Retailmenot, Inc.

Shaun Dubuque

Aaron Dragushan

Nicholas James Shiffert

Jeffrey Ryan Rego

J Seth Randle

Alexander M Cheng

Joe Kendall

Vivek Sagi

Nicholas J Shiffert

Disclosed are techniques for achieving high-volumes of low-latency price plus discount transactions that are dynamically created through transaction optimization. Aspects may include combining and optimizing different types of discounts into a single discount and dynamically controlling the single discount through a single user-facing transaction. A computer model may determine one or more transactions and sets of discounts applicable to those transactions upon which the user-facing transaction and single discount are based. Associations between discounts and items may be determined for at least some different types of discounts to apply a set of discounts including at least two different discounts of different discount types to a desired transaction for one or more items. Aspects may include determining a discount transaction comprising a plurality of constituent transactions that form a single user-facing transaction.

Predictive bounding of combinatorial optimizations that are based on data sets acquired post-prediction through high-latency, heterogenous interfaces

Provided is a process including: determining that a mobile computing device has crossed a geofence associated with a merchant store; sending, to a remote classifier server, a request for object-recognition classifiers for objects in the merchant store; receiving a set of object-recognition classifiers; receiving with the mobile computing device from user a request to search for offers; capturing an image with a camera of the mobile computing device; receiving one or more wireless beacon identifiers with the mobile computing device; based on the wireless beacon identifiers, selecting a subset of the object-recognition classifiers in the set of object-recognition classifiers; and recognizing an object in the captured image based on the selected subset of the object-recognition classifiers; and requesting, from a remote offer publisher server, offers corresponding to the recognized object; and receiving offers from the remote offer publisher server; and displaying the received offers to the user.

Reducing the search space for recognition of objects in an image based on wireless signals

Provided is a process of classifying ambient signals to reduce fraudulent use of information, the process including: receiving, with the mobile computing device, from a remote server, balance-access information by which a stored value card balance can be spent at a point of sale terminal; storing, with the mobile computing device, the balance-access information; sensing, with one or more sensors of a mobile computing device, ambient signals; classifying the ambient signals as indicating the user is in a retail establishment; and in response to the classification, displaying, on a display screen of the mobile computing device, the balance-access information, such that the balance-access information can be input to a point-of-sale terminal.

Modulating mobile-device displays based on ambient signals to reduce the likelihood of fraud

Provided is a process, including: obtaining, in memory of a first mobile computing device, a plurality of content items, at least some of the content items pertaining to respective different geographic areas; receiving, with the first mobile computing device, data indicating a user interaction with a given content item among the plurality of the content items; and in response to receiving the data indicative of the user interaction, transmitting a wireless signal from the first mobile computing device directly to a second mobile computing device that is different from the first mobile computing device, the wireless signal being indicative of the given content item and indicating that the given content item pertains to a given geographic area within range of the wireless signal transmission.

Peer-to-peer geotargeting content with AD-HOC mesh networks

Provided is a process including: receiving a stored value card from a first computing device and a first geolocation of the first computing device, the first computing device having balance access information of the stored value card; receiving a request for a stored value card from a second computing device at a second geolocation; determining to not send the stored value card to the second computing device as a result of the second geolocation being within a threshold geographic distance to the first geolocation; receiving another request for a stored value card from a third computing device at a third geolocation; and determining to send the stored value card to the third computing device as a result of the third geolocation not being within the threshold geographic distance to the first geolocation; and sending balance-access information of the stored value card to the third computing device.

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Austin, TX, United States of America

Shaun Dubuque