This page provides you with instructions on how to extract data from Autopilot and load it into Amazon S3. (If this manual process sounds onerous, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)
What is Autopilot?
Autopilot is a visual tool that allows marketers to track their prospects' customer journeys. Some of the information stored in Autopilot is valuable input for business analytics.
What is S3?
Amazon S3 (Simple Storage Service) provides cloud-based object storage through a web service interface. You can use S3 to store and retrieve any amount of data, at any time, from anywhere on the web. S3 objects, which may be structured in any way, are stored in resources called buckets.
Getting data out of Autopilot
Autopilot exposes data through a REST API, which developers can use to extract information. For example, to retrieve a batch of 100 contacts, you could 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 Amazon S3
To upload files you must first create an S3 bucket. Once you have a bucket you can add an object to it. An object can be any kind of file: a text file, data file, photo, or anything else. You can optionally compress or encrypt the files before you load them.
Keeping Autopilot data up to date
At this point you’ve coded up a script or written a program to get the data you want and successfully moved it into your data warehouse. But how will you load new or updated data? It's not a good idea to replicate all of your data each time you have updated records. That process would be painfully slow and resource-intensive.
Instead, identify key fields that your script can use to bookmark its progression through the data and use to pick up where it left off as it looks for updated data. Auto-incrementing fields such as updated_at or created_at work best for this. When you've built in this functionality, you can set up your script as a cron job or continuous loop to get new data as it appears in Autopilot.
And remember, as with any code, once you write it, you have to maintain it. If Autopilot modifies its API, or sends a field with a datatype your code doesn't recognize, you may have to modify the script. If your users want slightly different information, you definitely will have to.
Other data warehouse options
S3 is great, but sometimes you want a more structured repository that can serve as a basis for BI reports and data analytics — in short, a data warehouse. Some folks choose to go with Amazon Redshift, Google BigQuery, PostgreSQL, Snowflake, Microsoft Azure Synapse Analytics, or Panoply, which are RDBMSes that use similar SQL syntax. If you're interested in seeing the relevant steps for loading data into one of these platforms, check out To Redshift, To BigQuery, To Postgres, To Snowflake, To Azure Synapse Analytics, and To Panoply.
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 move data from Autopilot to Amazon S3 automatically. With just a few clicks, Stitch starts extracting your Autopilot data, structuring it in a way that's optimized for analysis, and inserting that data into your Amazon S3 data warehouse.