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https://github.com/fivetran/dbt_facebook_ads

Fivetran data models for Facebook Ads built using dbt.
https://github.com/fivetran/dbt_facebook_ads

dbt dbt-packages facebook-ads fivetran

Last synced: 3 months ago
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Fivetran data models for Facebook Ads built using dbt.

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README 

          
# Facebook Ads Transformation dbt Package ([Docs](https://fivetran.github.io/dbt_facebook_ads/))





    

        

    

        

    

        

    

        

    

        




## What does this dbt package do?

- Produces modeled tables that leverage Facebook Ads data from [Fivetran's connector](https://fivetran.com/docs/applications/facebook-ads) in the format described by [this ERD](https://fivetran.com/docs/applications/facebook-ads#schemainformation) and builds off the output of our [Facebook Ads source package](https://github.com/fivetran/dbt_facebook_ads_source).

- Enables you to better understand the performance of your ads across varying grains:

  - Providing an account, campaign, ad group, keyword, ad, and utm level reports.

- Materializes output models designed to work simultaneously with our [multi-platform Ad Reporting package](https://github.com/fivetran/dbt_ad_reporting).

- Generates a comprehensive data dictionary of your source and modeled Facebook Ads data through the [dbt docs site](https://fivetran.github.io/dbt_facebook_ads/).



The following table provides a detailed list of all tables materialized within this package by default.

> TIP: See more details about these tables in the package's [dbt docs site](https://fivetran.github.io/dbt_facebook_ads/#!/overview?g_v=1&g_e=seeds).



| **Table**                | **Description**                                                                                                                                |

| ------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------- |

| [facebook_ads__account_report](https://fivetran.github.io/dbt_facebook_ads/#!/model/model.facebook_ads.facebook_ads__account_report)             | Each record in this table represents the daily performance at the account level. |

| [facebook_ads__campaign_report](https://fivetran.github.io/dbt_facebook_ads/#!/model/model.facebook_ads.facebook_ads__campaign_report)            | Each record in this table represents the daily performance of a campaign at the campaign/advertising_channel/advertising_channel_subtype level. |

| [facebook_ads__ad_set_report](https://fivetran.github.io/dbt_facebook_ads/#!/model/model.facebook_ads.facebook_ads__ad_set_report)            | Each record in this table represents the daily performance at the ad set level. |

| [facebook_ads__ad_report](https://fivetran.github.io/dbt_facebook_ads/#!/model/model.facebook_ads.facebook_ads__ad_report)            | Each record in this table represents the daily performance at the ad level. |

| [facebook_ads__country_report](https://fivetran.github.io/dbt_facebook_ads/#!/model/model.facebook_ads.facebook_ads__country_report)            | Each record represents the daily performance of a Facebook account at the country level. |

| [facebook_ads__region_report](https://fivetran.github.io/dbt_facebook_ads/#!/model/model.facebook_ads.facebook_ads__region_report)            | Each record represents the daily performance of a Facebook account at the region level. |

| [facebook_ads__url_report](https://fivetran.github.io/dbt_facebook_ads/#!/model/model.facebook_ads.facebook_ads__url_report)            | Each record in this table represents the daily performance of URLs at the ad level. _By default, this will exclude ads with NULL `url` values._ |

| [facebook_ads__url_tags](https://fivetran.github.io/dbt_facebook_ads/#!/model/model.facebook_ads.facebook_ads__url_tags)            | Each record in this table is a unique combination of creative_id and the corresponding key, value, and type values contained in the url_tags field. _This excludes creatives without url tags._ |



### Materialized Models

Each Quickstart transformation job run materializes 34 models if all components of this data model are enabled. This count includes all staging, intermediate, and final models materialized as `view`, `table`, or `incremental`.



## How do I use the dbt package?



### Step 1: Prerequisites

To use this dbt package, you must have the following:



- At least one Fivetran Facebook Ads connection syncing data into your destination.

- A **BigQuery**, **Snowflake**, **Redshift**, **PostgreSQL**, or **Databricks** destination.

- You will need to configure your Facebook Ads connection to pull the `basic_ad` pre-built report and its child `basic_ad_actions` and `basic_ad_action_values` pre-built reports. These pre-built reports should be enabled in your connection by default. However, to confirm these reports are actively syncing you may perform the following steps:

    1. Navigate to the connection schema tab in Fivetran.

    2. Search for `basic_ad`, `basic_ad_actions`, and `basic_ad_action_values` and confirm they are all selected/enabled. If you would like country and region-level transformations, do the same for `demographics_country`, `demographics_country_actions`, `demographics_region`, and `demographics_region_actions`.

    3. If not selected, do so and sync. If already selected you are ready to run the models!



 >**Note**: If you do not have your Facebook Ads connection [schema change settings](https://fivetran.com/docs/using-fivetran/features/data-blocking-column-hashing/config#configureschemachangesettingsforexistingconnectors) set to `Allow all`, it is very possible that you are missing `basic_ad_actions` or `basic_ad_action_values`. If you would like to surface conversion metrics in your Facebook and/or Ad Reporting models, please ensure these reports are syncing. Otherwise, the `conversions` and `conversions_value` fields will be `null`.



