This page provides you with instructions on how to extract data from Zapier and analyze it in Google Data Studio. (If the mechanics of extracting data from Zapier 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 Zapier?
Zapier lets non-programmers integrate multiple applications and services to automate repetitive tasks. It uses a graphical web interface – no coding involved.
Getting data out of Zapier
Zapier exposes data through webhooks. You can use Zapier webhooks to push data to a defined HTTP endpoint as events happen. Zapier supports form-encoded, XML, and JSON webhooks.
It's up to you to parse the objects you catch via your webhooks and decide how to load them into your data warehouse.
Keeping Zapier data up to date
Once you've set up the webhooks you want and have begun collecting data, you can relax – as long as everything continues to work correctly. You'll have to keep an eye out for any changes to Zapier’s webhooks implementation.
From Zapier to your data warehouse: An easier solution
As mentioned earlier, the best practice for analyzing Zapier data in Google Data Studio 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 Zapier to Redshift, Zapier to BigQuery, and Zapier to Snowflake.
Easier yet, however, is using a solution that does all that work for you. Products like Stitch were built to solve this problem automatically. With just a few clicks, Stitch starts extracting your Zapier 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 Google Data Studio.