Insight Engine Automation for Role-Tailored Dashboard Recommendations
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Solution Overview
Problem
Users struggle to identify and address insights in large volumes of dispersed data across multiple platforms and repositories, often lacking a relevant viewpoint tailored to their role, and face challenges in formatting data for easy consumption.
Innovation Solution
An insight engine generates user-directed insights based on usage tracking information, including user-based parameters, followed by a recommendation engine providing tailored recommendations and dashboard profiles or components to address the identified insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually gather and analyze data from multiple platforms and repositories, then they can identify insights, but the process becomes time-consuming and costly
Solution Approach 1:
The system performs self-service by automatically gathering usage tracking information, generating user-directed insights, and creating dashboard recommendations without requiring manual user intervention. The insight engine autonomously analyzes data from multiple platforms and repositories, identifying insights and formatting them into actionable recommendations with associated dashboards.
Solution Approach 2:
The patent introduces an intermediary system comprising an insight engine and recommendation engine that mediates between raw dispersed data and the user. This intermediary automatically processes usage tracking information, generates insights tailored to the user's role and preferences, and presents formatted recommendations with dashboard profiles, eliminating the need for users to manually navigate multiple platforms.
2Quantity of substance
If data is dispersed across multiple platforms and repositories, then comprehensive information is available, but it becomes difficult for users to cohesively view and appreciate larger trends
Solution Approach 1:
The system merges dispersed data from multiple platforms and repositories into a unified analysis framework. The insight engine consolidates usage tracking information across different data sources, combining them into cohesive user-directed insights and dashboard recommendations that present larger trends in an integrated manner.
Solution Approach 2:
The patent creates a universal system that handles multiple data sources and formats through a single multi-functional platform. The insight engine and recommendation engine can process usage tracking information from various platforms and repositories, generating unified insights and dashboard profiles that work across different data types and sources.
3Adaptability or versatility
If insights are not tailored to the user's role or position, then broader observations can be made, but the insights become less relevant to the user
Solution Approach 1:
The system applies local quality by tailoring insights to the specific user's role, position, and preferences. The insight engine generates user-directed insights that are customized to each user's context, and the recommendation engine further personalizes recommendations based on user-specific parameters, ensuring that the information is locally optimized for each user's needs.
Solution Approach 2:
The patent implements preliminary action by pre-filtering and personalizing insights before they are presented to the user. The system uses user-based parameters and usage tracking information to pre-process data and generate insights that are already tailored to the user's role and preferences, eliminating the need for users to manually filter or adapt the information.
4Ease of operation
If users format data into dashboards manually, then data can be presented in an easily digestible manner, but the process becomes time-intensive
Solution Approach 1:
The recommendation engine performs self-service by automatically generating dashboard profiles and recommendations based on user-directed insights. The system autonomously formats data into easily digestible dashboard presentations without requiring manual user intervention, maintaining both ease of operation and high productivity.
Solution Approach 2:
The system performs preliminary action by pre-formating insights into dashboard profiles before they are presented to the user. The recommendation engine prepares the data in an easily digestible format in advance, so when users receive recommendations, they are already formatted for optimal presentation and consumption.
Data Source
AI summary
Systems and methods for providing autonomous user-directed insights and recommendations are provided herein. For example, a system includes a non-transitory computer-readable medium and a processor communicatively coupled to the non-transitory computer-readable medium. The processor is configured to execute processor-executable instructions to determine, by an insight engine, first usage tracking information associated with a first client device and generate, by the insight engine, a user-directed insight based on the first usage tracking information associated with the first client device. The user-directed insight includes a natural language insight. The processor is also configured to execute processor-executable instructions to generate, by a recommendation engine, recommendations based on the user-directed insight and the first usage tracking information, where each of the recommendations includes a recommendation response and one of a recommendation for a dashboard profile corresponding to the user-directed insight or a recommendation for creating a dashboard corresponding to the user-directed insight.