Granted Patent B2

US 12,738,365 · App. 17/236,710 · Granted Sep 15, 2026

Inventors: Kimberly S. Dunwoody (Parker, CO); Susan E. Teague Rector (Denver, CO)

Assignee: MONDAY.COM LTD

G16H40/20G06F16/9535G06Q10/00G06Q40/08G06Q50/22G16H10/60

Abstract

Claims (68)

1 . A method, in a data processing system including at least one memory and at least one processor, wherein the at least one memory includes instructions that are executed by the at least one processor to configure the at least one processor to implement the method, the method comprising:

presenting, on a client computing device, a first dashboard providing a graphical user interface to a first user;

tracking user inputs to the client computing device, at least during and after presentation of the first dashboard to the first user, to identify at least one characteristic of the user inputs;

generating predictive analytics by applying logic to: identify and analyze dashboard usage patterns associated with one or more other users that accessed the first dashboard and transitioned from the first dashboard to one or more other dashboards, and interactions of the one or more other users with portions of the one or more other dashboards, and to identify and analyze user characteristics associated with the one or more other users;

applying the predictive analytics to the tracked user inputs to predict a type of data the first user is attempting to access and that is not provided by the first dashboard;

correlating the predicted type of data with the one or more portions of the one or more other dashboards, wherein the one or more portions of the one or more other dashboards provide a representation of data having a type matching the predicted type of data that is not provided by the first dashboard;

outputting a recommendation to the first user via an interactive graphical user interface element indicating the one or more correlated portions of the one or more other dashboards providing the representation of data matching the predicted type of data that is not provided by the first dashboard;

receiving a user selection of the recommendation via the interactive graphical user interface element; and

in response to the user selection, modifying the first dashboard to display the predicted type of data by incorporating into the first dashboard the one or more correlated portions of the one or more other dashboards.

2 . The method of claim 1 , wherein presenting the first dashboard comprises:

Receiving input data from one or more source computing systems via one or more data networks;

analyzing the input data to generate analytics results data; and

generating-the first dashboard by populating portions of a dashboard data structure with corresponding portions of the analytics results data to generate a plurality of data representations within the first dashboard.

3 . The method of claim 1 , wherein tracking user inputs to the client computing device comprises tracking user inputs to user interface elements of the first dashboard and tracking user inputs to at least one other user experience system providing another user interface for accessing content or exchanging information with another user.

4 . The method of claim 3 , wherein the at least one other user experience system comprises at least one of a search engine user interface or an electronic messaging user interface.

5 . The method of claim 4 , wherein tracking user inputs to the at least one other user experience system comprises extracting key terms or key phrases entered by the first user into the search engine user interface or electronic messaging user interface, and wherein correlating the predicted type of data with the one or more portions of the one or more other dashboards comprises searching metadata associated with the one or more other dashboards based on the extracted identified key terms or key phrases to identify the one or more other dashboards as having at least one matching key term or key phrase in the metadata as the extracted key terms or key phrases.

6 . The method of claim 1 , wherein the outputting the recommendation to the first user comprises outputting a portion of the first dashboard or another user interface having user selectable links that, when selected by the first user, access a corresponding one of the one or more other dashboards.

7 . The method of claim 1 , further comprising:

storing, for the first dashboard, tracked usage metrics based on tracking the user inputs to the client computing device cumulatively with other user inputs to the first dashboard;

generating a dashboard recommendation based on the cumulatively stored tracked usage metrics; and

outputting the dashboard recommendation to a system administrator.

8 . The method of claim 1 , wherein correlating the predicted type of data with one or more portions of one or more other dashboards comprises:

creating a cluster of the one or more other users having at least one matching characteristic to the first user based on the analyzed user characteristics associated with the one or more other users; and

generating the recommendation based on the one or more other dashboards accessed by at least some of the users in the cluster.

9 . The method of claim 8 , wherein generating the recommendation based on the one or more other dashboards accessed by at least some of the users in the cluster comprises:

identifying at least one of the one or more other dashboards accessed by the at least some of the users in the cluster which provides a representation of data having a type matching the predicted type of data, and which has not been previously accessed by the first user during a current user session.

10 . The method of claim 1 , wherein the identified at least one characteristic includes at least one key text portion extracted from a text input of the user inputs, and wherein the correlating the predicted type of data with one or more portions of one or more other dashboards further comprises performing a search of metadata of a plurality of dashboards based on the extracted key text portion and selecting the one or more other dashboards based on a matching of the key text portion with content in metadata associated with the one or more other dashboards.

11 . The method of claim 1 , wherein one or more of: the first dashboard; or the one or more other dashboards, are predefined.

12 . The method of claim 1 , wherein the recommendation is displayed in the first dashboard or as a pop-up window.

13 . The method of claim 1 , wherein the recommendation is stored in the at least one memory as user characteristic information associated with the first user.

14 . The method of claim 1 , wherein the dashboard usage patterns are identified based on at least a threshold number of the one or more other users that accessed the first dashboard and transitioned from the first dashboard to the one or more other dashboards.

