Mailchimp
to
PostgreSQL

Connect Mailchimp to PostgreSQL with No Code

With Portable, you can sync Mailchimp data into your PostgreSQL warehouse in minutes. Access all of your Integrated Marketing Platform data from PostgreSQL without having to manage cumbersome ETL scripts.

The Two Paths To Connect Mailchimp To Your Data Warehouse

There are two ways to sync data from Mailchimp into your data warehouse for analytics.

Method 1: Manually Developing A Custom Data Pipeline Yourself

Write code from scratch or use an open-source framework to build an integration between Mailchimp and your warehouse.

Method 2: Automating The ETL Process With A No-Code Solution

Leverage a prebuilt connector from a cloud-hosted solution like Portable.

Two Paths To Connect Mailchimp To Your Data Warehouse
Two Paths To Connect Mailchimp To Your Data Warehouse

How To Create Value With Mailchimp Data

Teams connect Mailchimp to their data warehouse to build dashboards and generate value for their business. Let’s dig into the capabilities Mailchimp exposes via their API, outline insights you can build with the data, and summarize the most common analytics environments teams are using to process their Mailchimp data.

Extract: What Data Can You Extract From The Mailchimp API?

Mailchimp is an integrated marketing platform used for audience management, automation, insights, and analytics.

To help clients power downstream analytics, Mailchimp offers an application programming interface (API) for clients to extract data on business entities. Here are a few example entities you can extract from the API.

  • Lists
  • Members
  • Campaigns
  • Automations
  • Automation Emails
  • Landing Pages
  • Etc.

You can visit the Mailchimp API documentation to explore the entire catalog of available API resources and the complete schema definition for each. As an example, here are some of the details for the campaigns endpoint in the Mailchimp API documentation.

Mailchimp campaigns API
Mailchimp campaigns API

As you think about the data you will need for analytics, don’t forget that Portable offers no-code integrations to other similar applications like HubSpot, Sendinblue, and Klaviyo that can be useful for comparison purposes.

Regardless of the SaaS solution you use, it’s important to find a integrated marketing platform with robust data available for analytics.

Load: Which Destinations Are Best For A Mailchimp ETL Pipeline?

To turn raw data from Mailchimp into dashboards, most companies centralize information into a data warehouse or data lake. For Portable clients, the most common ETL pipelines are:

  1. Mailchimp to Snowflake Integration
  2. Mailchimp to Google BigQuery Integration
  3. Mailchimp to Amazon Redshift Integration
  4. Mailchimp to PostgreSQL Integration
Common Data Warehouses
Common Data Warehouses

Once you have a destination to load the data, it’s common to combine Mailchimp data with information from other enterprise applications like Jira, HubSpot, Zendesk, and LinkedIn.

From there, you can build cross-functional dashboards in a visualization tool like Power BI, Tableau, Looker, or Retool.

Develop: Which Dashboards Should You Build With Mailchimp Data?

Now that you have identified the data you want to extract, the next step is to plan out the dashboards you can build with the data.

As a process, you want to consume raw data, overlay SQL logic, and build a dashboard to either 1) increase revenue or 2) decrease costs.

Here are three email analytics dashboards you should consider as a starting point.

  1. Customer Lifecycle Summary - The best way to improve the client experience is to understand the touchpoints where your marketing team engages with those customers. You can create a summary of the customer lifecycle based on the campaigns that are sent to various lists.
  2. Contact Summary View - Create a dashboard with a filter at the top (to select a specific contact). From there, break out all of the lists and automations that the customer is included in. It's the beginning of a customer 360 view and can involve data from other data sources as well.
  3. Audience Insights - Offer users the ability to select a specific audience. Once an audience is selected, you can break down the audience based on member details. For instance, you can create a geography breakdown, a summary by sign-up date, and slice the audience by custom tags you have added to members.

Beyond the dashboards above, replicating Mailchimp data into your cloud data warehouse can unlock a wide array of opportunities to power analytics, automate workflows, and develop products. The use cases are endless.

Now that we have a clear sense of the insights we can create, let’s compare the process of developing a custom Mailchimp integration with the benefits of using a no-code ETL solution like Portable.

Method 1: Building A Custom Mailchimp ETL Pipeline

To build your own Mailchimp integration, there are three steps:

  1. Navigate the Mailchimp API documentation
  2. Make your first API request
  3. Turn an API request into a complete data pipeline

Let’s walk through the process in more detail.

How To Interpret Mailchimp’s API Documentation

When reading API documentation, there are a handful of key concepts to consider.

Authentication

There are many common authentication mechanisms. OAuth 2.0 (Auth Code and Client Credentials), API Keys, JWT Tokens, Personal Access Tokens, Basic Authentication, etc. For Mailchimp, it’s important to identify the authentication mechanism and how best to incorporate the necessary credentials into your API requests.

Mailchimp uses OAuth 2.0 Auth Code for authentication. Developers need to create an application with a client ID and client secret, redirect users to an authentication URL, and generate a token. Once a bearer token is generated, it is added to the API header for every request.

Mailchimp Authentication Overview
Mailchimp Authentication Overview

Authorization

In addition to understanding how to authenticate with the Mailchimp API, it’s also important to understand the permissions and scopes necessary to make calls to various API endpoints and how access is granted to users and systems.

