Groupon, Inc.

Sebastian Kreft

Gaston L'Huillier

Francisco Jose Larrain

Evan MacMillan

Ricardo Andres Zilleruelo

The email suggestor system and method provide an efficient and effective way to capture a user identifier, such as an email address of a consumer in a retail environment. The email suggestor system generates one or more suggested first text portions based on input data, outputs at least one of the suggested first text portions, and receives a selection of a first text portion. The email suggestor system generates one or more suggested second text portions of a user identifier based on the input data, outputs at least one of the suggested second text portions, and receives a selection of a second text portion. The email suggestor system generates a user identifier including the selected first text portion and the selected second text portion. The email suggestor system uses received feedback response to refine and/or train one or more models with which it generates the suggested text portions.

System for determining consumer identification information at a point-of-sale

Various methods are provided for determining transactional networks using transactional data. One example method may comprise receiving a set of transactional data associated each of a plurality of customers, the set of the transactional data comprising a plurality of ordered lists of elements, each ordered list of elements defining a transaction of a plurality of transactions, the ordered list of elements comprising information identifying a particular customer from the plurality of customers, a merchant, and a timestamp, for each particular customer from the plurality of customers, generating a network, each generated network comprising one or more merchant nodes, a plurality of customer nodes, one or more merchant-customer edges between at least one of the one or more merchant nodes and at least one of the plurality of customer nodes, and one or more customer-customer edges between two or more customer nodes.

Determining transactional networks using transactional data

Email suggestor system

The early adopters and potential influencers (EAPI) system, method and computer-readable medium provide a way to identify early adopters and potential influencers. The EAPI system obtains a list of purchases for customers of merchants and/or subscriptions from a transaction tracking system. The EAPI system creates a time-based transaction network, and using a scoring function, the EAPI system determines an early adopter and/or potential influencer ranking among customers in the network. The EAPI system may use one or more customer attributes to determine a customer's influence with respect to different dimensions.

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San Francisco, CA, United States of America

Sebastian Kreft