Drip to Google Data Studio

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

Drip is an online marketing automation platform.

Getting data out of Drip

You can collect data from Drip’s servers using webhooks and user-defined HTTP callbacks. Set up the webhook in your Drip account, and define a URL that your script listens to and from which it can collect the data.

Sample Drip data

Once you've set up webhooks and HTTP endpoints, Drip will begin sending data via the POST request method. Data will be enclosed in the body of the request in JSON format. Here's a sample of what that data might look like.

{
  "id": "z1togz2hcjrkpp5treip",
  "status": "active",
  "email": "john@acme.com",
  "custom_fields": {
    "name": "John Doe"
  },
  "tags": ["Customer", "SEO"],
  "time_zone": "America/Los_Angeles",
  "utc_offset": -440,
  "created_at": "2017-06-21T10:31:58Z"
  "ip_address": "123.123.123.123",
  "user_agent": "Mozilla/5.0",
  "lifetime_value": 2000,
  "original_referrer": "https://google.com/search",
  "landing_url": "https://www.drip.co/landing",
  "prospect": true,
  "base_lead_score": 30,
  "lead_score": 65,
  "user_id": "123"
}

Preparing Drip data

You need to map all the data fields in the JSON data from your webhook into a schema that can be inserted into your database. For each value in the response, you need to identify a predefined datatype (i.e. INTEGER, DATETIME, etc.) and build a table that can receive them.

Keeping Drip data up to date

Once you’ve coded up a script or written a program to get the data you want and move it into your data warehouse, you’re going to have to maintain it. If Drip modifies its webhook implementation, 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.

From Drip to your data warehouse: An easier solution

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