Google Ads to QuickSight

This page provides you with instructions on how to extract data from Google Ads and analyze it in Amazon QuickSight. (If the mechanics of extracting data from Google Ads seem too complex or difficult to maintain, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)

What is Google Ads?

Google Ads (formerly AdWords) is a popular paid marketing tool. With Google Ads, you set a budget, select keywords, and publish ads that appear on Google search results pages relevant to your keywords. Google Ads collects data about campaigns that businesses can use to measure their effectiveness.

What is QuickSight?

Amazon QuickSight is the AWS business intelligence tool for creating dashboards and visualizations. Users are charged per session only for the time when they access dashboards or reports. QuickSight supports a variety of data sources, such as individual databases (Amazon Aurora, MariaDB, and Microsoft SQL Server), data warehouses (Amazon Redshift and Snowflake), and SaaS sources (Adobe Analytics, GitHub, and Salesforce), along with several common standard file formats.

Getting data out of Google Ads

Google provides a SOAP API for Google Ads. The first step of getting your data into your data warehouse is pulling the data off of Google's servers by using the AdWords API's Reporting features. This is a subset of the API's functionality, which also includes the ability to manage ads.

You can also link your Google Analytics and Google Ads accounts to allow the data to cross-pollinate. This can provide richer reporting due to the breadth of knowledge that exists in Google Analytics about the people who may have viewed or clicked your ads.

You can extract granular data from AdWords API reports, allowing you to see things like impressions, clickthrough rates, and CPC broken out by time period.

Loading data into QuickSight

You must replicate data from your SaaS applications to a data warehouse (such as Redshift) before you can report on it using QuickSight. Once you specify a data source you want to connect to, you must specify a host name and port, database name, and username and password to get access to the data. You then choose the schema you want to work with, and a table within that schema. You can add additional tables by specifying them as new datasets from the main QuickSight page.

Using data in QuickSight

QuickSights provides both a visual report builder and the ability to use SQL to select, join, and sort data. QuickSight lets you combine visualizations into dashboards that you can share with others, and automatically generate and send reports via email.

Keeping Google Ads data up to date

So, now what? You've built a script that pulls data from Google Ads and loads it into your data warehouse, but what happens tomorrow when you have thousands of new impressions?

The key is to build your script in such a way that it can also identify incremental updates to your data. If you can identify some fields that auto-increment, you could use them to give your script the ability to recognize new data. You can then set your script up as a cron job or continuous loop to keep pulling down new data as it appears.

From Google Ads to your data warehouse: An easier solution

As mentioned earlier, the best practice for analyzing Google Ads data in Amazon QuickSight is to store that data inside a data warehousing platform alongside data from your other databases and third-party sources. You can find instructions for doing these extractions for leading warehouses on our sister sites Google Ads to Redshift, Google Ads to BigQuery, Google Ads to Azure Synapse Analytics, Google Ads to PostgreSQL, Google Ads to Panoply, and Google Ads to Snowflake.

Easier yet, however, is using a solution that does all that work for you. Products like Stitch were built to move data automatically, making it easy to integrate Google Ads with Amazon QuickSight. With just a few clicks, Stitch starts extracting your Google Ads data, structuring it in a way that's optimized for analysis, and inserting that data into a data warehouse that can be easily accessed and analyzed by Amazon QuickSight.