SendGrid to Google Data Studio

This page provides you with instructions on how to extract data from SendGrid and analyze it in Google Data Studio. (If the mechanics of extracting data from SendGrid 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 SendGrid?

SendGrid provides a customer communication platform for transactional and marketing email. It allows companies to send email without having to maintain their own email servers.

Getting data out of SendGrid

SendGrid gives customers a number of ways to export data out of its system. It offers Web, SMTP, and SendGrid APIs, and also supports two kinds of webhooks: The Event Webhook POSTs when an email event occurs, such as a bounce or an unsubscribe. The Inbound Email Parse Webhook receives emails and then POSTs their constituent parameters (subject, body, and attachments).

Suppose you wanted a list of all bounced email. You could use the Web API to call GET /v3/suppression/bounces and specify optional parameters for things like start and end times.

Sample SendGrid data

SendGrid’s API returns JSON-format data. The data returned for a "bounced email" call might look like this:

[
  {
    "created": 1443651125,
    "email": "testemail1@test.com",
    "reason": "550 5.1.1 The email account that you tried to reach does not exist. Please try double-checking the recipient's email address for typos or unnecessary spaces. Learn more at  https://support.google.com/mail/answer/6596 o186si2389584ioe.63 - gsmtp ",
    "status": "5.1.1"
  },
  {
    "created": 1433800303,
    "email": "testemail2@testing.com",
    "reason": "550 5.1.1 : Recipient address rejected: User unknown in virtual alias table ",
    "status": "5.1.1"
  }
]

Preparing SendGrid data

If you don't already have a data structure in which to store the data you retrieve, you'll have to create a schema for your data tables. Then, for each value in the response, you'll need to identify a predefined datatype (INTEGER, DATETIME, etc.) and build a table that can receive them. SendGrid's documentation should tell you what fields are provided by each endpoint, along with their corresponding datatypes.

Complicating things is the fact that the records retrieved from the source may not always be "flat" – some of the objects may actually be lists. This means you'll likely have to create additional tables to capture the unpredictable cardinality in each record.

Keeping SendGrid 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 SendGrid.

And remember, as with any code, once you write it, you have to maintain it. If SendGrid modifies its API, or the API 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.

From SendGrid to your data warehouse: An easier solution

As mentioned earlier, the best practice for analyzing SendGrid 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 SendGrid to Redshift, SendGrid to BigQuery, and SendGrid 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 SendGrid 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.