PowerMetrics: Connecting to Mailchimp (with data feeds)


Our recent redesign simplifies the data transfer experience by combining raw and modelled data sources into a single object - data feeds. We’re gradually releasing this new feature to our customers.
If you see Data Feeds in the left navigation sidebar, you’ll learn how to connect to your data and create data feeds in this article. If not, go here.


If you want to add Mailchimp instant metrics, go here.


Ready to get the most from your Mailchimp email marketing data? Get started by setting up a connection between PowerMetrics and your Mailchimp data and adding one (or more) data feeds.

When you're finished adding Mailchimp data feeds, you'll use them to power your custom metrics.

This article includes:

Creating a Mailchimp data feed

When you create a data feed, you:

Connecting PowerMetrics to your Mailchimp data

The first step in creating a Mailchimp data feed is to connect PowerMetrics to your data. The first time you connect PowerMetrics to your Mailchimp data, you'll be asked to enter your Mailchimp API Key.

How do I find my Mailchimp API Key?

  1. Click the following link: Your Mailchimp API Key.
  2. Enter your Mailchimp login credentials.
  3. Copy the number that displays in the API Key field. This is your Mailchimp API Key.
    Note: If, at some point, you need to know your Data Center Name, it is the characters following the dash at the end of your API Key, for example, us12.

You can use the same account connection every time you connect to Mailchimp. You can also edit the connection (rename or enter a different API Key) by clicking the 3-dot menu for the connection. (See below.)

To connect PowerMetrics to your Mailchimp data:

  1. In the left navigation sidebar, click the + button beside Data Feeds.
  2. Click Select data.
  3. On the Where is your data? page, select Mailchimp.
  4. If this is your first time connecting to Mailchimp:
    • Click Add account settings.
    • Enter your Mailchimp API Key and click Use account.
  5. If you’ve connected to Mailchimp before, we assume you want to use the same account and take you directly to the next step - Choosing the data you want to retrieve in the query builder. If you want to connect to a different account, you can do so there by clicking the account connection at the top of the data preview window (see below). You can either select an alternate, existing account or click “Add new account”.

    You're connected! Next step – choose the data you want to retrieve using the query builder.

Choosing the data you want to retrieve in the query builder

In the query builder, you tell us what data you want to retrieve for your data feed. Later, when you create custom metrics, you’ll choose which pieces of data from the data feed you want to display for each metric.

Using the data view you select, we’ll run a query to get a list of available columns (fields) from within the data view. You’ll then choose from those columns to specify what data to include in your data feed.

Tip: Use filtering to pinpoint the data you want to retrieve and include in your data feed. This reduces the size of the query, improving performance and ensuring you only get the data you actually need. You can apply filters to the data view and to columns in the left sidebar and in the data preview. Learn more about filtering.

To choose the data you want to retrieve:

  1. In the Choose data for your data feed page, under Data view, click the drop-down and choose the subset of data you want to query.

    Tip: Find the data view you’re looking for by entering its name in the search box or by entering the name of a column/field to find the data view that includes it.
    Note: Default data views are dynamically generated based on the artifacts you create in Mailchimp. For example, creating a mailing list in Mailchimp creates a corresponding custom data view for that mailing list. In the query builder, custom views display with the “Custom view” tag. (See below for an example):
  2. Under Data view filters, add required filters (if needed) and optional filters (if desired).
    Tip: APIs for some services include "StartDate" and "EndDate" as optional data view filters. Applying filters here, at the query (source) level, rather than later at the query results level can improve efficiency and simplify data handling.
  3. Under Columns, select the checkboxes beside the columns you want to include in your data feed.
    Tip: Columns represent the fields that are available for the data view you selected above. Each item you choose will display as a column in the data preview table. If there are a lot of columns to choose from and you know what you’re looking for, start typing the column name into the search box. You can add up to 30 columns for each data view.
  4. Optionally, apply filters to applicable columns to narrow down your data before previewing.
    Tip: You may find it easier to apply filters to columns in the next step (in the data preview table) as you can see your data more clearly there. However, if you know your data set well, applying filters in the sidebar can be beneficial because it removes excess data before previewing. It may also be necessary when your data is too large to query all at once.
  5. When you’re done selecting (and filtering) columns, click Preview data. The data preview window is populated with the results of the query for the columns you chose.
    Note: The data preview table can show up to the first 1000 rows of your data. As a result, if you have a large data set, some rows may not display. Using the drop-down, you can select the number of rows to display (50, 100, 500, or 1000). You can also see how long it took for your query to complete. (See below.)
  6. If this isn’t the data you want for your data feed, choose a different data view and/or columns. To preview your most recent choices, either click Preview data again or click reload data Reload data (located above the data preview table).
    Note: At the top of the data preview window, you can see the Mailchimp account you’re currently connected to (see below). By clicking it, you can change to a different account. If you change accounts, your recent choices are removed and you start over by choosing a data view and columns.
  7. In the data preview window, you can narrow down the data you want to include in your data feed by applying filters to applicable columns.
  8. When you’re satisfied with your choices, click Use this data.
    You've chosen your data. Next step - refine the data in the data feed editor.

Refining data in the data feed editor (optional)

You’ve arrived in the data feed editor where you can choose to either accept the automatic settings or make changes. Learn more about editing data feeds.

If you’re happy with the automatic settings:

  • Click Save data feed.

If you want to make changes:

  • Some common adjustments include changing the data format or names for columns, updating the data feed name, and combining columns using formulas - there are many customization options available.
  • If you want to adjust your query choices (for example, add or remove columns or filters) click the tile under Data service to return to the query builder. (See below.)
  • When you’re finished editing the data feed, click Save data feed.

Next steps - Creating Mailchimp custom metrics

Now that you've created one or more Mailchimp data feeds, you can return to them and use them to make custom metrics. A single data feed can be used to create a single or multiple custom metrics.

To create custom metrics using a data feed:

  1. In the left navigation sidebar, click Data Feeds to open your list of data feeds.
  2. Select the data feed you want to use for your custom metric.
  3. Click either the +Add metric button in the top right corner of the window or open the Metrics tab and click +Add metric. (See below.)
  4. Choose the settings for your custom metric and click Save metric. If you need help, go here to learn more.
    The metric opens in its homepage and is added to your list of metrics (accessed by clicking Metrics in the left navigation sidebar).

Learn more

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