This page provides you with instructions on how to extract data from Google Ads and analyze it in Tableau. (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 Tableau?
Tableau is one of the world's most popular analysis platforms. The software helps companies model, explore, and visualize their data. It also offers cloud capabilities that allow analyses to be shared via the web or company intranets, and its offerings are available as both installed software and as a SaaS platform. Tableau is widely known for its robust and flexible visualization capabilities, which include dozens of specialized chart types.
In addition to its business software, Tableau also offers a free product called Tableau Public for analyzing open data sets. If you're new to Tableau, this offering is a great way to experience Tableau's capabilities at no cost and share your work publicly.
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 Tableau
Analyzing data in Tableau requires putting it into a format that Tableau can read. Depending on the data source, you may have options for achieving this goal, but the best practice among most businesses is to build a data warehouse that contains the data, and then connect that data warehouse to Tableau.
Tableau provides an easy-to-use Connect menu that allows you to connect data from flat files, direct data sources, and data warehouses. In most cases, connecting these sources is simply a matter of creating and providing credentials to the relevant services.
Once the data is connected, Tableau offers an option for locally caching your data to speed up queries. This can make a big difference when working with slower database platforms or flat files, but is typically not necessary when using a scalable data warehouse platform. Tableau's flexibility and speed in these areas are among its major differentiators in the industry.
Analyzing data in Tableau
Tableau's report-building interface may seem intimidating at first, but it's one of the most powerful and intuitive analytics UIs on the market. Once you understand its workflow, it offers fast and nearly limitless options for building reports and dashboards.
If you're familiar with Pivot Tables in Excel, the Tableau report building experience may feel somewhat familiar. The process involves selecting the rows and columns desired in the resulting data set, along with the aggregate functions used to populate the data cells. Users can also specify filters to be applied to the data and choose a visualization type to use for the report.
You can learn how to build a report from scratch for free (although a sign-in is required) from the Tableau documentation.
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 Tableau 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 SQL Data Warehouse, 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 from Google Ads to Tableau automatically. With just a few clicks, Stitch starts extracting your Google Ads data via the API, structuring it in a way that is optimized for analysis, and inserting that data into a data warehouse that can be easily accessed and analyzed by Tableau.