Drip to Redshift

This page provides you with instructions on how to extract data from Drip and load it into Redshift. (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 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": "",
  "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.

Loading data into Redshift

Once you've identified the columns you want to insert, you can use the Redshift CREATE TABLE statement to set up a table to receive all of the data.

To populate that table, you might be tempted to use INSERT statements to add data to your Redshift table row by row. Don't do that; Redshift isn't optimized for inserting data one row at a time. If you have a high volume of data to be inserted, a better approach is to load the data into Amazon S3 and use the COPY command to migrate it into Redshift.

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.

Other data warehouse options

Redshift is great, but sometimes you need to optimize for different things when you're choosing a data warehouse. Some folks choose to go with Google BigQuery, PostgreSQL, or Snowflake, which are RDBMSes that use similar SQL syntax, or Panoply, which works with Redshift instances. If you're interested in seeing the relevant steps for loading data into one of these platforms, check out To BigQuery, To Postgres, To Snowflake, 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 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 your Redshift data warehouse.