#### 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 (skip if also using the `ad_reporting` combo package)

Include the following facebook_ads 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.

```yml

packages:

  - package: fivetran/facebook_ads

    version: [">=0.10.0", "<0.11.0"] # we recommend using ranges to capture non-breaking changes automatically

```



Do NOT include the `facebook_ads_source` package in this file. The transformation package itself has a dependency on it and will install the source package as well.



### Step 3: Define database and schema variables

By default, this package runs using your destination and the `facebook_ads` schema. If this is not where your Facebook Ads data is (for example, if your Facebook Ads schema is named `facebook_ads_fivetran`), add the following configuration to your root `dbt_project.yml` file:



```yml

vars:

    facebook_ads_database: your_destination_name

    facebook_ads_schema: your_schema_name 

```



### (Optional) Step 4: Additional configurations

Expand/Collapse details



#### Union multiple connections

If you have multiple facebook_ads connections 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 `facebook_ads_union_schemas` OR `facebook_ads_union_databases` variables (cannot do both) in your root `dbt_project.yml` file:



```yml

vars:

    facebook_ads_union_schemas: ['facebook_ads_usa','facebook_ads_canada'] # use this if the data is in different schemas/datasets of the same database/project

    facebook_ads_union_databases: ['facebook_ads_usa','facebook_ads_canada'] # use this if the data is in different databases/projects but uses the same schema name

```

> NOTE: The native `source.yml` connection set up in the package will not function when the union schema/database feature is utilized. Although the data will be correctly combined, you will not observe the sources linked to the package models in the Directed Acyclic Graph (DAG). This happens because the package includes only one defined `source.yml`.



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.



#### Enable or Disable Country and Region Reports

This package uses the `demographics_country`, `demographics_country_actions`, `demographics_region`, and `demographics_region_actions` [pre-built](https://fivetran.com/docs/connectors/applications/facebook-ads/prebuilt-reports) reports, but takes into consideration that not every user may use these tables.



If you are running the Facebook Ads package via Fivetran Quickstart, transformations of the above tables will be dynamically enabled or disabled. Otherwise, transformations of these tables are **disabled** by default.



To enable transformations of the above geo-focused reports, add the following variable configurations to your root `dbt_project.yml` file:



```yml

vars:

  facebook_ads__using_demographics_country: True # False by default. Will enable/disable use of the `demographics_country` and `demographics_country_actions` reports

  facebook_ads__using_demographics_region: True # False by default. Will enable/disable use of the `demographics_region` and `demographics_region_actions` reports

```



#### Passing Through Additional Metrics

By default, this package will select `clicks`, `impressions`, `cost`, `conversion`, and conversion `value` (using the [default](https://fivetran.com/docs/connectors/applications/facebook-ads/custom-reports#attributionwindows) attribution window) from the source reporting tables to store into the output models. `reach` and `frequency` are also selected from `DEMOGRAPHICS_COUNTRY` and `DEMOGRAPHICS_REGION` (and passed to the `facebook_ads__country_report` and `facebook_ads__region_report` models) but not from `BASIC_AD`.



If you would like to pass through additional metrics to the output models, add the below configurations to your `dbt_project.yml` file. These variables allow for the pass-through fields to be aliased (`alias`) and transformed (`transform_sql`) if desired, but not required. Only the `name` of each metric field is required. Use the below format for declaring the respective pass-through variables:



> **Note** Please ensure you exercised due diligence when adding metrics to these models. The metrics added by default (taps, impressions, spend, and default-attribution window conversion values) 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:

    facebook_ads__basic_ad_passthrough_metrics: # add metrics found in BASIC_AD

      - name: "new_custom_field"

        alias: "custom_field_alias"

        transform_sql: "coalesce(custom_field_alias, 0)" # reference the `alias` here if you are using one (otherwise the `name`)

      - name: "another_one"

        transform_sql: "coalesce(another_one, 0)"

      - name: "cpc"

    facebook_ads__basic_ad_actions_passthrough_metrics: # add conversion metrics found in BASIC_AD_ACTIONS

      - name: "_7_d_click"

        alias: "conversion_value_7d_click"

      - name: "_1_d_view"

    facebook_ads__basic_ad_action_values_passthrough_metrics: # add conversion metrics found in BASIC_AD_ACTION_VALUES

      - name: "_7_d_click"

        alias: "conversion_value_7d_click"

      - name: "_1_d_view"

    facebook_ads__demographics_country_passthrough_metrics: # Add metrics from DEMOGRAPHICS_COUNTRY

      - name: "inline_link_clicks"

    facebook_ads__demographics_country_actions_passthrough_metrics: # Add conversion metrics from DEMOGRAPHICS_COUNTRY_ACTIONS

      - name: "inline"

    facebook_ads__demographics_region_passthrough_metrics: # Add metrics from DEMOGRAPHICS_REGION

