Interactive Dashboard Data Tours From Recorded User Actions
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Solution Overview
Problem
Existing dashboard guidance strategies are often static and burdensome to maintain, particularly for large-scale dashboards with diverse user bases, leading to guidance that is frequently ignored or not engaging.
Innovation Solution
A system and method for creating interactive data tours using generative artificial intelligence, allowing dashboard authors to record user interactions, generate explanatory titles and descriptions, and edit step-by-step guides to enhance user understanding and engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If static documentation is used for dashboard guidance, then authoring time is reduced, but user engagement and comprehension deteriorate
Solution Approach 1:
The patent transforms static documentation into dynamic interactive data tours that automatically execute and demonstrate dashboard functionalities. The system captures dashboard state changes and user interactions to generate step-by-step guided tours that adapt to different user needs, making guidance both time-efficient to author and highly engaging for users.
Solution Approach 2:
The system creates automated copies of actual dashboard usage scenarios by recording and replaying user interactions. These captured interactions are transformed into reusable guided tour templates that can be automatically generated and updated, eliminating manual documentation while preserving authentic usage patterns that engage users.
2Ease of operation
If interactive data tours are created manually, then user engagement improves, but authoring time and complexity increase
Solution Approach 1:
The system enables self-service automated generation of interactive data tours by capturing dashboard interactions and automatically converting them into guided tour formats. Authors simply need to define the dashboard scope, and the system autonomously records user interactions, generates explanatory content, and assembles complete interactive tours without manual scripting or documentation effort.
Solution Approach 2:
The system performs preliminary actions by pre-capturing and storing dashboard interaction patterns, component hierarchies, and state transitions. This pre-processing enables rapid generation of interactive tours when needed, as the foundational data about dashboard structure and usage patterns is already available, eliminating time-consuming manual authoring during deployment.
3Reliability
If dashboards are updated frequently, then data relevance improves, but guidance maintenance burden increases
Solution Approach 1:
The system implements feedback mechanisms that automatically detect changes in dashboard structure, components, and data. When dashboards are updated, the system monitors for modifications and triggers automatic regeneration of affected guided tours, ensuring guidance remains synchronized with current dashboard states without requiring manual intervention to maintain relevance.
Solution Approach 2:
The system creates automated copies of dashboard states and interactions that can be independently updated. When the underlying dashboard changes, the guidance system generates updated versions by replaying captured interaction patterns against the new dashboard state, maintaining accurate guidance copies that reflect current functionality without manual rewriting.
4Loss of information
If comprehensive guidance is provided for all dashboard components, then user understanding improves, but guidance complexity and length increase
Solution Approach 1:
The system segments comprehensive dashboard guidance into discrete, modular steps that correspond to specific user actions and dashboard components. Each step is independently authored and can be selectively executed based on user needs, allowing comprehensive coverage of all components while presenting information in manageable, non-overwhelming segments that reduce perceived complexity.
Solution Approach 2:
The system applies local quality by providing detailed, context-specific guidance only where and when users need it during dashboard interaction. Rather than presenting uniform comprehensive documentation, the system delivers targeted explanations for specific components and actions based on user behavior patterns, maintaining thorough understanding support while minimizing overall guidance complexity through contextual relevance.
Data Source
AI summary
A computer-implemented method can be used for creating and presenting interactive data tours for dashboards. The computer receives a communication intent for a data tour of a dashboard, records user interactions with components of the dashboard and generates steps for the data tour based on the recorded user interactions. The computer also generates (e.g., using a Large Language Model) an explanatory title and a description based on linked dashboard components and the communication intent, for each steps. The computer also presents an interface for editing the data tour, receives edits to the data tour, and stores the edited tour. In response to a request to play the data tour, the computer presents the data tour as an interactive step-by-step guide overlaid on the dashboard, including replaying the specific user interactions relevant to each step on the linked dashboard components, and displaying the explanatory title and short description as text overlays.