By Alex Rolnik

Twitter Ads - BigQuery

Integrates with:

The Twitter Ads kit uses the associated Stats report as a base table and adds in the appropriate Entity Tables. Each kit will have the Tweet Information and associated metrics including: number of clicks, impressions, spend, video_views, conversion values, purchases, replies, retweets, follows, likes, and engagement by date.

This Kit can be used in combination with the Modular Marketing Logic Kit to create a full spectrum marketing analysis table. Find out how to do this using the directions in the Modular Marketing Logic Kit preview.

This kit includes…

Twitter Promoted Tweets Rivers

Data ingestion rivers for Promoted Tweets Entity, Tweets Entity, Ad Groups Entity, Campaigns Entity, Accounts Entity, Cards Entity, Funding Instruments Entity, Promoted Tweets Stats
Master orchestration River

This includes logic to Join Entity/Stats Tables

Output Tables:

twitter_entity_accounts
twitter_entity_cards
twitter_entity_tweets
twitter_entity_campaigns
twitter_entity_fundinginstruments
twitter_entity_adgroups
twitter_entity_promotedtweets
twitter_stats_promotedtweets
twitter_promoted_tweets_stats (entity and stats combined)

Minimum RPU Consumption: 9

You can find the full contents, data model documentation, and source fields used here.

Configuring this template for use

Variables

In this Kit, there are two variables that need to be initialized to make for dynamic use of the target configuration.

{Dataset_Twitter} is used in all Target configurations and queries as the target dataset ID.
{Twitter_Ads_Failure_Group} is used as the alert email address(es) for when a river fails (optional).
{gcs_file_zone} is used as the File Zone Bucket for all Google BigQuery Target configurations. This variable should already be populated in your Rivery account as long as a Google BigQuery connection has previously been created.

Go to the Variables menu on the left side navigation bar and create variables for Dataset_Twitter and Twitter_Ads_Failure_Group. Then fill in the values as the Google BigQuery dataset ID where you would like the data to land and the email address(es) to which you would like the failure emails sent.