公开(公告)号：US11935080B2

公开(公告)日：2024-03-19

申请号：US16816730

申请日：2020-03-12

Applicant: ADOBE INC.

Inventor： John Bevil Bates ,  Ryan Elliott Cobourn ,  Benjamin Russell Gaines ,  Brooke Suzanne Wyckoff

IPC: G06Q30/0204 ,  G06F16/951 ,  G06Q10/067 ,  G06N20/00

CPC classification number: G06Q30/0204 ,  G06F16/951 ,  G06Q10/067 ,  G06N20/00

Abstract: Embodiments of the present invention relate to providing intelligent alerting and automation for marketing analytics software. In implementation, intelligent alerting is initiated by a user, which enables deep learning models to analyze various data patterns. Intelligent alerting learns about preferences and data consumption patterns of the user with marketing analytics software. Intelligent alerting also accounts for and learns from any manually created alerts set up by the user and/or alerts created automatically by anomaly detection. Intelligent alerting analyzes all other users within the organization of the user to find similar users based on their consumption patterns. An on-demand game may be provided to the user to determine the criticality of one metric change over another. This enables intelligent alerting to automatically provide alerts which pass a critical threshold of importance to the user and context to help the user understand why a metric changes in a significant way.

公开(公告)号：US20200211039A1

公开(公告)日：2020-07-02

申请号：US16816730

申请日：2020-03-12

Applicant: ADOBE INC.

Inventor： John Bevil Bates ,  Ryan Elliott Cobourn ,  Benjamin Russell Gaines ,  Brooke Suzanne Wyckoff

IPC: G06Q30/02 ,  G06F16/951 ,  G06N20/00 ,  G06Q10/06

Abstract: Embodiments of the present invention relate to providing intelligent alerting and automation for marketing analytics software. In implementation, intelligent alerting is initiated by a user, which enables deep learning models to analyze various data patterns. Intelligent alerting learns about preferences and data consumption patterns of the user with marketing analytics software. Intelligent alerting also accounts for and learns from any manually created alerts set up by the user and/or alerts created automatically by anomaly detection. Intelligent alerting analyzes all other users within the organization of the user to find similar users based on their consumption patterns. An on-demand game may be provided to the user to determine the criticality of one metric change over another. This enables intelligent alerting to automatically provide alerts which pass a critical threshold of importance to the user and context to help the user understand why a metric changes in a significant way.