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X (Twitter) Ads BigQuery

Connect X (Twitter) Ads to BigQuery

Send X (Twitter) Ads campaigns, accounts, funding instrument and 4 more report types to BigQuery on a schedule. Pick the ad accounts and filter by date. Refresh as often as every 15 minutes.

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BigQuery dataset twitter_ads
  • campaign
  • account
  • funding_instrument
  • ad_group_line_item
  • media_creative
  • 2 more report types
Each X (Twitter) Ads report type lands in its own table. You pick the dataset and table names.
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How to connect X (Twitter) Ads and BigQuery

7 steps. You can preview the X (Twitter) Ads data in Coupler.io before anything reaches BigQuery.

Step 1 of 7

Connect X (Twitter) Ads

Sign in to X (Twitter) Ads and authorize Coupler.io. There's no API key to copy.

Sign in with X (Twitter) Ads

Step 2 of 7

Choose what to export

Pick the X (Twitter) Ads data you want in BigQuery.

Ad accountsNot setSpecify Ad accounts from where you want to extract data.

Step 3 of 7

Set the report period

Choose the date range the report covers.

Start dateAny dateSpecify start date for the period you want to fetch data for.
End dateAny dateSpecify end date for the period you want to fetch data for.
Split data by periodNot setSpecify the period to split your report data.

Step 4 of 7

Pick metrics and dimensions

Choose what to measure and how to break it down.

Metric groupsNot setSelect one or more values for “metric groups”, e.g. “Billing”, “Engagement”, “Life time value mobile conversion”, “Media”, “Mobile conversion”.
DimensionNot setChoose the dimension by which your report data will be grouped. Dimensions are not supported for Media creative report type and Life time value mobile conversion metric group.
CountryNot setSpecify country for which report will be generated for selected previously dimension.
PlatformNot setSpecify platform for which report will be generated for selected previously dimension.

Step 5 of 7

Fine-tune the export

Optional settings for this X (Twitter) Ads export.

PlacementNot setSelect placement type to include in the report. For “All” option separate row will be returned for each placement type.

Step 6 of 7

Connect BigQuery

Upload the JSON key file from your Google Cloud service account, then enter the dataset and table for the X (Twitter) Ads data.

JSON key filecoupler-service-account.jsonKey file from a GCP service account
Dataset nametwitter_adsExactly as it appears in BigQuery
Table namecampaignExisting table or a new name to create
Autodetect table schemaOnOn by default. Turn off to define the schema as JSON

Step 7 of 7

Choose a write mode and schedule

Every run either replaces or appends the data in BigQuery. Run it as often as every 15 minutes.

Write mode

Each run overwrites campaign with fresh X (Twitter) Ads data.

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Get the most of X (Twitter) Ads to BigQuery integration

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Gather data

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Understand data

Preview, transform, sort, and filter data for better clarity in just a few clicks in the Coupler.io interface. Take your data analytics to the next level.
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Automate data

Access data that is always up to date by enabling the automatic data refresh on a schedule as often as every 15 minutes and using triggered automation.
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Act on data

Visualize your data by quickly connecting to data visualization and BI tools. Build insightful dashboards in a breeze and make better decisions.
X (Twitter) Ads to BigQuery questions

7 report types, including Campaign, Account, Funding instrument, Ad group (Line item) and Media creative.

You sign in to X (Twitter) Ads and authorize Coupler.io. There's no API key to copy.

Yes. Set the start date and end date to cover the period you need. Splitting the data by period is available too.

Yes. If the table doesn't exist in the dataset you choose, Coupler.io creates it on the first run and fills it with X (Twitter) Ads data.

Refresh the source field list in Coupler.io and select the new column. If you define the BigQuery table schema manually, add the column there too.

On a schedule you choose, from monthly down to every 15 minutes, depending on your Coupler.io plan.

Yes. Add more sources to the same data flow, for example Google Ads or Facebook Ads, and join or append them before the data reaches BigQuery.

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