Oracle International Corporation

John Benjamin Nolt

Michael James Strutton

Chad Estes

Horace Williams, Ii

John Schult

Jason C Reynolds

Benjamin Turner

John Maxwell

Paulo Delgado

Bryan S Pocius

Slain J Wilde

Wenhua Li

Tara U Roberts

Natalie You

Yizhou Jiang

Kimberly Ann Wolfe

James V Anderson

Andrei Erdoss

Brian Culler

Wenchang Yan

Sriti Kumar

Robert M Maury

Paul M Broft

Maria F Arscott

Nancy M Lim

Joe Kearney

Melinda M Weathers

Erica M Stanley

Geoffrey Hom

Gregory K Dunn

Matt White

Reginald R Bradford

Andrew Robert Dorr

Systems and methods for delivering application media content to multiple social media systems (SMSs) for display to SMS members. The method includes the steps of providing initial application media content to respective SMSs. Once a respective SMS member interacts with the initial content, a social relationship management system (SRMS) receives indication from an SMS of such interaction, and retrieves a unique application media file relating to application media content. The unique application media file is then applied to an application media container file that overcomes certain formatting protocols and requirements of the SMS and enables transmission and delivery of the application media content to the SMS. The application media content is then delivered to the SMS member on the SMS through the application media container file.

Systems and methods for creating and inserting application media content into social media system displays

Techniques for using machine learning to configure social media campaigns are disclosed. A social relationship management (SRM) service performs supervised machine learning to generate a learned model, at least by: generating feature vectors based on training data including campaign configuration data and one or more campaign success metrics; and performing pattern recognition on the feature vectors to determine one or more preferred campaign configurations. The SRM service publishes messages to one or more social media platforms and receives user interaction data associated with users' interactions with the messages. The SRM service performs unsupervised machine learning to update the learned model based at least in part on the user interaction data. The SRM service receives a request to configure a social media campaign, applies data associated with the request to the learned model to determine a preferred campaign configuration, and configures the social media campaign based on the preferred campaign configuration.

Machine learning system for configuring social media campaigns

Disclosed is a system, method, and computer program product for implementing a marketing automation tool that provides an improved approach for an integrated and/or customized workspace for a social relationship management system. The present invention provides a mechanism to allow the user of a SRM system to configure a workspace for the SRM product, to choose the specific functionality from the SRM suite to be displayed and executed for the user and to post a message while simultaneously viewing the workspace.

Method and system for implementing a custom workspace for a social relationship management system

Systems and methods for evaluating the effectiveness of social media pages. Users of social media systems review and publish various kinds of content on social media pages, including various messages, audio clips, video clips, polls, web links, etc. A social media page evaluation system hosted on a physical server or a cloud receives a social media page that is to be evaluated, and provides results of an evaluation process. The evaluation process involves processing of various criteria and parameters that characterize engagements and interactions between users of social media pages. Results of an evaluation process include qualitative and quantitative attributes in connection with evaluating the effectiveness of published content on social media pages. Such results are useful for purposes of enriching content in social media pages, resulting in greater network traffic due to increased engagements and interaction among users of social media pages.

Systems and methods for determining value of social media pages

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Atlanta, GA, United States of America

John Benjamin Nolt