How Software Recommends Dashboards Based on What You Click
This patent describes a system that watches how you interact with data dashboards and uses AI to suggest other dashboards you might find useful, making it easier to find the information you need.
Original patent title: “Dashboard usage tracking and generation of dashboard recommendations”
This patent describes a system that watches how you interact with data dashboards and uses AI to suggest other dashboards you might find useful, making it easier to find the information you need. Granted in 2026.
Coverage
What does this patent actually cover?
The patent describes a system that shows a user a 'dashboard interface' on a device. It then 'tracks user inputs' like clicks or searches, both while the dashboard is open and afterwards. Using 'predictive analytics,' which is a type of AI, the system tries to guess what kind of data the user is looking for. It then finds other dashboards that have similar data and 'outputs a recommendation' to the user. For example, if a user frequently clicks on sales figures for a specific region, the system might recommend a dashboard showing detailed marketing spend for that same region.
The gap
What does this patent NOT cover?
- Does not cover systems that recommend individual data points or reports, only entire dashboard interfaces or portions thereof.
- Does not cover generating new dashboards from scratch, only recommending existing ones.
- Does not cover recommendations based solely on explicit user queries or preferences, but rather 'tracked user input patterns'.
- Does not cover systems that do not use predictive analytics to determine the user's predicted data type.
- Does not cover recommending non-dashboard content, such as articles or products.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The noveltynoveltyThe requirement that an invention be different from anything publicly known before its priority date.Read more → lies in combining the tracking of a user's interaction patterns with predictive analytics to infer their current data interest, and then using that inference to recommend entirely different, but related, dashboard interfaces. This moves beyond simple keyword matching to anticipate user needs based on behavior.
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
Microsoft Power BI's suggested content
Tableau's recommendation engine for related dashboards
Google Looker's smart suggestions
Custom business intelligence platforms with AI-driven insights
CRM dashboards with contextual recommendations
Why it matters
The bigger picture
In today's data-rich environments, users often struggle to find the specific information they need within vast collections of dashboards. This patent aims to make data discovery more efficient by intelligently suggesting relevant dashboards. It helps users navigate complex business intelligence systems, reducing the time spent searching and potentially improving the speed and quality of data-driven decisions.
Filed
April 21, 2021
Granted
September 15, 2026
Market context
Who's building on this
Companies in this space
Major business intelligence and data analytics companies are actively developing and integrating recommendation features into their platforms. Companies like Microsoft with Power BI, Salesforce with Tableau, and Google with Looker are continually enhancing how users discover and interact with data. Many enterprise software providers are also incorporating similar intelligent suggestions into their dashboard offerings.
Market impact
This type of technology significantly improves the user experience for data analysis tools, making complex data more accessible and actionable. It helps reduce the learning curve for new users and increases productivity for experienced analysts by streamlining data discovery. The market benefits from more efficient data utilization and potentially faster, more informed decision-making across organizations.
Claim 1 — Plain English
What this patent covers
The patent describes a system that shows a user a 'dashboard interface' on a device. It then 'tracks user inputs' like clicks or searches, both while the dashboard is open and afterwards. Using 'predictive analytics,' which is a type of AI, the system tries to guess what kind of data the user is looking for. It then finds other dashboards that have similar data and 'outputs a recommendation' to the user. For example, if a user frequently clicks on sales figures for a specific region, the system might recommend a dashboard showing detailed marketing spend for that same region.
The clever bit
The novelty lies in combining the tracking of a user's interaction patterns with predictive analytics to infer their current data interest, and then using that inference to recommend entirely different, but related, dashboard interfaces. This moves beyond simple keyword matching to anticipate user needs based on behavior.
What it does not cover
- Does not cover systems that recommend individual data points or reports, only entire dashboard interfaces or portions thereof.
- Does not cover generating new dashboards from scratch, only recommending existing ones.
- Does not cover recommendations based solely on explicit user queries or preferences, but rather 'tracked user input patterns'.
- Does not cover systems that do not use predictive analytics to determine the user's predicted data type.
- Does not cover recommending non-dashboard content, such as articles or products.
Patent timeline
Application submitted to the patent office
Patent officially issued
PatentBrief Score
Impact Score
Early stage
Citation count
0/40
No citations yet
Claim breadth
0/20
Narrow claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
20/20
Granted within 5 years
Assignee scale
0/20
Independent or smaller assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$19K – $61K
Midpoint $38K · 14.5 yr remaining · industry ×1.6
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
Claim text not yet imported for this patent
Concepts involved
Cite this patent
(2026). How Software Recommends Dashboards Based on What You Click (U.S. Patent No. 12,738,365). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/12738365/dashboard-usage-tracking-and-generation-of-dashboard-recommendations
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does How Software Recommends Dashboards Based on What You Click cover?
This patent describes a system that watches how you interact with data dashboards and uses AI to suggest other dashboards you might find useful, making it easier to find the information you need.
When does this patent expire?
This patent is expected to expire on September 15, 2046, when the invention enters the public domain.
What problem does this patent solve?
In today's data-rich environments, users often struggle to find the specific information they need within vast collections of dashboards. This patent aims to make data discovery more efficient by intelligently suggesting relevant dashboards. It helps users navigate complex business intelligence systems, reducing the time spent searching and potentially improving the speed and quality of data-driven decisions.
What does this patent NOT cover?
Does not cover systems that recommend individual data points or reports, only entire dashboard interfaces or portions thereof.
Patent monitoring