Add conversions (#34)

* recreate seed data to depict more real story * add macro for backwards compat passthrough, update models with conversion data and passthrough macro * add conversion columns and update yml * update versions * documentation * tests * temp change deps * add additional test field in ad group seed * breaking changes * update seed data and the package deps * string config in integration test yml since thats whats in the get columns macro * cast micro dollar fields as bigint * seed data update * add conversion fields to consistency pin test * add explicit string cast for advertiser id join * update integrity tests * readme updates and realized i left out the advertiser report identifier plus comment out test configs and add models config * decisionlog * switch schema and add to changelog * new schema try * docs * docs * new schema try * update changelog * docs * docs * docs * changelog * updates to readme * Docs * bk * add note to changelog * update decision log * joe tweak * source packge ref --------- Co-authored-by: Jamie Rodriguez <65564846+fivetran-jamie@users.noreply.github.com>
fivetran · Oct 21, 2024 · 2700b8a · 2700b8a
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diff --git a/.gitignore b/.gitignore
@@ -3,4 +3,5 @@ target/
 dbt_modules/
 logs/
 .DS_Store
-dbt_packages/
+dbt_packages/
+integration_tests/package-lock.yml
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,3 +1,24 @@
+# dbt_pinterest v0.11.0
+[PR #34](https://github.com/fivetran/dbt_pinterest/pull/34) includes the following **BREAKING CHANGE** updates:
+
+## Feature Updates: Native Conversion Support
+- We have added the following conversion metrics to each `pinterest_ads` end model:
+  - `total_conversions`: The sum of all website conversion events.
+  - `total_conversions_quantity`: The total count of items or units involved in conversions.
+  - `total_conversions_value` (converted from `total_conversions_value_in_micro_dollar`) Total order value associated with conversions.
+- In the event that you were already passing the above fields in via our [passthrough columns](https://github.com/fivetran/dbt_pinterest/blob/main/README.md#passing-through-additional-metrics), the package will dynamically avoid "duplicate column" errors.
+
+> The above new field additions are **breaking changes** for users who were not already bringing in conversion fields via passthrough columns.
+
+## Documentation
+- Added more information about the difference in grains and their relationships in the [DECISIONLOG](https://github.com/fivetran/dbt_pinterest/blob/main/DECISIONLOG.md#pinterest-ads-grains).
+
+## Under the hood
+- Created `pinterest_ads_persist_pass_through_columns` macro to ensure that the new conversion fields are backwards compatible with 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 data to represent an e-commerce customer scenario.
+- Coalesces `spend` with 0 to ensure proper downstream aggregations.
+
 # dbt_pinterest v0.10.0
 [PR #30](https://github.com/fivetran/dbt_pinterest/pull/30) includes the following updates:
 

diff --git a/DECISIONLOG.md b/DECISIONLOG.md
@@ -2,4 +2,9 @@
 ## UTM Report Filtering
 This package contains a `pinterest_ads__url_report` which provides daily metrics for your utm compatible ads. It is important to note that not all Ads within Pinterest's `pin_promotion_report` source table leverage utm parameters. Therefore, this package takes an opinionated approach to filter out any records that do not contain utm parameters or leverage a url within the promoted pin.
 
