Groupon, Inc.

Vyomkesh Tripathi

Rajesh Girish Parekh

Nipun Agarwal

Feili Hou

Gaston L'Huillier

Francisco Jose Larrain

Bhupesh Bansal

Raju Balakrishnan

Ricardo Andres Zilleruelo

Kamson Lai

Latife Genc-Kaya

Guoxian Zhang

Rahim Daya

Shi Zhao

Hernan Arroyo

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

Provided herein are systems, methods and computer readable media for facilitating pricing. An example method may include determining a price adjustable promotion from a plurality of promotions, the price adjustable promotion having a first promotional price, a forecasted demand that provides an indication of a promotion inventory exhaustion period and a plurality of redemption parameters that comprise at least a promotional period, a promotional value and a redemption expiration and causing the price adjustable promotion to be offered at the second promotional price while at least one of the plurality of redemption parameters for the price adjustable promotion remain constant.

Method, apparatus, and computer program product for facilitating dynamic pricing

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

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

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Mountain View, CA, United States of America

Vyomkesh Tripathi