Story Beat - GermainUX Docs

ServiceAnalytics

Availability2014.1 or later

Story Beat on a Flow

Sequence of user activities

Wait, Orient and Act

Time split across three phases

Hierarchical Labels

Five levels of descriptions

Analyze Friction with Story Beat

Spot where users struggle

Overview

Story Beat automatically converts low-level user activity into functional descriptions of what a user was doing in an application. Instead of requiring teams to interpret every click, mouse movement, scroll or field change individually, Story Beat organizes those signals into meaningful intervals of activity. This reduces noise and makes user journeys, business workflows and periods of lost productivity easier to understand. Depending on the monitored application, Story Beat can use application-specific context. For example, Shopify Pixel data can provide additional insight into product browsing, cart activity and checkout behavior.

What Story Beat Helps You Understand

Story Beat can help answer questions such as:

What was the user trying to accomplish?
Which functional steps did the user perform?
How much time was spent waiting, orienting and acting?
Where did the user become idle, delayed or blocked?
Which steps were repeated or abandoned?
Where did technology performance interrupt the workflow?
How did activity across multiple pages or browser tabs contribute to the journey?

From Click-Level Activity to Functional Insight

Story Beat analyzes activity at several levels of abstraction.

Level	Example
Raw interaction	Clicked a size selector
Functional action	Selecting a shoe size
Task	Reviewing product options
Journey stage	Comparing products
User intent	Rebuying a larger size of a previously returned shoe

Higher-level labels depend on the context available from the application and the clarity of the user’s behavior. Not every Story Beat will contain all levels.

Story Beat on a Flow

In a Flow visualization, Story Beats show the sequence of functional activities performed by users or sessions. This view can help teams:

Identify the most common paths through an application
See where users branch into alternative activities
Locate repeated, slow or abandoned steps
Compare successful and unsuccessful journeys
Understand which activities occur before a conversion, error or drop-off

More details on Flow Visualization and Journey.

Story Beat on a Focused Flow

A limits the analysis to a selected journey, workflow, population or outcome. Story Beats then describe the functional activities occurring within that scope. For example, a Focused Flow can analyze only:

Users who abandoned checkout
Employees who failed to complete a CRM workflow
Sessions containing a specific error
Customers who successfully converted
Users who followed an unexpected path

This reduces unrelated activity and helps teams understand why the selected journey succeeded or failed.

Story Beat Categories

Story Beat assigns user-session time to four activity categories:

Category	Meaning	Examples
Browse	The user explores or reviews information without triggering a primary action.	Reading, scrolling or moving the pointer while reviewing content
Trigger	The user initiates an action.	Selecting a link, button or other actionable element
Edit	The user enters or changes information.	Typing in a field, selecting an option or changing a checkbox
Idle	No user interaction is detected during the interval.	Pausing, leaving the application unattended or waiting without interacting

Together, these categories account for the analyzed session time.

Wait, Orient and Act

Each Story Beat can divide its duration into three phases:

Phase	Description	Example
Wait	Time during which network activity, scripting or rendering prevents or delays the next user action.	Waiting for a page, panel or result to load
Orient	Time during which the user prepares for the next action.	Finding the next control, reviewing the screen, scrolling or moving the pointer toward a target
Act	Time assigned to the primary activity represented by the Story Beat category.	Browsing content, triggering an action, editing a value or remaining idle

Conceptually, each beat is represented as:

Beat category	Wait	Orient	Act
Browse	Technology delay	Preparation	Browsing activity
Trigger	Technology delay	Preparation	Triggering activity
Edit	Technology delay	Preparation	Editing activity
Idle	Technology delay, when present	Transition or preparation, when detected	Idle interval

This breakdown helps distinguish time lost to technology from time spent understanding the interface or completing the task.

Story Beat Attributes

Attribute	Type	Description
`timestamp`	Date and time	Start of the interval represented by the Story Beat
`waitDuration`	Seconds	Time blocked or delayed by page activity such as network requests, JavaScript execution or rendering
`orientDuration`	Seconds	Time spent preparing for the next action, which can include reviewing, scrolling or moving the pointer
`actionDuration`	Seconds	Time assigned to the Story Beat’s primary activity category
`actionCategory`	String	Activity category: `browse`, `trigger`, `edit` or `idle`
`labelHint`	Object	Context collected to help the backend assign functional labels
`label1`–`label5`	String	Hierarchical descriptions of the user’s activity, from most granular to highest-level intent

Attribute names and availability may vary by monitored technology and data model.

