,Search,Broad,Broad,AOL search - Top,0,0,0.0,,,,
+2019-05-11,150175881,Windows,Computer,AOL search,USD,Search,Phrase,Phrase,AOL search - Top,0,0,0.0,0,0,0.0,0
+2019-04-21,150175881,Android,Smartphone,AOL search,USD,Search,Broad,Broad,AOL search - Top,0,0,0.0,0,0,0.0,0
+2019-04-15,150175881,iOS,Tablet,AOL search,USD,Search,Broad,Broad,AOL search - Top,0,0,0.0,0,0,0.0,0
+2019-04-22,150175881,Unknown,Computer,AOL search,USD,Search,Broad,Broad,AOL search - Top,0,0,0.0,0,0,0.0,0
+2018-12-06,150175881,Unknown,Computer,AOL search,USD,Search,Phrase,Phrase,AOL search - Top,0,0,0.0,0,0,0.0,0
+2019-04-15,150175881,Windows,Computer,AOL search,USD,Search,Broad,Broad,AOL search - Top,0,0,0.0,0,0,0.0,0
+2019-04-16,150175881,Unknown,Computer,AOL search,USD,Search,Broad,Broad,AOL search - Top,0,0,0.0,0,0,0.0,0
+2018-12-26,150175881,Windows,Computer,AOL search,USD,Search,Broad,Phrase,AOL search - Top,4,5,0.0,1,2,0.1,3