Groupon, Inc.

Bytedance Inc.

Tihomir Tsankov Georgiev

David Gomez-Rosado

Robert James Skillington

Geoffrey Hubert Woo

Michael Chen

Mahmudul Arefin Din

Sri Viswanath

Andrey Zaytsev

David Scott Parker

Seth Harris

Qi Li

Josh Krall

Travis Chow

Samuel Thorpe

Clive Richard Beavis

Gabe Nydick

Rishi R Arora

Alan Deitch

Systems, apparatus, methods, and non-transitory media for providing prescient and adaptive point-of-sale services via electronic networks are discussed herein. Some embodiments may include a system with one or more servers. The one or more servers may be configured to generate digital consumer tokens and provide the digital consumer tokens to consumer devices for sharing with merchant devices. When a merchant device receives the digital consumer token, the merchant device may forward the digital consumer token to the one or more servers in exchange for consumer data to facilitate consumer service. In some embodiments, the one or more servers may be configured to provide point-of-sale interfaces that adapt to different consumer preferences or consumer device signals. Some embodiments may provide for consumer interfaces that allow consumers to manage their electronic identity at various (e.g., merchant) locations.

Prescient and adaptive point-of-sale systems

Provided herein are method, apparatus, and computer program products for facilitating a learning user interface. The interface may be presented as a plurality of dynamic icons representing a plurality of items. The interface may further be facilitated by accessing, by a processor, business data corresponding to the plurality of items. The interface may be facilitated by determining, by the processor, a visual bias for at least one of the plurality of dynamic icons based on the business data corresponding to the plurality of items and may be facilitated by applying, via the interface, the visual bias to the at least one of the plurality of dynamic icons.

Learning user interface

Provided herein are method, apparatus, and computer program products for facilitating a learning user interface. The interface may be presented as a plurality of dynamic icons representing a plurality of items. The plurality of dynamic icons may include at least one suggested dynamic icon representing at least one suggested item of the plurality of items and at least one secondary dynamic icon representing a secondary item of the plurality of items. The interface may be facilitated by determining, via a processor, a visual bias for the at least one suggested dynamic icon relative to the at least one secondary dynamic icon. The interface may be facilitated by applying the visual bias, via the interface, to the at least one suggested dynamic icon.

Systems, apparatus, methods, and non-transitory media for programmatically grouping consumers are discussed herein. Some embodiments may include a system configured to provide to shared promotion redemptions. The system may include a merchant device with processing circuitry configured to associate multiple consumer accounts with a point-of-sale order. Based on receiving redemption data from a consumer device associated with one of the consumer accounts, the system may be further configured to allow the consumer device to share a selected promotion. For example, the system may determine payment share amounts for each consumer account based on a transaction price of the point-of-sale order and the redemption value of the promotion selected for shared redemption.

Systems and methods for providing shared promotion redemptions

Provided herein are method, apparatus, and computer program products for facilitating a learning user interface. The interface may be presented as a plurality of dynamic icons representing a plurality of items. The interface may be facilitated by receiving, by a processor, a selection indication associated with one item of the plurality of dynamic icons. The interface may be facilitated by determining, via the processor, at least one suggested item of the plurality of items based on the selection indication. The interface may also be facilitated by determining a visual bias for at least one suggested dynamic icon representing the at least one suggested item relative to at least one secondary dynamic icon and may be facilitated by applying the visual bias, via the interface, to the at least one suggested dynamic icon.

Systems, apparatus, methods, and non-transitory media for programmatically grouping consumer devices into stable spatial clusters are discussed herein. Some embodiments may include a point-of-sale system including a first consumer device of a stable spatial cluster of consumer devices to serve as a communication beacon. The first consumer device, that serves as the communication beacon, is configured to transmit and receive signals between a server and the other consumer devices of the stable spatial cluster of consumer devices. The other consumer devices receive a beacon identifier from the first consumer device and are thereby associated with a point-of-sale order to facilitate suitable point-of-sale functionality that may be provided via the first consumer device.

Systems and methods for programmatically grouping consumer devices into stable spatial clusters

Provided herein are a method and apparatus for facilitating a learning user interface. The interface may be presented as a plurality of dynamic icons representing a plurality of items. The interface may be facilitated by determining, via a processor, a visual bias for at least one of the plurality of dynamic icons, wherein the visual bias may include an at least partial ring extending about the at least one of the plurality of dynamic icons. The interface further may be facilitated by applying, via the interface, the visual bias to the at least one of the plurality of dynamic icons and in response to a user selection of such at least one dynamic icon, incrementing the visual bias, such that the incrementing of the visual bias is triggered by the selection of the at least one dynamic icon.

Incrementing a visual bias triggered by the selection of a dynamic icon via a learning user interface

Provided herein are method, apparatus, and computer program products for facilitating a learning user interface. The interface may be presented as a plurality of dynamic icons representing a plurality of items. The interface may further be facilitated by receiving a profile identifier and by accessing, via a processor, profile data associated with the profile identifier. The interface may be facilitated by determining, via the processor, a visual bias for at least one of the dynamic icons relative to another of the dynamic icons based on the profile data and may be facilitated by applying the visual bias, via the interface, to the at least one of the dynamic icons. Multiple interfaces may be applied to the same or different screens.

Learning user interface apparatus, computer program product, and method

Systems, apparatus, methods, and non-transitory media for programmatically grouping consumers are discussed herein. Some embodiments may include a point-of-sale system including a merchant device and one or more communication beacons. The communication beacons may be placed at locations of interest and may be configured to broadcast different beacon identifiers. Nearby consumer devices that receive the beacon identifier may be determined to be associated with a point-of-sale order and suitable point-of-sale functionality may be provided. In some embodiments, a peer consumer device may be selected as an ad hoc communication beacon for broadcasting a beacon identifier to other consumer devices.

Growing community of inventors

Menlo Park, CA, United States of America

Tihomir Tsankov Georgiev