-If you would like to leverage a report that contains all promoted pins and their daily metrics, we would suggest you leverage the `pinterest_ads__ad_report` which does not apply any filtering.
+If you would like to leverage a report that contains all promoted pins and their daily metrics, we would suggest you leverage the `pinterest_ads__ad_report` which does not apply any filtering.
+
+## Why don't metrics add up across different grains (Ex. ad level vs campaign level)?
+When aggregating metrics like clicks and spend across different grains, discrepancies can arise due to differences in how data is captured, grouped, or attributed at each grain. For example, certain actions or costs might be attributed differently at the ad, campaign, or ad group level, leading to inconsistencies when rolled up. Additionally, for example, at the keyword grain, where a keyword can belong to multiple ad groups, aggregations can lead to over counting. Conversely, some ads may only be represented at the ad group level, rather than individual ad levels, leading to under counting at the ad grain.
+
+This is a reason why we have broken out the ad reporting packages into separate hierarchical end models (Ad, Ad Group, Campaign, and more). Because if we only used ad-level reports, we could be missing data.
diff --git a/README.md b/README.md
@@ -31,7 +31,7 @@ The following table provides a detailed list of all tables materialized within t
 | [pinterest_ads__ad_group_report](https://fivetran.github.io/dbt_pinterest/#!/model/model.pinterest.pinterest_ads__ad_group_report)            | Each record in this table represents the daily performance of ads at the campaign, advertiser, and ad group level.|
 | [pinterest_ads__keyword_report](https://fivetran.github.io/dbt_pinterest/#!/model/model.pinterest.pinterest_ads__keyword_report)            | Each record in this table represents the daily performance of a keyword at the advertiser, campaign, ad group, and keyword level. |
 | [pinterest_ads__pin_promotion_report](https://fivetran.github.io/dbt_pinterest/#!/model/model.pinterest.pinterest_ads__pin_promotion_report)            | Each record in this table represents the daily performance of ads at the advertiser, campaign, ad group, and pin level. |
-| [pinterest_ads__url_report](https://fivetran.github.io/dbt_pinterest/#!/model/model.pinterest.pinterest_ads__url_report)            |Each record in this table represents the daily performance of ads at the advertiser, campaign, ad group, and url level. |
+| [pinterest_ads__url_report](https://fivetran.github.io/dbt_pinterest/#!/model/model.pinterest.pinterest_ads__url_report)            | Each record in this table represents the daily performance of ads at the advertiser, campaign, ad group, and url level. |
 
 <!--section-end-->
 
@@ -45,19 +45,20 @@ To use this dbt package, you must have the following:
 
 #### Databricks Dispatch Configuration
 If you are using a Databricks destination with this package you will need to add the below (or a variation of the below) dispatch configuration within your `dbt_project.yml`. This is required in order for the package to accurately search for macros within the `dbt-labs/spark_utils` then the `dbt-labs/dbt_utils` packages respectively.
+
 ```yml
 dispatch:
   - macro_namespace: dbt_utils
     search_order: ['spark_utils', 'dbt_utils']
 ```
 
-### Step 2: Install the package
-Include the following pinterest package version in your `packages.yml` file:
-> TIP: Check [dbt Hub](https://hub.getdbt.com/) for the latest installation instructions or [read the dbt docs](https://docs.getdbt.com/docs/package-management) for more information on installing packages.
-```yaml
+### Step 2: Install the package (skip if also using the `ad_reporting` combo package)
+Include the following pinterest_ads package version in your `packages.yml` file _if_ you are not also using the upstream [Ad Reporting combination package](https://github.com/fivetran/dbt_ad_reporting):
+
+```yml
 packages:
   - package: fivetran/pinterest
-    version: [">=0.10.0", "<0.11.0"] # we recommend using ranges to capture non-breaking changes automatically
+    version: [">=0.11.0", "<0.12.0"] # we recommend using ranges to capture non-breaking changes automatically
 ```
 
 Do NOT include the `pinterest_source` package in this file. The transformation package itself has a dependency on it and will install the source package as well.
@@ -71,15 +72,19 @@ vars:
     pinterest_schema: your_schema_name 
 ```
 
-#### Step 4: Disabling Keyword Models
+### Step 4: Disabling Keyword Models
 This package takes into consideration that not every Pinterest account tracks `keyword` performance, and allows you to disable the corresponding functionality by adding the following variable configuration:
+
 ```yml
 # dbt_project.yml
 vars:
     pinterest__using_keywords: False # Default = true
 ```
 
 ### (Optional) Step 5: Additional configurations
+
+<details open><summary>Expand/Collapse details</summary>
+
 #### Union multiple connectors
 If you have multiple pinterest 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 `pinterest_ads_union_schemas` OR `pinterest_ads_union_databases` variables (cannot do both) in your root `dbt_project.yml` file:
 
@@ -92,10 +97,10 @@ 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.
 
