Why Use BigQuery For Paid Search Marketing
The Google Ads interface is intuitive with new feature sets in every release to streamline workflows and reporting. Yet both large and small advertisers should consider using Big Query alongside Google Ads and Search Ads 360 to supercharge insights and build automated workflows.
Use cases for Big Query
Merge internal business data with paid search
- Fiscal calendar reporting instead of calendar date
- Custom regions rather than default geographic areas
- Cost of Goods Sold tied to Shopping Ad SKUS
- CRM data tied to GCLIDs or SA360 Floodlight U values
- Call tracking tied to GCLID or SA360 Floodlight U values
Merge paid search with other cloud data sets
- Google Search Console data for understanding total organic and paid search presence
- Google Analytics Big Query export
- Google Merchant Center export: understand how changes in SKU price and out of stocks impact shopping ad performance
Leverage machine learning & automation
- Use ML Predict in Big Query to build forecasts for paid search performance using SQL.
- Use the Google Cloud Natural Language API for syntactic analysis to build tokens, topic and entity themes from search query and ad copy data to understand patterns and trends in the data.
Big Query is a server less, cloud data warehouse for running SQL queries across large data sets at significant scale and speed.
A native transfer service is built directly into Big Query for setting up a daily export from the Google Ads Reporting API into Big Query.
Steps:
1. Enable the transfer service in Google Big Query.
2. Create a data set for the transfer in Big Query
3. Get your MCC Account ID from the Google Ads Platform
4. Follow the setup instructions in the Transfer Console