Google Ads

LookML files for a schema mapping on BigQuery for google Ads compatible with Google's BigQuery Data Transfer Service for Google Ads. This is designed to work with an ETL agnostic Google Ads block.

README Contents

• Using this block
• Interface
• Block Info
• Data Structure
• Reporting Schema

To use this block, you will need to:

Include it in your manifest.lkml:

Note: This requires the Local Project Import feature currently in /admin/labs to be enabled on your Looker instance.

Via local project import:

Fork this repo and create a new project named app-marketing-google-ads-adapter

manifest.lkml

local_dependency: {
  project: "app-marketing-google-ads-adapter"
}


local_dependency: {
  project: "app-marketing-google-ads"
}

OR

Via remote project import:

For remote dependencies which don't require a local version.

manifest.lkml

remote_dependency: app-marketing-google-ads-adapter {
  url: "git://github.com/looker/app-marketing-google-ads-transfer-bigquery"
  ref: "76b9cfc1711f205dae6c6f71ea547ca7036121e7"
}

remote_dependency: app-marketing-google-ads {
  url: "git://github.com/looker/app-marketing-google-ads"
  ref: "557fa52e9fee322d9a601ee5bf009cf929ef0261"
}

Note that the ref: should point to the latest commit in each respective repo google-ads-transfer-bigquery and google-ads.

Create a google_ads_config view that is assumed by this project.

For example:

google_ads_config.view.lkml

LookML
view: google_ads_config {
  extension: required

  dimension: adwords_schema {
    hidden: yes
    sql:adwords;;
  }

  dimension: adwords_customer_id {
    hidden: yes
    sql:1234567890;;
  }
}

Include the view files in your model.

For example:

marketing_analytics.model.lkml

LookML
include: "/app-marketing-google-ads-adapter/*.view"
include: "/app-marketing-google-ads/*.view"
include: "/app-marketing-google-ads/*.dashboard"

Interface

Account Structure

ad.view:

• ad_adapter
  • external_customer_id
  • campaign_id
  • ad_group_id
  • creative_id
  • creative
  • status_active

ad_group.view:

• ad_group_adapter
  • external_customer_id
  • campaign_id
  • ad_group_id
  • ad_group_name
  • status_active

campaign.view:

• campaign_adapter
  • external_customer_id
  • campaign_id
  • campaign_name
  • status_active
  • budget_id
  • amount

customer.view:

• customer_adapter
  • external_customer_id

Targeting Criteria

geo.view

• geotargeting
  • state
  • country_code
  • name
  • postal_code

keyword.view

• keyword_adapter
  • external_customer_id
  • campaign_id
  • ad_group_id
  • criterion_id
  • criteria
  • status_active
  • bidding_strategy_type

Reports

ad_impressions.view

• _date
• ad_network_type
• device_type
• cost
• impressions
• interactions
• clicks
• conversions
• conversionvalue
• averageposition

Account Stats

• ad_impressions_adapter
• ad_impressions_hour_adapter
  • hour_of_day

Campaign Stats

• ad_impressions_campaign_adapter
• ad_impressions_campaign_hour_adapter
  • hour_of_day

Ad Group Stats

• ad_impressions_ad_group_adapter
• ad_impressions_ad_group_hour_adapter
  • hour_of_day

Keyword Stats

• ad_impressions_keyword_adapter

Ad Stats

• ad_impressions_ad_adapter

Targeting Reports

• ad_impressions * [age_range, audience, gender, geo, parental_status, video]

Block Info

This Block is modeled on the schema from Google's BigQuery Transfer Service.

The schema documentation for AdWords can be found in Google's docs.

Google AdWords Raw Data Structure

• Entity Tables and Stats Tables - There are several primary entities included in the AdWords data set, such as ad, ad group, campaign, customer, keyword, etc.. Each of these tables has a corresponding "Stats" table, which includes all the various metrics for that entity. For example, the "campaign" entity table contains attributes for each campaign, such as the campaign name and campaign status. The corresponding stats table - "Campaign Basic Stats" contains metrics such as impressions, clicks, and conversions. These stats tables are mapped to an ad_impression explore as an interface to the Looker Marketing Analytics application.

• Snapshots - AdWords tables keep records over time by snapshotting all data at the end of each day. The following day, a new snapshot is taken, and appended to the table. There are two columns on each table: _DATA_DATE and _LATEST_DATE. _DATA_DATE tells you the day the data was recorded, while _LATEST_DATE is an immutable field that tells you the most recent date a snapshot was taken. Querying the table using _DATA_DATE = _LATEST_DATE in the WHERE clause would give you only the data for the latest day.

Reporting Schema Layout