15 . A computer program product including a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to:

present, on a client computing device, a first dashboard providing a graphical user interface to a first user;

track user inputs to the client computing device, at least during and after presentation of the first dashboard to the first user, to identify at least one characteristic of the user inputs;

generate predictive analytics by applying logic to: identify and analyze dashboard usage patterns associated with one or more other users that accessed the first dashboard and transitioned from the first dashboard to one or more other dashboards, and interactions of the one or more other users with portions of the one or more other dashboards, and to identify and analyze user characteristics associated with the one or more other users;

apply the predictive analytics to the tracked user inputs to predict a type of data the first user is attempting to access and that is not provided by the first dashboard;

correlate the predicted type of data with the one or more portions of the one or more other dashboards, wherein the one or more portions of the one or more other dashboards provide a representation of data having a type matching the predicted type of data that is not provided by the first dashboard;

output a recommendation to the first user via an interactive graphical user interface element indicating the one or more correlated portions of the one or more other dashboards providing the representation of data matching the predicted type of data that is not provided by the first dashboard;

receive a user selection of the recommendation via the interactive graphical user interface element; and

in response to the user selection, modify the first dashboard to display the predicted type of data by incorporating into the first dashboard the one or more correlated portions of the one or more other dashboards.

16 . The computer program product of claim 15 , wherein the computer readable program causes the computing device to present the first dashboard at least by:

receiving input data from one or more source computing systems via one or more data networks;

analyzing the input data to generate analytics results data; and

generating the first dashboard by populating portions of a dashboard data structure with corresponding portions of the analytics results data to generate a plurality of data representations within the first dashboard.

17 . The computer program product of claim 15 , wherein the computer readable program causes the computing device to track user inputs to the client computing device at least by tracking user inputs to user interface elements of the first dashboard and tracking user inputs to at least one other user experience system providing another user interface for accessing content or exchanging information with another user.

18 . The computer program product of claim 17 , wherein the at least one other user experience system comprises at least one of a search engine user interface or an electronic messaging user interface.

19 . The computer program product of claim 18 , wherein the computer readable program causes the computing device to track user inputs to the at least one other user experience system at least by extracting key terms or key phrases entered by the first user into the search engine user interface or electronic messaging user interface, and wherein the computer readable program causes the computing device to correlate the predicted type of data with the one or more portions of the one or more other dashboards at least by searching metadata associated with the one or more other dashboards based on the extracted key terms or key phrases to identify the one or more other dashboards as having at least one matching key term or key phrase in the metadata as the extracted key terms or key phrases.

20 . The computer program product of claim 15 , wherein the computer readable program further causes the computing device to:

store, for the first dashboard, tracked usage metrics based on tracking the user inputs to the client computing device cumulatively with other user inputs to the first dashboard;

generate a dashboard recommendation based on the cumulatively stored tracked usage metrics; and

output the dashboard recommendation to a system administrator.

21 . The computer program product of claim 15 , wherein the computer readable program causes the computing device to correlate the predicted type of data with one or more portions of one or more other second dashboards at least by:

creating a cluster of the one or more other users having at least one matching characteristic to the first user based on the analyzed user characteristics associated with the one or more other users; and

generating the recommendation based on the one or more other dashboards accessed by at least some of the users in the cluster.

22 . The computer program product of claim 21 , wherein the computer readable program causes the computing device to generate the recommendation based on the one or more other dashboards accessed by the at least some of the users in the cluster at least by:

identifying at least one of the one or more other dashboards accessed by the at least some of the users in the cluster which provides a representation of data having a type matching the predicted type of data, and which has not been previously accessed by the first user during a current user session.

23 . The computer program product of claim 15 , wherein the identified at least one characteristic includes at least one key text portion extracted from a text input of the user inputs, and wherein the correlating the predicted type of data with one or more portions of one or more other dashboards further comprises performing a search of metadata of a plurality of dashboards based on the extracted key text portion and selecting the one or more dashboards based on a matching of the key text portion with content in metadata associated with the one or more other dashboards.

24 . An apparatus comprising:

a processor; and

a memory coupled to the processor, wherein the memory includes instructions which, when executed by the processor, cause the processor to:

present, on a client computing device, a first dashboard providing a graphical user interface to a first user;

track user inputs to the client computing device, at least during and after presentation of the first dashboard to the first user, to identify at least one characteristic of the user inputs;

generate predictive analytics by applying logic to: identify and analyze dashboard usage patterns associated with one or more other users that accessed the first dashboard and transitioned from the first dashboard to one or more other dashboards, and interactions of the one or more other users with portions of the one or more other dashboards, and to identify and analyze user characteristics associated with the one or more other users;

apply predictive analytics to the tracked user inputs to predict a type of data the first user is attempting to access and that is not provided by the first dashboard;

correlate the predicted type of data with the one or more portions of the one or more other dashboards, wherein the one or more portions of the one or more other dashboards provide a representation of data having a type matching the predicted type of data that is not provided by the first dashboard;

output a recommendation to the first user via an interactive graphical user interface element indicating the one or more correlated portions of the one or more other dashboards providing the representation of data matching the predicted type of data that is not provided by the first dashboard;

receive a user selection of the recommendation via the interactive graphical user interface element; and

in response to the user selection, modify the first dashboard to display the predicted type of data by incorporating into the first dashboard the one or more correlated portions of from the one or more other dashboards.

Assignments (2)

Continuity (2)

References Cited (400)