Visualize, discover, and act on your Mailchimp email marketing data with metrics and metric dashboards!

Get started by connecting to your Mailchimp data and adding some instant or custom metrics.

This article includes:

• Connecting to your Mailchimp data
• Adding Mailchimp instant metrics
• Adding Mailchimp custom metrics

Connecting to your Mailchimp data

The first time you connect Klipfolio 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.)
   

Adding Mailchimp instant metrics

PowerMetrics includes a wide variety of instant metrics for Mailchimp. Created for you by industry experts and based on best practices, our instant metrics will get you tracking your Mailchimp data in no time!

Note: The first time you connect to Mailchimp, you’ll need to enter your Mailchimp API Key.

The following procedure describes adding an instant metric from the left navigation sidebar. You can also add instant metrics from the Metric List page, or from Explorer, or from an open dashboard, in Edit mode.

To add Mailchimp instant metrics:

1. In the left navigation sidebar, click the + button beside Metrics and select See all services.
2. On the Where is your data page, select Mailchimp.
3. Select one or more instant metrics.
   You can select up to 5 metrics each time you visit this page. If you want to learn more about a metric, click the information button (see below) to see a brief metric definition, a list of available dimensions, and the metric formula. For more detailed information, click the link to go to its information page in MetricHQ.
   
4. Click Add metrics.
5. If this is your first time adding metrics for Mailchimp, click Add account settings.
   
6. Enter your Mailchimp API Key and click Use account.
   
   Note: The next time you add Mailchimp instant metrics, you won’t need to enter your Mailchimp API Key. That’s because we assume you want to use the same account as before and skip that step. However, if you want to connect to a different account, before clicking “Add metrics”, click the account connection in the top right of the window (see below) and either select an alternate, existing account or click “Add new account”.
   

 

That's all there is to it! You just added Mailchimp instant metrics to your account. If you added them from the navigation sidebar or from your Metric List page, they're added to your list of metrics. If you added them from an open dashboard, they're added to the dashboard and to your list of metrics. If you added them from Explorer, they open in Explorer and are added to your list of metrics.

You're ready to start analyzing and tracking your data as it changes over time. Learn more about viewing and exploring your data.

Note:

• Instant metrics are managed by Klipfolio. As such, they each have a set date range for the data being retrieved. If you add an instant metric and don’t see the date range you’re looking for, we suggest you create a custom metric instead.
• After adding an instant metric, you can edit it and set it as certified. Learn more about certifying metrics. You can also edit the metric to change its service icon. Learn more about changing metric icons. Learn more about editing instant metrics.

Adding Mailchimp custom metrics

If our Mailchimp instant metrics don’t get you to the data you’re looking for, create a custom metric instead.

Custom metrics use data feeds. Think of a data feed as the information channel between your source data and your metrics. Every time your data refreshes, the data feed gets updated accordingly. The resulting data is then added to the existing data for all the metrics that use the feed. Learn more about data feeds.

When you add Mailchimp custom metrics, you:

• Connect to your Mailchimp account and add a data feed.
• Choose the data to include in your data feed.
• Refine the data in the data feed editor (optional).
• Configure your custom metric.

Connecting to your Mailchimp account and adding a data feed

The first time you connect PowerMetrics to your Mailchimp data, you enter your Mailchimp API Key. When you create custom metrics next time, you can use the same account connection or add new account settings (using a different API Key) to point to different data.

Every custom metric needs a data feed. As you create your metrics, you’ll either create a new data feed or select one from your list of existing data feeds.

To connect PowerMetrics to your Mailchimp account and add a data feed:

1. In the left navigation sidebar, click the + button beside Metrics and select See all services.
2. On the Where is your data? page, select Mailchimp.
3. Click Can't find the instant metric you need? Build a custom metric instead. It's located at the end of your list of instant metrics. (See below.)
   
4. If this is your first time connecting to Mailchimp:
   • Click +New data feed > Select Mailchimp data.
   • Click Add account settings.
     
   • Enter your Mailchimp API Key and click Use account.
     
   • Next, choose the data to include in your data feed.
5. If you’ve connected to Mailchimp before:
   • You skip the account connection steps described above (we assume you want to use the same account settings as before) and go directly to the step for creating a new data feed or selecting an existing data feed.
     Note: If you want to connect to different account settings, you can do so in the query builder when choosing data to include in your data feed. There you can click the account connection at the top of the data preview window (see below) and select an alternate, existing account or click “Add new account”.
     
   • To create a new data feed, click Select data feed > +New Mailchimp data feed > Select Mailchimp data. Then, choose the data to include in your data feed.
   • To use an existing data feed, click Select data feed. Choose a data feed from the list on the Select a data feed page and click Select. Then, configure your custom metric.

Choosing data to include in your data feed

In the query builder, you tell us what data you want to retrieve for your data feed. When you use the data feed for your custom metrics, you’ll choose which pieces of data from the 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: You can apply filters to the data view and to columns in the left sidebar and in the data preview. Applying filters helps narrow down the data you’re looking for, ensuring you only query the data you need. By pinpointing your desired data, you optimize the volume of data being queried, which not only makes your data easier to understand and handle, it often makes the query run faster! Learn more about filtering.

To choose data to include in your data feed:

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 provided out-of-the-box from Mailchimp’s API. Custom 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.
   Note: 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 (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

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 and proceed to Configuring your custom metric.

