This page provides you with instructions on how to extract data from Autopilot and load it into Google BigQuery. (If this manual process sounds onerous, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)
Autopilot is a visual tool that allows marketers to track the customer journey of their prospects. Some of the information stored in Autopilot can be valuable input for business analytics, but getting the information into a data warehouse can be a chore.
What is Google BigQuery?
Google BigQuery is a data warehouse that delivers super-fast results from SQL queries, which it accomplishes using a powerful engine dubbed Dremel. With BigQuery, there's no spinning up (and down) clusters of machines as you work with your data. With all of that said, it's clear why some claim that BigQuery prioritizes querying over administration. It's super fast, and that's the reason why most folks use it.
Getting data out of Autopilot
Autopilot exposes data through a REST API, which developers can use to extract information. Each API call must contain an API authentication key. To get the API key for your Autopilot account:
- Log in at https://login.autopilothq.com
- Go to Settings > Autopilot API
- Click "Generate"
- Copy the API key
You must use the API key in every method call, in a header called
Once you have an API key, you can use a GET method to retrieve data via the API. For example, to retrieve a batch of 100 contacts, call
The call returns a JSON object with two or three properties as a reply:
total_contacts: the total number of contacts
contacts: the current batch of 100 contacts
bookmark: if there are more contacts on the list, the bookmark allows you to access the next group of contacts via another GET call.
Each Autopilot contact may have any or all of 26 standard fields, along with any custom fields you may have defined.
Loading data into Google BigQuery
Google Cloud Platform offers a helpful guide for loading data into BigQuery. You can use the
bq command-line tool to upload the files to your awaiting datasets, adding the correct schema and data type information along the way. The
bq load command is your friend here. You can find the syntax in the bq command-line tool quickstart guide. Iterate through this process as many times as it takes to load all of your tables into BigQuery.
Other data warehouse options
BigQuery is really great, but sometimes you need to optimize for different things when you're choosing a data warehouse. Some folks choose to go with Postgres or Redshift, which are two RDBMSes that use similar SQL syntax. If you're interested in seeing the relevant steps for loading this data into Postgres or Redshift, check out To Redshift and To Postgres.
Easier and faster alternatives
If all this sounds a bit overwhelming, don’t be alarmed. If you have all the skills necessary to go through this process, chances are building and maintaining a script like this isn’t a very high-leverage use of your time.
Thankfully, products like Stitch were built to solve this problem automatically. With just a few clicks, Stitch starts extracting your Autopilot data via the API, structuring it in a way that is optimized for analysis, and inserting that data into your Google BigQuery data warehouse.