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Output types

Discover different output types and how to configure them.


Outputs are the results of a workflow. While designing your workflows, you can add markdown texts, tables, bar charts and pie charts. Let's take a closer look to each component and their settings.

Markdown

Markdown outputs are used for generating text results of your workflows with markdown formatting elements. You can also add buttons in new blocks. These buttons can call manual workflows in your app.

Info

Supported markdown elements are: Heading, Bold, Italic, Underline, Bullet list, Numbered list, Link and Images.

Visit markdown format page to see how you can style your outputs.

Configuring a markdown (text) output

Node title: The title you give to your output node becomes the title of the output displayed when the workflow is run. If your workflow has multiple outputs, users can click each of their title to navigate between them.

Blocks: Blocks are a series of components that can be combined to create visually rich and interactive outputs. You can select to add a markdown block or an action block.

  • Markdown block: A block that is used to display text messages. They are typically generated from responses of actions in your workflow. You can use markdown formatting elements to style your output and use Actioner's smart autocomplete to access the data from your nodes.

  • Action block: A block that inserts buttons to an output. The button can trigger a manual workflow from your app.

You can enter a label for the button, select its style and specify the workflow that will be triggered. You can select from the list of manual workflows in your app.

When you select a workflow on an action block, the parameters of the selected workflow opens up. These parameters are the inputs of the selected workflows. If you want to provide a value for a parameter, you can generate it from your rows or from nodes in your workflows. Entered value will be the value of the input when that workflow is run through your output. If you don't add any value to a parameter, users will need to enter that value while running the workflow.

Run immediately option: When enabled, the added workflow can be automatically executed through the output, without the need to enter any value.

→ Learn how to add workflows to markdown outputs.

Table

Action responses are often complex and contains a large number of arrays. Table outputs visually convert the JSON responses of actions to a paginated table for easy navigation. Each element of a JSON array is mapped to a row of a table. You can select the values to be included in your columns, style these columns and use other dynamic data sources for the cell values. You can also add button columns to your tables. When you add a button column, the workflows associated with that button can be run on the output and that workflow is triggered for only the row that the workflow is run for.

Configuring a table

Node title: The title you give to your output node becomes the title of the output displayed when the workflow is run. If your workflow has multiple outputs, users can click each of their title to navigate between them.

Table source: is generated from JSON responses of your actions. Use Actioner's smart autocomplete to access the data from your nodes.

Below example returns the tickets array from the body of the response to List tickets action. The alias of the action is action0. This notation maps each element of tickets array to a new row.

{{nodes.action0.response.body.tickets}}

Info

To style your output, you can use markdown.

Columns: are typically produced from the source entered for the table. Click + button to add a new column to your table. Next, provide a title and the value of your column. Title is placed as a key on the left side of the table. Value is placed on the right side of the table.

Typically, a property of an array element can be added as the value of a column. currentItem refers to the mapped element of an array. With adding a property to currentItem, you can access that property's value.

Below places the id values of each element on the selected column.

currentItem.id

To change the order of a column, click on it and while holding the mouse button down – drag to a new location.

Button columns: are configured to trigger manual workflows from your output.

You can enter a label for the button, select its style and specify the workflow that will be triggered. You can select from the list of manual workflows in your app.

When you select a workflow on a button column, the parameters of the selected workflow opens up. These parameters are the inputs of the selected workflows. If you want to provide a value for a parameter, you can generate it from your rows or from nodes in your workflows. Entered value will be the value of the input when that workflow is run through your output. If you don't add any value to a parameter, users will need to enter that value while running the workflow.

Run immediately option: When enabled, the added workflow can be automatically executed through the output, without the need to enter any value.

→ Learn how to add workflows to table outputs.

Key value table

JSON data often contains large number of nested objects. Key value table output converts each keys and value into a friendly table format. It extracts data from JSON objects and represents it as a key value pair. You can select the key value pairs to be included or excluded in your key value table and use other dynamic data sources for the cell values.

Configuring a key value table

Node title: The title you give to your output node becomes the title of the output displayed when the workflow is run. If your workflow has multiple outputs, users can click each of their title to navigate between them.

Key value table source: is generated from JSON responses of your actions. Use Actioner's smart autocomplete to access the data from your nodes.

Below example returns the ticket object from the body of the response to Get ticket action. The alias of the action is action0.

