PowerMetrics: Adding Airtable custom metrics (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 add Airtable custom metrics in this article. If not, go here.


Visualize, discover, and act on your Airtable database-spreadsheet data with metrics and metric dashboards!

Get started by connecting to your Airtable data and adding some custom metrics.

This article includes:

Connecting to your Airtable data

One of the first steps toward adding custom metrics is connecting PowerMetrics to your Airtable data. Here are a couple things to note about connecting:

Your data is safe with us. The first time you connect your Airtable data to PowerMetrics, you'll be prompted to enter your Airtable login credentials and give permission to allow access to the data within your Airtable account. We are serious about protecting your data privacy.

Managing your connections. By default, your connection name looks like this: yourname<date and time created>. You can rename connections from your list of connections (accessed by clicking the in the left navigation sidebar and selecting Connections) or within the application as you add metrics. Go here for more information on managing your account connections. You can use the same account connection every time you connect to Airtable. If you have trouble accessing an existing connection, your OAuth token may have expired. If that happens to you, check out these troubleshooting tips.

Adding Airtable custom metrics

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 Airtable custom metrics, you:

Connecting to your Airtable account and adding a data feed

The first time you connect PowerMetrics to your Airtable data, you log into your Airtable account, allow Klipfolio PowerMetrics to access your Airtable data, and specify the data you want to connect to by choosing account settings (your Airtable base). When you create custom metrics next time, you can use the same account connection or select a new account 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 Airtable account and add a data feed:

  1. In the left navigation sidebar click the + button beside Metrics and select Browse all services.
  2. On the Where is your data? page, select Airtable.

Note: Your metrics will refer to data that’s associated with the Airtable account you’re currently connected to. If you’ve connected to Airtable before but want to use a different account this time, click the currently-connected account in the upper-right corner of the window to select a different account and/or account settings.

  1. If this is your first time connecting to Airtable:
  • Click +New data feed > Select Airtable data.
  • Click Add new account.

  • Enter your Airtable login credentials and click Sign in.
  • Click +Add a base and either select All current and future bases in all current and future workspaces or a specific base. We recommend you select the "All current and future bases" option, as, if you add a specific base and want to add another one later, you'll need to update your account connection (token) to be able to select it as an option in PowerMetrics.

  • Click Grant access to allow Klipfolio PowerMetrics to securely access your Airtable data.
  • Next, to further define the data you're looking for, under Select account settings, click Add account settings.
  • Under Choose account settings, select the Airtable base from the drop-down list. Click Use account.

Note: The next time you connect to Airtable to create a custom metric, you won’t need to enter your Airtable credentials or select your account settings. That’s because we assume you want to use the same account as before. If you want to connect to a different account, you can do so when choosing data to include in your data feed (in the query builder) 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”.

  1. If you’ve connected to Airtable before:

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.

  1. 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.

  1. 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.

  1. 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.

  1. 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 display up to the first 1000 rows of your data. As a result, if you have a large data set, some rows may not display.

  1. 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 Reload data (located above the data preview table).

Note: At the top of the data preview window, you can see the Airtable 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.

  1. 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.
  2. When you’re satisfied with your choices, click Save query.

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.

If you’re happy with the automatic settings:

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.)

Learn more about editing data feeds.

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 an Airtable data feed. Next step - choose settings for your custom metric.

Choosing settings for your custom metric

To choose settings for your custom metric:

  1. Under Measure, select the column from the data feed that contains the values you want to track in your metric.

Note: The metric is automatically named based on the measure you choose. However, you can type over this name and apply a custom one if desired.

  1. 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 timestamp column, select Use the date and time imported instead.

  1. Under Data structure, select from Include all values, Use latest values, or Use latest values per period. Your choice determines the data points your metric will use when calculating the metric value for a time period.

Here’s a bit more information to help you decide. Choose different options and see the impact of your choice as a live preview, before saving the metric. If you’re still unsure which option is best, that’s okay. You can change your selection later by editing the metric.

  • Include all values: Select this option if you want to include every value for a time period to create the total of values. For example, you may have a spreadsheet that includes all sales transactions for the month of January. In this case, you want to sum all values to get the total values for the month.
  • Use latest values: Select this option if your data includes current value totals for specific points in time and new values replace older values. For example, if you’re tracking social media followers, each import gives you the current value, which is the total of all values for the time period.
  • Use latest values per period: (Hour, Day, Week, Month, Year) Select this option if each value in your data is a summary of a time period. For example, with Google Analytics "sessions by day" data, the value at any point in time is the summary up to that point in the day. Your data is collected again on the following day, beginning at zero. In such cases, the last value is the complete summary of the day. To calculate the metric's value for a month, you sum the last value for each day in the month. When you select this option, you also select a time period from the drop-down list below it (Hour, Day, Week, Month, or Year).

After selecting the measure, date and time, and data structure settings, your metric displays as a live preview and the settings under Properties are available for you to select. We encourage you to experiment with all of the settings until the metric is exactly what you’re looking for. Then click Save metric.

Here are a few notes about the settings listed under Properties:

  • Default aggregation: The default aggregation type is 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 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.

  • Show as cumulative (optional): Set your data to display cumulatively by default for all of the metric's view modes.

  • Favourable trend (optional): 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.

  • Format: Select a data format. The choices include: 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.

  • Segmentation: Select the columns by which you want to be able to segment and filter your metric value. You can select up to 5 columns. Each selection shows a unique view of your business, for example, you might choose to segment your sales data based on region, sales rep, or product type. The segments you select when creating a metric become filters in the finished metric. You can filter on the individual metric level or at the dashboard level (when you add your metric to a dashboard). You can also create a metric with no segmentations, by not selecting any dimensions.

Note: When choosing segmentation, you can only select columns that have a text format. If the associated data feed doesn’t include any text columns (or has only one text column) there will be no available categories by which to segment.

  • Data feed: If you click the area under Data feed, the associated data feed opens so you can view or edit it. (See below.) Learn about editing data feeds.

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.

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