Jorge Ivan Jimenez

US Patent:

20210075752, Mar 11, 2021

Filed:

Sep 10, 2019

Appl. No.:

16/566116

Inventors:

- San Francisco CA, US
Jorge Jimenez - San Francisco CA, US
Sandy Yu - Millbrae CA, US

International Classification:

H04L 12/58
G06N 20/00
G06Q 10/10

Abstract:

The present invention comprises a feedback-driven enterprise communications platform that continuously monitors and improves the effectiveness of communications within and across organizations. In one embodiment, it employs supervised machine learning techniques to correlate the attributes of such communications (e.g., topic, purpose, sentiment, authors, target audience, title and body length, publication date and time, inclusion of images, video and other media, as well as various other characteristics) with metrics representing the behavioral interactions with such communications by dynamically changing target audiences. The present invention utilizes such correlations to optimize predefined communications-related goals (defined as functions of such metrics) by generating advice (e.g., in the form of ranges of attribute values) designed to improve over time the two-way dialogue between the authors of communications and their dynamically changing target audiences. Such advice is segmented across one or more dimensions (e.g., different authors, departments or other audience segments, communication types, time periods, etc.).