{{nodes.action0.response.body.ticket}}

Info

To style your output, you can use markdown.

Rows: are typically produced from the source entered for the table. Click + button to add a new row to your table. Next, provide a title and the value of your row. Title is placed as a key on the left side of the table. Value is placed on the right side of the table.

Typically, a property of an array element can be added as the value of a row. currentItem refers to the source of the table. With adding a property to currentItem, you can access that property's value.

Below places the id value on the selected row.

currentItem.id

To change the order of a row, click on it and while holding the mouse button down – drag to a new location.

Bar chart

Visually display comparison between different values such as volume changes or differences in total count over time. Works best with data such as daily sales volume or issue distribution by labels.

Configuring a bar chart

Node title: The title you give to your output node becomes the title of the output displayed when the workflow is run. If your workflow has multiple outputs, users can click each of their title to navigate between them.

Chart source: is generated from JSON responses of actions in your workflow. Use Actioner's smart autocomplete to access a JSON array from the data of your nodes.

Below example returns the tickets array from the body of the response to List tickets action. The alias of the action is action0.

{{nodes.action0.response.body.tickets}}

X-axis values: Typically, it is a field of the chart source that will be used to group and display your data. {{currentItem}} refers to the chart source. With adding a field after currentItem, you can group and display your data by that field.

Below shows distribution by priority when added in X-axis values field.

{{currentItem.priority}}

Dataset source: is a unique attribute from the chart source typically id.

Method: is an aggregation method, allowing you to summarize or combine data points within your visual chart. They are used to transform raw data into a more useful format for presentation

Available methods are: Sum, Count, Average, Median, Mode, Standard deviation, Minimum value, Maximum value, First value, Last value and Percentile.

Chart title: is the title of chart.

X-axis title: is the label of the X-axis.

Y-axis title: is the label of the Y-axis.

Pie chart

Divides a circle into multiple slices as proportional to their contribution towards the total sum. Useful for comparing the share or proportion of various items. Works best when you have only one data series; such as this month's total issue count distribution by issue priority.

Configuring a pie chart

Node title: The title you give to your output node becomes the title of the output displayed when the workflow is run. If your workflow has multiple outputs, users can click each of their title to navigate between them.

Chart source: is produced from JSON responses of actions in your workflow. Use Actioner's smart autocomplete to access a JSON array from the data of your nodes.

X-axis values: Typically, it is a field of the chart source that will be used to group and display your data. {{currentItem}} refers to the chart source. With adding a field after currentItem, you can group and display your data by that field.

Below shows distribution by status when added as X-axis values.

{{currentItem.status}}

Dataset source: is a unique attribute from the chart source typically id.

Method: is an aggregation method, allowing you to summarize or combine data points within your visual chart. They are used to transform raw data into a more useful format for presentation

Available methods are: Sum, Count, Average, Median, Mode, Standard deviation, Minimum value, Maximum value, First value, Last value and Percentile.

Chart title: is the title of chart.


Aggregation methods in charts

Sum

This method adds up all the data points in a set. For example, you use this method to generate a chart showing the total revenue per month.

Count

This aggregation method simply counts the number of data points in a set. For example, you can use this method to generate a chart showing the number of orders per day.

Average

This method calculates the average of all the data points in a set. For example, you can use this method to generate a chart showing the average rating of a product per month.

Median

This method calculates the middle value in a set of data. For example, you can use this method to generate a chart showing the median income of employees in a department.

Mode

This method calculates the most frequently occurring value in a set of data. For example, you can use this method to generate a chart showing the most popular product sold in a store.

Standard deviation

This method measures the amount of variation or dispersion of a set of data values. For example, you can use this method to generate a chart showing the variation in CSAT scores.

Minimum value

This method calculates the minimum value in a set. For example, you can use this method to generate a chart showing the team with the lowest sales volume.

Maximum value

This method calculates the maximum value in a set. For example, you can use this method to generate a chart showing the highest sales figure in each month.

First value

This method returns the first value in a set. For example, you can use this method to generate a chart showing the date of the first purchase made by a customer.

Last value

This method returns the last value in a set. For example, you can use this aggregation method to generate a chart showing the price of a product on the last day of the month.

Percentile

This method identifies the value below which a given percentage of observations in a group of observations fall. For example, you can use this method to generate a chart showing the 90th percentile of employee salaries in a department.