Action Categories

Value	Description
`edit`	The user interacts with an input control, such as a text box, list, checkbox or other editable field.
`trigger`	The user selects a link, button or other control that initiates an action.
`browse`	The user primarily reviews content, scrolls or moves the pointer.
`idle`	No user interaction is detected during the interval.

Label Hints

labelHint contains application and interaction context used to create meaningful Story Beat labels. All Story Beats can include:

Attribute	Type	Description
`uiHierarchy`	`String[]`	Current application navigation or view hierarchy at the beginning of the interval
`actionTargets`	`String[]`	Hierarchical description of the elements involved in the action, ordered from general to specific

An action target can contain values such as:

[appletName, formName, fieldName]
[tabName, tableName, buttonLabel]

The corresponding HTML tag can be appended to each target when available.

Hierarchical Labels

Story Beat can assign up to five levels of functional description:

Label	Purpose	Example
`label1`	Most granular description of the immediate activity	Picking a shoe size
`label2`	Groups related low-level actions into a small task	Reviewing size options
`label3`	Describes a broader functional activity	Comparing details across two products
`label4`	Groups activities into a journey stage	Evaluating replacement products
`label5`	Highest-level description of likely intent	Rebuying a larger size of the same shoe just returned

The number and meaning of populated labels depend on the monitored application and available context.

Processing Pipeline

Story Beat is generated through the following process:

Step	Description
Capture activity:	GermainUX records the relevant user, application and technology signals.
Create intervals:	Adjacent activity is divided into Story Beat intervals.
Assign categories:	Each interval is classified as Browse, Trigger, Edit or Idle.
Calculate phases:	Time is divided into Wait, Orient and Act where the required signals are available.
Generate label hints:	Application-specific logic populates `uiHierarchy`, `actionTargets` and other contextual clues.
Consolidate activity:	Story Beats from multiple browser tabs are combined into a user-level stream.
Assign hierarchical labels:	Backend logic populates `label1` through `label5` according to the available heuristics and context.
Backfill intent:	Higher-level labels can be updated when the user’s intent becomes clearer later in the journey.
Group for visualization:	Portlets group adjacent Story Beats when they share the same labels at the selected hierarchy level.

Application-Specific Behavior

The captured attributes, labeling heuristics and processing pipeline can vary by monitored technology. Examples include:

Microsoft applications
Oracle Siebel CRM
Salesforce (CRM, Experience Cloud, etc)
SAP (Commerce Cloud, etc)
Shopify
WordPress
Other supported or custom applications

Application-specific context generally produces more meaningful labels than generic browser activity alone.

Analyze Friction with Story Beat

Story Beat can be combined with other GermainUX analytics to identify:

Excessive Wait time caused by slow technology
Excessive Orient time caused by confusing navigation or design
Repeated Trigger or Edit actions
Unexpected Idle time during a workflow
Journey branches associated with drop-off
Differences between successful and unsuccessful users
Time lost across a business process

Teams can drill from aggregate Story Beat patterns into individual sessions and use Session Replay or technical traces to understand what happened.

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The content of this document is proprietary to GERMAIN SOFTWARE.

Story Beat on a Flow

Wait, Orient and Act

Hierarchical Labels

Analyze Friction with Story Beat

​Overview

​What Story Beat Helps You Understand

​From Click-Level Activity to Functional Insight

​Story Beat on a Flow

​Story Beat on a Focused Flow

​Story Beat Categories

​Wait, Orient and Act

​Story Beat Attributes

​Action Categories

​Label Hints

​Hierarchical Labels

​Processing Pipeline

​Application-Specific Behavior

​Analyze Friction with Story Beat

​Get Help

Contact GermainUX Support

Can't find what you need?

Overview

What Story Beat Helps You Understand

From Click-Level Activity to Functional Insight

Story Beat on a Flow

Story Beat on a Focused Flow

Story Beat Categories

Wait, Orient and Act

Story Beat Attributes

Action Categories

Label Hints

Hierarchical Labels

Processing Pipeline

Application-Specific Behavior

Analyze Friction with Story Beat

Get Help