Groupon, Inc.

Yahoo! Inc.

Bytedance Inc.

Data General Corporation

Rajesh Girish Parekh

Shafiq Shariff

Nipun Agarwal

Raju Balakrishnan

Feili Hou

Vyomkesh Tripathi

Guoxian Zhang

Gaston L'Huillier

Kavita Kochar

Logan Tyler Jennings

Mechie Nkengla

Pavel Berkhin

Ying Chen

Prashant Gaurav

Bob Beaty

Jignashu Parikh

Zahra Ferdowsi

Angela Han

Riva Ashley Vanderveld

Andrew Stephen Tomkins

Boris Klots

Shawn Ryan Jeffery

Derek Nordquist

Narayan Lakshmi Bhamidipati

Usama M Fayyad

Richard Tao-Hwa Chow

Elena Eneva

Nicolas Eddy Mayoraz

Scott J Gaffney

Mark Bennett Hecker

Suju Rajan

Robert N Murdoch

Adwait Ratnaparkhi

Dragomir Dimitrov Yankov

Matt DeLand

Brian Mullins

Kris Urie

Bassel Ojjeh

Nabil Takla

Jignesh Parmar

David Wellspring Sculley, Ii

Raymond Chu

Michael Busch

Systems, apparatus, methods, and computer program products are provided for optimized and effective leading messages, which may be an email subject that may provoke a consumer to access the body portion of an email message. A system may include circuitry configured to programmatically determine a predicted access rate for a leading message when the leading message is provided as a portion of a promotional message. Circuitry may be configured to track historical data indicating the access rates of leading messages and/or leading message terms. The circuitry may be configured to leverage the historical data to determine predicted access rates for leading messages, such as based at least in part on historical access rates associated with one or more leading message terms of the leading message.

Systems and methods for providing optimized leading messages

Embodiments provide methods, systems, apparatuses, and computer program products for predicting behavior. An example method includes determining a classification for a first consumer, where the classification is based on a measure of frequency of purchases by the first consumer; identifying one or more first attributes for the first consumer based on the determined classification, the one or more attributes being attributes selected for predicting the respective one or more metric associated with the first consumer; and determining, based on values for the one or more first attributes, a first prediction value that indicates a programmatically expected number of purchases by the first consumer.

Method, apparatus, and computer program product for predicting consumer behavior

The present disclosure relates to methods, systems, and apparatuses for providing electronic communications to client devices based on clustering and filtering candidates for inclusion in the electronic communications based on programmatically generated correlation metrics and thresholds associated with the clustering.

Method and apparatus for providing electronic communications

In general, embodiments of the present invention provide systems, methods and computer readable media for recommending contextually relevant promotions to consumers in order to facilitate their discovery of promotions that they are likely to purchase from a promotion and marketing service.

Generating optimized in-channel and cross-channel promotion recommendations using free shipping qualifier

A method, apparatus, and computer program product are disclosed for improved machine learning using a statistical model. In the context of an apparatus, some example embodiments include a processor configured to cause retrieval of information regarding a plurality of consumers, and modeling circuitry configured to train a statistical model of the plurality of consumers based on the retrieved information, and predict, using the statistical model, an incremental booking value associated with the promotion for each consumer of the plurality of consumers. The processor is further configured to select a subset of the plurality of consumers for receiving impressions of the promotion. Some example embodiments may further include communications circuitry configured to transmit an impression of the promotion to each consumer in the subset of the plurality of consumers.

Apparatus and method for enhanced message targeting

Embodiments of the present invention provide methods, systems, apparatuses, and computer program products for predicting consumer behavior. In one embodiment a method is provided comprising determining a classification for a first consumer, wherein the classification is based on a measure of frequency of purchases by the first consumer; identifying one or more first attributes for the first consumer based on the determined classification, the one or more attributes being attributes selected for predicting the respective one or more metric associated with the first consumer; and determining, based on values for the one or more first attributes, a first prediction value that indicates a programmatically expected number of purchases by the first consumer.

Certain embodiments provide a computer-executed method for generating a future sales estimate for an item. The method includes programmatically accessing, from a dataset via a network device, an inventory residence time period of an item. The method also includes programmatically accessing, from the dataset via the network device, prior performance data associated with the item. The method also includes programmatically executing an inventory valuation engine to generate a future sales estimate for the item based on the inventory residence time period and the prior performance data. The method further includes executing a notification generation engine to adjust a notification policy defining a frequency or other characteristic of electronic marketing communications indicating the item transmitted to consumer devices based on the future sales estimate.

Computer system and computer-executed method for inventory valuation

Generating in-channel and cross-channel promotion recommendations using promotion cross-sell

Systems and methods for providing optimized leading messages in an email subject

Embodiments provide a computer-executable method, computer system and non-transitory computer-readable medium for programmatically generating an association among two or more purchase categories based on purchase data of a plurality of consumers. The method includes programmatically accessing, from a dataset via a network device, prior purchase data associated with purchases of a plurality of commercial objects by a plurality of consumers. The method also includes programmatically identifying a plurality of categories associated with the plurality of commercial objects. The method also includes, for each consumer in the plurality of consumers, programmatically generating a total number of purchases by the consumer in each category in the plurality of categories. The method further includes generating, using a processor of a computing device, a category association score between each pair of categories in the plurality of categories by programmatically analyzing similarities among the total numbers of purchases in the plurality of categories for the plurality of consumers.

Method and system for generating purchase recommendations based on purchase category associations

A method, apparatus and computer program product are provided for generation of analytic data. An example embodiment includes a method for identifying trending items based on electronically generated velocity metrics derived from transaction data. The method includes performing at least one electronic transaction between a consumer and the promotion and marketing service to offer, via the electronic transaction, at least one promotion to the consumer, storing a set of transaction data in a memory, the set of transaction data comprising electronic data indicating the at least one transaction, determining, via processing circuitry, one or more velocity metrics for a plurality of promotions from the set of transaction data, determining at least one trending promotion from the plurality of promotions based on the velocity metrics, generating, via the processing circuitry, an electronic communication comprising the at least one trending promotion, and transmitting, via communications circuitry, the electronic communication.

Method and apparatus for identifying trending promotions

Provided herein are systems, methods and computer readable media for forecasting demand. An example method comprises generating a virtual offer for one or more combinations of a category or sub-category, location, and price range, accessing consumer data comprising one or more users and user data related to each of the one or more users, calculating a probability that a particular user would buy a particular offer in a particular time frame for at least a portion of the plurality of users and for each of the virtual offers, and determining an estimated number of units of to be sold for at least a portion of the one or more virtual offers as a function of at least the probability associated with each of the one or more virtual offers.

Method, apparatus, and computer program product for forecasting demand

A method, apparatus, and computer program product are disclosed for improved promotion targeting. An example apparatus includes a processor configured to cause retrieval of historical information regarding transactions associated with a plurality of identifier entities. The example apparatus further includes modeling circuitry configured to train a statistical model using the retrieved historical information, and estimate, using the statistical model, values for expected identifier entity transaction requests associated with each of the plurality of identifier entities. The processor of the example apparatus may further be configured to select, based on the estimated values, a subset of identifier entities to receive impressions of the promotion, and the apparatus may further include communications circuitry configured to transmit an impression of the promotion to each identifier entity in the subset.

Growing community of inventors

San Jose, CA, United States of America

Rajesh Girish Parekh