      - name: "cost_per_inline_link_click"

    facebook_ads__demographics_region_actions_passthrough_metrics: # Add conversion metrics from DEMOGRAPHICS_REGION_ACTIONS

      - name: "inline"

```



### Configuring Conversion Action Types

By default, this package considers the following kinds of custom, purchase, and lead `action_types` to be conversions from the `basic_ad_actions`, `basic_ad_action_values`, `demographics_country_actions`, and `demographics_region_actions` source reports:



| Action Type    | Action Description ([Meta docs](https://developers.facebook.com/docs/marketing-api/reference/ads-action-stats/)) |

| -------- | ------- |

| `offsite_conversion.fb_pixel_custom`  |  Custom pixel events defined by the advertiser. This will group together individual `offsite_conversion.custom%` custom conversion events.  |

| `offsite_conversion.fb_pixel_lead`  | The number of "lead" events tracked by the pixel or Conversions API on your website and attributed to your ads. Off-Facebook leads, in short.  |

| `onsite_conversion.lead_grouped`  | The number of leads submitted on Meta technologies (including forms and Messenger) and attributed to your ads. On-Facebook leads, in short.   |

| `offsite_conversion.fb_pixel_purchase`  | The number of "purchase" events tracked by the pixel or Conversions API on your website and attributed to your ads. Off-Facebook purchases, in short.   |

| `onsite_conversion.purchase`  | The number of purchases made within Meta technologies (such as Pages or Messenger) and attributed to your ads. On-Facebook purchases, in short.   |



These metrics will be summed together into `conversions` and `conversions_value` fields in each `*_report` end model.



However, you may choose your own `action_types` to consider as conversions. To do so, provide each action type to the below `facebook_ads__conversion_action_types` variable. For each action type, provide either an exact `name` **OR** a consistent `pattern` of naming convention. You may also provide an optional `where_sql` argument for each action type, in case you would like to dynamically choose conversion actions based on other columns (ie `source_relation` if you are running the package on multiple advertisers' datasets).



```yml

# dbt_project.yml

vars:

  facebook_ads__conversion_action_types: # case-insensitive

    - name: exact_conversion_action_type_name # will grab `*_actions` and `*_action_values` records where action_type = 'exact_conversion_action_type_name'

    - pattern: onsite_conversion% # will grab all `onsite_conversion%` records

    - name: offsite_conversion.custom.my_custom_conversion_123

    - name: very_specific_conversion_action

      where_sql: source_relation = 'specific advertiser source' # will grab `*_actions` and `*_action_values` records where (action_type = very_specific_conversion_action and {{ where_sql }})

    - pattern: subscribe%

      where_sql: source_relation = 'advertiser who only cares about subscriptions' # will grab `*_actions` and `*_action_values` records where (action_type like 'subscribe%' and {{ where_sql }})

```



> **Note**: Please ensure to exercise due diligence when adding or removing conversion action types. The action types added by default have been heavily vetted by our friends at [Seer Interactive](https://www.seerinteractive.com/) and the Fivetran team maintaining this package for accuracy. There are many ways to accidentally double-count conversion values, as some action types are hierarchical/aggregates or overlap with others. Reference the action type descriptions in the Meta [API docs](https://developers.facebook.com/docs/marketing-api/reference/ads-action-stats/) to ensure you select action types that appropriately and accurately fit your use case.



#### Change the build schema



By default, this package builds the Facebook Ads staging models (8 views, 8 tables) within a schema titled (`` + `_facebook_ads_source`) and your Facebook Ads modeling models (6 tables, 2 intermediate views) within a schema titled (`` + `_facebook_ads`) in your destination. If this is not where you would like your Facebook Ads data to be written to, add the following configuration to your root `dbt_project.yml` file:



```yml

models:

    facebook_ads_source:

      +schema: my_new_schema_name # leave blank for just the target_schema

    facebook_ads:

      +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. This is not available when running the package on multiple unioned connections.



> IMPORTANT: See this project's [`dbt_project.yml`](https://github.com/fivetran/dbt_facebook_ads/blob/main/dbt_project.yml) variable declarations to see the expected names.



```yml

vars:

    facebook_ads__identifier: your_table_name 

```



### (Optional) Step 5: Orchestrate your models with Fivetran Transformations for dbt Core™

Expand for more details



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).



## 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/facebook_ads_source

      version: [">=0.10.0", "<0.11.0"]



    - package: fivetran/fivetran_utils

      version: [">=0.4.0", "<0.5.0"]



    - package: dbt-labs/dbt_utils

      version: [">=1.0.0", "<2.0.0"]



    - 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/facebook_ads/latest/) of the package and refer to the [CHANGELOG](https://github.com/fivetran/dbt_facebook_ads/blob/main/CHANGELOG.md), [DECISIONLOG](https://github.com/fivetran/dbt_facebook_ads/blob/main/DECISIONLOG.md) and release notes for more information on changes across versions.



### Contributions

A small team of analytics engineers at Fivetran develops these dbt packages. However, the packages are made better by community contributions.



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_facebook_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_facebook_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).