Abstract: Systems and methods for generating location-based retail pricing options are discussed herein. In an example, a method for generating location-based retail pricing options includes receiving, over a network from a user, a pricing request. The pricing request includes information identifying the user, a merchant, and an intended purchase. In this example, the method further includes determining a pricing option associated with the merchant and the intended purchase, and transmitting the pricing option to the user. The method still further includes processing a purchase transaction, associated with the user, for the intended purchase based on the pricing option.

Abstract: Systems and methods for generating location-based retail pricing options are discussed herein. In an example, a method for generating location-based retail pricing options includes receiving, over a network from a user, a pricing request. The pricing request includes information identifying the user, a merchant, and an intended purchase. In this example, the method further includes determining a pricing option associated with the merchant and the intended purchase, and transmitting the pricing option to the user. The method still further includes processing a purchase transaction, associated with the user, for the intended purchase based on the pricing option.

Abstract: Systems and methods for generating location-based retail pricing options are discussed herein. In an example, a method for generating location-based retail pricing options includes receiving, over a network from a user, a pricing request. The pricing request includes information identifying the user, a merchant, and an intended purchase. In this example, the method further includes determining a pricing option associated with the merchant and the intended purchase, and transmitting the pricing option to the user. The method still further includes processing a purchase transaction, associated with the user, for the intended purchase based on the pricing option.

Abstract: Systems and methods for real-time location-aware recommendations are discussed herein. In an example, a method for generating location-aware recommendations can include receiving a current location of a user, calculating a place graph for the user, traversing the place graph, selecting a recommendation, and communicating the recommendation. In this example, the place graph is calculated based on the current location. Traversing the place graph can identify one or more potential recommendations within a pre-defined distance of the current location.

Abstract: Systems and methods for generating location-based retail pricing options are discussed herein. In an example, a method for generating location-based retail pricing options includes receiving, over a network from a user, a pricing request. The pricing request includes information identifying the user, a merchant, and an intended purchase. In this example, the method further includes determining a pricing option associated with the merchant and the intended purchase, and transmitting the pricing option to the user. The method still further includes processing a purchase transaction, associated with the user, for the intended purchase based on the pricing option.

Abstract: Systems and methods to deliver a location-aware offer based on past demonstrated intent to purchase are discussed. For example, a method to deliver a location-aware offer can include operations for receiving a current location, determining when the user is within a pre-defined proximity to a merchant location, accessing user profile data, generating an offer, and delivering the offer to a client device. The current location can represent the physical location of a client device. The user profile data including an intended purchase list. Generating the offer includes matching inventory available at the merchant location to an item on the intended purchase list.

Abstract: Systems and methods for delivering context sensitive dynamic mobile advertisements are discussed. In an example, a method for delivering context sensitive dynamic mobile advertisements can include receiving user-related context data, generating an advertisement, transmitting the advertisement, updating a dynamic content portion of the advertisement, and transmitting at least the updated dynamic content portion. The advertisement is generated based at least in part on the user-related context data, and includes the dynamic content portion to display dynamic data related to the user-related context data.

Abstract: Systems and methods for real-time location-aware recommendations are discussed herein. In an example, a method for generating location-aware recommendations can include receiving a current location of a user, calculating a place graph for the user, traversing the place graph, selecting a recommendation, and communicating the recommendation. In this example, the place graph is calculated based on the current location.