Salesforce Com, Inc.

Mindjet LLC

Leslie Fine

Vitaly Gordon

Shubha Umesh Nabar

Matthew John Fogarty

Leah McGuire

Brian Brechbuhl

Rick Munoz

Nanahari Phatak

Xiuchai (Meko) Xu

John Grotland

A method for improving mass messaging in an electronic messaging system includes receiving recipient data describing a response of each of one or more recipients to receiving a prior message, generating predictor data based on the recipient data, where the predictor data indicates a plurality of predictors of recipient behavior in response to a message, identifying one or more top predictors of recipient behavior, the one or more top predictors being selected from among the plurality of predictors based on preferred recipient behaviors, generating, for each of the one or more recipients and from the recipient data, one or more predictive scores for each combination of top predictor and recipient, and assigning, based on one or more predictive scores of a specific recipient, the specific recipient to a specific persona, wherein the specific persona describes an expected behavior of the recipient.

Predictive scoring and messaging in messaging systems

The present disclosure provides a system that implements a prediction market, used for making forecasts and, more particularly, for extracting participant utility. One or more forecasts of a specific participant or subset of participants are taken, and a measure of divergence of these forecasts from a group as a whole (or for that matter, any group) is calculated. This divergence may then later be employed in the prediction market (e.g., for present or future forecasting). For example, if it is known that 'sales managers' are consistently too liberal in forecasting product release dates than others within a company, this tendency may be compensated for or used in a variety of manners, such as automatically correcting predictions or forecasts for perceived error, automatically discarding or modifying predictions, or automatically generating 'virtual' predictions for future events. Other actions may also be taken.

Participant utility extraction for prediction market based on region of difference between probability functions

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San Francisco, CA, United States of America

Leslie Fine