Time series data is important for Customer Success because it helps you understand how your customer relationship has evolved over time. It allows you to ask important questions such as: "How is the usage of Module A compared to Module B in our Enterprise customers?" or "What is the pattern in Ticket requests from Customer A?”

However, there is a challenge in setting up calculated metrics using raw formulas. If you want a calculated metric showing the difference between the last 30 days of data and the previous 30 days of data this requires you to write a long and complex formula.

With Planhat’s metric template library creating new calculated metrics even complex ones becomes an easy task. Instead of working on the text-based formula and deciding which operations and in which order to use, you will be primarily working with templates similar to Automation templates.

Overview of functionality

When adding a new metric you will be greeted by the new Metric library interface. This is a starting point for your metric creation process.

The metric library has 3 main components to it:

The template cards section contains templated metrics that allow you to quickly add both system and calculated metrics. You can further customise the template after or use the template as a starting point for building more specific formulas.

The “New calculated metric" option will bring up an already familiar interface for adding new calculated metrics from scratch.

Navigate between different types of metrics - System or Calculated. Additional filtering tags will help you get to a subset of metrics that best suit your needs.

Within the Metric library, there is a System metrics section now. You now have more granular control over which system metrics to have in Planhat. Although system metrics are still predefined and are not customisable, you can add and remove system metrics depending on your needs. This contributes to having only the system metrics that are actually useful in your case and reduces the informational and visual noise.

Since system metrics are not customisable, your Planhat instance can have no more than one system metric of each kind added. System metrics that have already been added to your instance of Planhat will have a white background and explain that the metric has already been added. For system metrics that are available to be added, you will see a blue background and while hovering over a specific metric, you will also see a button that says “Add metric”.

Using the quick filtering on the left-hand side of the metric library by the “Calculated metrics” tag you can see the list of calculated metrics available to be added to your Planhat environment.

In the current version, you have access to 5 metrics that focus on trends over time:

Changes over time

Deviations from normal

Metric combinations

To add a metric from the template it's enough to simply click “Add metric” on the template card of your choice. After this, you will be taken to the metric customisation view.

In the metric customisation view, you can change various aspects of your metric. In case of Period-on-Period Change in Percentages, you can customise:

Once the metric has been created from the template you have access to all the usual customisation options:

For metrics created from a template, you still have access to the template that was used to create a metric and can adjust it using the same options without having to work on a text-based formula

In this view, it's also possible to view the formula that's under the hood of the template. Simply click on the eye icon in the right upper corner of the template area to view the underlying formula used for the metric.

Should you have a need to use the template as a quick start with the aim of building a more customised metric you can utilise the convert to formula functionality to gain access to the underlying formula.

The Metric template library gives you the option to quickly start getting insights from your time-series data without spending too much time figuring out how to build a custom formula. This in turn helps you drive actions within your customer base and understand the customers and changes in their behaviour much faster. 😊