-#### Passing Through Additional 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:
+### Passing Through Additional Metrics
+By default, this package will select `clicks`, `impressions`, `spend` (converted from `spend_in_micro_dollar`), `total_conversions`, `total_conversions_quantity`, and `total_conversions_value` (converted from `total_conversions_value_in_micro_dollar`) 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 (clicks, impressions, spend, total conversions, total conversions quantity, and total conversions value) 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:
@@ -113,8 +118,9 @@ vars:
       - name: "other_id"
         alias: "another_id"
 ```
+
 #### Change the build schema
-By default, this package builds the Pinterest Ads staging models within a schema titled (`<target_schema>` + `_pinterest_source`) and your Pinterest Ads modeling models within a schema titled (`<target_schema>` + `_pinterest`) in your destination. If this is not where you would like your Pinterest Ads data to be written to, add the following configuration to your root `dbt_project.yml` file:
+By default, this package builds the Pinterest Ads staging models (10 views, 10 models) within a schema titled (`<target_schema>` + `_pinterest_source`) and your Pinterest Ads modeling models (6 tables) within a schema titled (`<target_schema>` + `_pinterest`) in your destination. If this is not where you would like your Pinterest Ads data to be written to, add the following configuration to your root `dbt_project.yml` file:
 
 ```yml
 models:
@@ -123,9 +129,9 @@ models:
     pinterest:
       +schema: my_new_schema_name # leave blank for just the target_schema
 ```
-    
+
 #### Change the source table references
-If an individual source table has a different name than the package expects, add the table name as it appears in your destination to the respective variable:
+If an individual source table has a different name than the package expects, add the table name as it appears in your destination to the respective variable. This is not available when running the package on multiple unioned connectors.
 
 > IMPORTANT: See this project's [`dbt_project.yml`](https://github.com/fivetran/dbt_pinterest/blob/main/dbt_project.yml) variable declarations to see the expected names.
 
@@ -134,8 +140,11 @@ vars:
     pinterest_<default_source_table_name>_identifier: your_table_name 
 ```
 
-### (Optional) Step 6: Orchestrate your models with Fivetran Transformations for dbt Core™
+</details>
+
+### (Optional) Step 6: Orchestrate your models with Fivetran Transformations for dbt Core™   
 <details><summary>Expand for more details</summary>
+<br>
 
 Fivetran offers the ability for you to orchestrate your dbt project through [Fivetran Transformations for dbt Core™](https://fivetran.com/docs/transformations/dbt). Learn how to set up your project for orchestration through Fivetran in our [Transformations for dbt Core setup guides](https://fivetran.com/docs/transformations/dbt#setupguide).
 
@@ -144,11 +153,11 @@ Fivetran offers the ability for you to orchestrate your dbt project through [Fiv
 ## Does this package have dependencies?
 This dbt package is dependent on the following dbt packages. These dependencies are installed by default within this package. For more information on the following packages, refer to the [dbt hub](https://hub.getdbt.com/) site.
 > IMPORTANT: If you have any of these dependent packages in your own `packages.yml` file, we highly recommend that you remove them from your root `packages.yml` to avoid package version conflicts.
-    
+
 ```yml
 packages:
     - package: fivetran/pinterest_source
-      version: [">=0.10.0", "<0.11.0"]
+      version: [">=0.11.0", "<0.12.0"]
 
     - package: fivetran/fivetran_utils
       version: [">=0.4.0", "<0.5.0"]
@@ -159,8 +168,10 @@ packages:
     - package: dbt-labs/spark_utils
       version: [">=0.3.0", "<0.4.0"]
 ```
+
 ## How is this package maintained and can I contribute?
 ### Package Maintenance
+
 The Fivetran team maintaining this package _only_ maintains the latest version of the package. We highly recommend you stay consistent with the [latest version](https://hub.getdbt.com/fivetran/pinterest/latest/) of the package and refer to the [CHANGELOG](https://github.com/fivetran/dbt_pinterest/blob/main/CHANGELOG.md) and release notes for more information on changes across versions.
 
 ### Opinionated Decisions
@@ -171,6 +182,11 @@ 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_pinterest/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_pinterest/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).
diff --git a/dbt_project.yml b/dbt_project.yml
@@ -1,5 +1,5 @@
 name: 'pinterest'
-version: '0.10.0'
+version: '0.11.0'
 config-version: 2
 require-dbt-version: [">=1.3.0", "<2.0.0"]
 models:

diff --git a/docs/catalog.json b/docs/catalog.json