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 and proceed to Configuring your custom metric.

Note: After you’re finished creating a custom metric with this data feed, you can return to it and use it to make more custom metrics. In the left navigation sidebar, click Data Feeds. Select the desired data feed from the list and click +Add metric.

You've created a Mailchimp data feed. Next step - Configuring your custom metric.

Configuring your custom metric

As you configure your custom metric, you can click the button, located beside “Measure”, “Date and Time”, and “Date handling”. This opens a guide for each setting that helps you decide which options to choose. As you make choices, you’ll see the result in the metric preview window on the left. Don’t worry about getting everything right the first time. Before clicking “Save metric”, you can go back and forth, making changes and observing the preview until you arrive at the configuration settings that give you the exact metric you’re looking for.

To configure your custom metric:

1. Under Data source, optionally, click Filter source data to include or exclude members for columns in the data feed. Excluded members will not display or be available as dimensions in the saved metric visualization.
   Note: You can filter by member or by condition. By default, the first time you apply filters to a metric, you’ll see the UI for member filtering. To filter by condition, click the “Condition filters” link. Note: You can apply up to 10 filter conditions/dimension.
   Tip: You can also view and edit the data feed that’s associated with this metric by clicking the tile as shown below.
   
2. Under Measure, select the column from the data feed that contains the values you want to track in your metric.
   
3. Under Dimensions, select the columns by which you want to be able to segment and/or filter your metric value (measure). Each selection shows a unique view of your business, for example, you might choose to look at your sales data based on region, sales rep, or product type.
• By default, selected dimensions will be available for filtering and segmentation in the final metric visualization. To modify this setting for individual dimensions, click All beside the dimension name and deselect the checkbox for as a filter or as a segment. (See below.)
  
• You can also create a metric with no ability to segment or filter, by not selecting any dimensions.
• Note: When choosing dimensions, you can only select columns that have a text format. If the associated data feed doesn’t include any text columns there will be no available categories by which to segment.
• Tip: You can optionally change a dimension’s name by selecting the current name and typing a new one. This changes the display name only (not the name of the dimension in the data feed). If you change the display name and want to see the one that’s being used in the data feed, hover over the dimension’s name. Note: If you change a name for a dimension that’s also being used by other metric visualizations, associated filters and segmentations will be removed from those visualizations and need to be reapplied.
• Note: The number of dimensions you can select depends on your pricing plan. To see details for your plan or to upgrade, click the button in the left navigation sidebar and select Plan.
4. Under Date and Time, select the column from the data feed that contains the date/time associated with each value.
   
   If the data feed doesn’t include a date column or history, deselect the Data feed contains historical data toggle to use the date and time the data feed is refreshed. (See below.)
   
5. Click the Settings tab.
   
6. Under Date handling, select Use all values or Use most recent values only. Your choice determines the data points your metric will use when calculating the metric value for a time period.
   
   If you chose Use most recent values only, select the desired time period. (See below.)
   
   If you need more help deciding which date handling option to choose, check out this article: Choosing the right date handling method for your custom metrics.
7. Under Format, select from Numeric, Currency, Percentage, or Duration.
   
   If you selected Currency as the data format, the default currency symbol that will display is USD $. You can select an alternate Currency symbol from the drop-down list. Note: This is a display option only. Currency is not converted.
   If you selected Duration as the data format, optionally, adjust the Maximum and Minimum Granularity settings.
8. Under Decimal places, select the number of decimals to display (from 0 - 9). The Auto setting displays up to 4 decimal places and drops trailing zeros.
   Note: If you change the decimal place setting for a metric and want to see the source data values with their original decimal places, reselect Auto.
9. Under Favourable trend, choose whether you want ascending or descending values to indicate a positive trend. For example, if your metric includes sales totals, a higher (ascending) number demonstrates a positive trend but, if your metric includes cost to acquire customers, a lower (descending) number indicates a positive trend. Favourable trends are indicated by a green arrow. Unfavourable changes in metric values are indicated by a red arrow.
   
10. Under Default aggregation, you’ll see the default aggregation type. It’s based on the measure you selected for the metric. For numeric columns, the default aggregation type is “sum”. For text columns, it's “count”. The default aggregation type will be used when the aggregation has not been set by the user in a metric visualization and wherever there are no configuration options available. For example, on the Metric List page, metrics will display using a default aggregation type based on your selection here.
    Note: When metrics are created, they’re automatically visualized using the most appropriate aggregation type. As such, we don’t recommend changing the default aggregation type.
    
11. Enable the Users can override aggregation option if you want to allow changes to the aggregation setting for the metric.
    
    Note: When metrics are created, they’re automatically visualized using the most appropriate aggregation type. As a result, we recommend disabling the ability to override the default aggregation.
12. Click the About tab.
    
13. Optionally, enter a new name and description for the metric.
    Note: The metric was automatically named based on the measure you chose.
14. Under Metric image, optionally, click Edit image to change the metric’s service icon. Learn more here.
15. Under Certification, optionally, enable the Certify this metric toggle. Learn more here.
16. When you’re done configuring your metric, click Save metric.

If you added the custom metric from the navigation sidebar or from your Metric List page, it's added to your list of metrics. If you added the custom metric from an open dashboard, it's added to the dashboard and to your list of metrics.

You're ready to start analyzing and tracking your data as it changes over time. Learn more about viewing and exploring your data.