Creating metrics

PowerMetrics offer a wealth of opportunities for you to visualize, learn from, and share your data. As with all PowerMetrics features, the metric creation process is highly flexible, with multiple options to help you envision your most essential data and track your business metrics meaningfully.

Before adding a metric, consider the data you want to visualize. What data service do you want to connect to? What metric do you want to measure? For example, if you want to track customer interaction with your company’s website, you could connect to your data in Google Analytics and track interactions using the Sessions metric.

If you’re not sure which metrics to track, our instant metric options can help. Want to get creative? We have custom metric options too.

This article contains the following sections:

Metric options - Instant, custom, or calculated?

In PowerMetrics, you can add instant metrics, custom metrics, or calculated metrics.

  • Instant metrics get their data directly from 3rd-party services. Just sign in!
  • Custom metrics get their data from modelled data sources you create. These can be based on something as simple as a spreadsheet or as sophisticated as an SQL query.
  • Calculated metrics get their data from formulas that combine metrics. Calculated metrics are described in depth in this article.

Why instant metrics?

  • They’re fast! They provide instant access to the most popular metrics for the most essential data services.
  • They’re for everyone. You don’t have to be a data expert to create powerful, meaningful metrics. No data modelling, formula writing, or further configuration is required.
  • They’re created for you based on best practices and industry expertise. They’re great when you know what you’re looking for and also when you don’t!

Why custom metrics?

  • They give you access to hundreds of data services. We are continuously adding to our library of instant metrics. However, if the metric you’re looking for isn’t covered by our instant metrics, you can create a custom metric instead. Our custom metrics give you access to hundreds of data services and all the metrics you can imagine.

Why calculated metrics?

  • They’re cross-service. You can combine metrics from different services.
  • They’re customizable. With the ability to combine metrics, using formulas, you can create the exact metric you need for every situation.

Data service options - Where is your data coming from?

When adding new metrics, one of the first steps is choosing the service you want to get data from. The metric options available to you depend on the service you choose:

  1. Many popular services support both instant metrics and custom metrics.

Some examples include: Google Analytics, Facebook, Quickbooks, Instagram Business, and HubSpot.

  1. All other services can be used to create custom metrics only.

These services include file-based and query-based services such as: file upload, SQL and REST/URL queries, and FTP & SFTP. They also include services with public APIs that aren’t enabled yet for instant metrics. Some examples of such services are: Insightly, Moz, and Twilio.

Adding instant metrics

Our instant metrics cover the most popular metrics for the most popular data services. They get you to your data fast!

When you add instant metrics, you:

  1. Connect PowerMetrics to your data.

You’ll create a reusable account connection by logging into your service account and giving permission for Klipfolio PowerMetrics to access your data. Learn more about managing your account connections.

  1. Choose metrics to visualize and track.

Each data service includes a wide variety of instant metrics - and we’re adding more all the time!

Click the links below to go to specific instructions for adding instant metrics for these data services:

Creating custom metrics

Custom metrics put you in control of your data choices. Specific instructions vary depending on the data service you choose:

In general, when you create custom metrics, you:

  1. Connect PowerMetrics to a service.

You’ll create a reusable account connection by logging into your service account and giving permission for Klipfolio PowerMetrics to access your data.

  1. Create a modelled data source, which acts as a channel between a service and your custom metric.

Modelled data sources are the conduit between data services and custom metrics. They continuously transfer data from the service to the metric where the data is stored. When you create a modelled data source, you choose the data to query and then, optionally, further refine that data. A single modelled data source can be used to create a single or multiple custom metrics.

  1. Choose settings for your metric.

In this step, you’ll choose display settings and which data to include in your metric.

Creating custom metrics for services that also have instant metrics

If your data service includes instant metrics but you don’t see the metric you’re looking for, you can create a custom metric instead.

Click the links below to go to specific instructions for adding custom metrics for these data services:

Want to see custom metric creation in action? This informative video includes examples for Google Analytics and HubSpot:

Creating custom metrics for custom-only data services

Some data services are not enabled yet for instant metrics and can only be used to create custom metrics.

There are a couple things to note before creating metrics for custom-only data services:

      • Connecting PowerMetrics to your data.

Some services require you to connect to your data, usually by entering your login credentials but sometimes by entering other identifiers such as API keys and account IDs. Instructions for connecting can differ between services. If you need help connecting to specific services, refer to this section in our Knowledge Base.

      • Custom metrics require modelled data sources.

If you already have a raw (unmodelled) data source you want to use for your custom metric, you must model it before building your metric. After modelling the data source, you’ll be able to select it during the custom metric creation process and then quickly advance to creating your metric.

If you choose to model your data while you create your metric, in the Verify your data page, either click Continue (to accept the auto-selected choices for modelling your data source) or, if you want to make modifications to the modelled data source, click the Edit button, make changes, and then click Save. For more information about modelled data sources, see: Introduction to modelled data sources and How do I model a data source?

To create custom metrics for custom-only data services:

      1. In the left navigation sidebar, click the + button beside Metrics.

Note: You can also add a custom metric from the Metric List page or from an open dashboard, in Edit mode.

OR

      • Use an existing data source if you already have a modelled data source you want to use to build the metric. Next, on the Saved data sources page, select the modelled data source.

OR

      • Select one of the options under Core Data Services:
      • Upload a file
      • REST/URL
      • SQL Query
      • FTP & SFTP

OR

      • Select a data service that doesn’t include support for instant metrics: These display under All Data Services and can be found quickly by entering their name into the search field.
      1. Regardless of the option you chose above, follow the workflow until you arrive at the Create a custom metric page where you will configure your custom metric.

      1. In the Connect to your data step, you can:
      • Click Modify data to see details for (or edit) your selected data source.
      • Click Use a different data connection to choose a different, saved data source or to create a new data source.
      1. In the Select a metric value step, choose which column of data you want to track in your metric.

Once you've chosen a metric value, its default aggregation type displays. 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.

      1. In the Segment metric value by category step, select the categories by which you want to segment or filter your data.

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).

If you want to create a metric without allowing filtering or segmentation, click the toggle button at Segment values for this metric to turn off this step in the setup wizard.

If the modelled data source for your metric doesn’t include any text columns (or has only one text column) there will be no available categories by which to segment. This step will be marked as complete and you will move on to the next step in the wizard. If you want to add columns to your modelled data source to enable segmentation, click Modify data.

      1. In the Select a date column step, either select a timestamp column from your modelled data source or Use the current date and time (if your modelled data source doesn’t include a timestamp column).

      1. In the Tell us about your data step, select an appropriate aggregation method: Transactional values, Current values, or Periodic summary. Your choice determines the data points your metric will use when calculating the metric value for a time period. If you’re unsure which selection is best don’t worry, you can change your selection later by editing the metric:
      • Transactional 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.
      • Current 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 are tracking social media followers, each import gives you the current value, which is the total of all values for the time period.
      • Periodic summary: (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).
      1. In the Connect to your data step:
      • Enter a Name for the metric.
      • Choose a data format: Numeric, Currency, Percentage, or Duration.
      • Set your data to Show as cumulative by default for all of the metric's view modes.
      • Set the Favourable trend for your metric. 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. Note: This option is not applicable to all visualization types.
      1. Click Save.

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 that dashboard and to your list of metrics.

Now you're ready to explore your metric by personalizing and experimenting with your data! Learn more about exploring your data.

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