For OAuth applications, users can grant access to their specific account and can revoke access to a specific API consumer.

Resources

It’s important to identify the Mailchimp API endpoints you want to use for analytics. Most APIs offer GET, POST, PUT, and DELETE methods; however, for analytics, GET requests are typically the most useful. At times, POST requests can be used to extract data as well.

For Mailchimp, the campaigns endpoint is a great place to get started.

Request Parameters

For each API endpoint, you would like to use for analytics, you need to understand the method (GET, POST, PUT, or DELETE) and the URL, but there are other considerations to take into account as well. You should look out for pagination mechanics, query parameters, and parameters that are added to the request path.

Mailchimp uses count and offset parameters for pagination.

Mailchimp Pagination Overview
Mailchimp Pagination Overview

Most requests require a data center ID, and some API endpoints require unique identifiers from a previous API response to be included in the URL path. For instance, to list all members for a list, you need a data center ID and a list ID that is returned from another endpoint.

Mailchimp API Request Parameters
Mailchimp API Request Parameters

How Do You Call The Mailchimp API? (Tutorial)

  1. Follow the instructions above to read the Mailchimp API documentation
  2. Identify and collect your credentials for authentication
  3. Pick the API resource you want to pull data from
  4. Configure the necessary parameters, method, and URL to make your first request (Either with curl or Postman)
  5. Add your credentials and make your first API call. Here is an example request using curl (without real credentials):
curl -X GET \
  'https://${dc}.api.mailchimp.com/3.0/campaigns' \
  --user ""anystring:${apikey}""'

How Do You Maintain A Custom Mailchimp ETL Pipeline?

Making a call to the Mailchimp API is just the beginning of maintaining a complete custom ETL pipeline.

Here is a getting started guide to building a production-grade pipeline for Mailchimp:

  • For each API endpoint, define schemas (which fields exist and the type for each)
  • Process the API response and parse the data (typically parsing JSON or XML)
  • Handle and replicate nested objects and custom fields
  • Identify which fields are primary keys and which keys are required vs. optional
  • Version control your changes in a git-based workflow (using GitHub, GitLab, etc.)
  • Handle code dependencies in your toolchain and the upgrades that come with each
  • Monitor the health of the upstream API, and - when things go wrong - troubleshoot via the status page, reach out to support, and open tickets
  • Handle error codes (HTTP error codes like 400s, 500s, etc.)
  • Manage and respect rate limits imposed by the server

We won’t go into detail on all of the items above, but rate limits are a great example of the complexity found in a production-grade data pipeline.

For rate limits, the Mailchimp documentation doesn't reference an explicit threshold for requests over a time frame; however, the marketing API does limit the number of concurrent connections you can make from a single API key.

Mailchimp Rate Limits
Mailchimp Rate Limits

If you don’t respect rate limits, and if you can’t handle server responses (like 429 errors with a Retry-After header), your pipeline can break, and analytics can become out-of-date.

What Are The Drawbacks Of Building A Mailchimp ETL Pipeline Yourself?

You can probably tell at this point that there is a lot of work that goes into building and maintaining an ETL pipeline from Mailchimp to your data warehouse.

If you want less development work, faster insights, and no ongoing responsibilities, you should consider a cloud-hosted ETL solution.

Let’s walk through the setup process for a no-code ETL solution and its benefits.

Method 2: Using A No-Code Mailchimp ETL Solution

No-code ETL solutions are simple. Vendors are specialized in building and maintaining data pipelines on your behalf. Instead of starting from scratch for each integration. Companies like Portable create connector templates that can be leveraged by hundreds or thousands of clients.

Step-By-Step Tutorial For Configuring A Mailchimp ETL Pipeline

Off-the-shelf ETL tools offer a no-code setup process. Here are the instructions to connect Mailchimp to your cloud data warehouse with Portable.

  1. Create an account (no credit card required)
  2. Add a source - Search for and select Mailchimp
  3. Authenticate with Mailchimp using the instructions in the Portable console
  4. Select your warehouse (Snowflake, BigQuery, Redshift, or PostgreSQL) and authenticate
  5. Set up a flow connecting Mailchimp to your analytics environment
  6. Run your flow to replicate data from Mailchimp to your warehouse
  7. Use the dropdown to set your data flow to run on a cadence

What Are The Benefits Of Using Portable For Mailchimp ETL?

No-Code Simplicity

Start moving Mailchimp data in minutes. Save yourself the headaches of reading API documentation, writing code, and worrying about maintenance. Leave the hassle to us.

Easy To Understand Pricing

With predictable, fixed-cost pricing per data flow, you know exactly how much your Mailchimp integration will cost every month.

Fast Development Speeds

Access lightning-fast connector development. Portable can build new integrations on-demand in hours or days.

Hands-On Support

APIs change. Schemas evolve. Mailchimp will have maintenance issues and errors. With Portable, we will do everything in our power to make your life easier.

Unlimited Data Volumes

You can move as much Mailchimp data as you want without worrying about usage credits or overages. Instead of analyzing your ETL costs, you should be analyzing your data.

Free To Get Started

Sign up and get started for free. You don’t need a credit card to manually trigger a data sync, so you can try all of our connectors before paying a dime.

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