GROUPON, INC.

Systems and related methods facilitating payments with a mobile device are discussed herein. Circuitry in a networked-based payment system may be configured to receive payment information from a first device. The first device may include circuitry configured to wirelessly receive wallet identifying data from the payment system. The wallet identifying data may be used to secure messages between the first device and another device over a wireless link. For example, the first device may be configured to send the wallet identifying data to a second device, which may then communicate with the payment system. In response, consumer identifying data associated with the wallet identifying data may be received by the second device from the payment system. In some embodiments, use of wallet identifying data may be applied to other communications, such as for messages that authorize payment.

Provided herein are systems, methods and computer readable storage media for facilitating payments for consumer transactions and redemption of deal offerings. In providing such functionality, the system can be configured to, for example, receive payment for one or more products, determine a deal voucher's current value and cause the redemption of the deal voucher.

Methods, apparatus, systems, and computer program products are disclosed for utilizing specially configured machine learning models to generate incremental currency value(s) associated with one or more target merchant data objects. Some embodiments, based on one or more market record sets, identify an actual electronic currency value for a total merchant data object set, and include a counterfactual model configured to generate a counterfactual electronic currency value for use in determining a counterfactual incremental electronic currency impact, and in some embodiments for ranking other models. Embodiments, additionally or alternatively, include an incrementality-trained ensemble model for generating a predictive incremental electronic currency impact. The incrementality-trained ensemble model may be trained to predict based on the rankings of the outputs of the counterfactual model. Embodiments may further rank target merchant data objects and perform one or more additional actions, including assigning the target merchant data objects to sales account data structures for management.

Systems and related methods facilitating payments with a mobile device are discussed herein. Circuitry in a networked-based central system, which may be a promotional system or payment system, may be configured to receive payment information from a consumer device. The consumer device may include circuitry configured to receive wallet identifying data from the central system. The wallet identification data may be used to secure messages between the consumer device and another device, such as a merchant device, over a wireless link. In some embodiments, the consumer device may receive promotional offers, such as deal vouchers or rewards, and make payments to the other device via the wireless link.

Embodiments of the present invention provide methods, systems, apparatuses, and computer program products for predicting consumer behavior. In one embodiment a method is provided comprising automatically creating a link graph comprising nodes representing webpages, links representing hyperlinks, and weights for each link representing a number of times a hyperlink associated with the respective link redirected the a user devices from a webpage associated with a first node connected to the link to a webpage associated with a second node connected to the link; and determining based on the link graph a programmatically expected path for a particular user, wherein the programmatically expected path identifies, at least, two or more webpages that the particular user is programmatically expected to visit and specifying a programmatically expected order at which the particular user will visit the webpages.

Provided herein are systems, methods and computer readable media for facilitating delivery of a digital notification of a physical product to inform a recipient of the identity of the physical product. A digital notification may inform the recipient of the identity of a physical product ordered for the recipient by a sender. A digital unwrapping trigger may be utilized to ensure that the recipient is authorized to view the identity of the digital product. For example, the digital notification may not identify the identity of the physical product until a particular date has passed (e.g., a holiday or birthday), until the recipient performs a certain task, or until the recipient meets a certain goal. In response to the trigger occurring, the digital notification may be enabled for viewing of the identity of the physical product. The physical delivery of the product may be coordinated with delivery of the digital notification.

Various methods are provided for determining and displaying local content. One example method may comprise receiving input to open a mobile application at a mobile device, and without any additional input, accessing a location service of the GPS enabled mobile device to determine a GPS location and automatically generating a query, the query comprising the GPS location, identifying a predefined mix of content from a content index in accordance with an editing target, wherein the editing target specifies a number of articles and wherein the predefined mix indicates a portion of the editing target directed to at least one category, determining whether the editing target and the predefined mix are met, determining a new location, the new location being larger in geographic area and containing the location, in an instance in which the editing target and the predefined mix are not met, and displaying the results.

Provided herein are systems, methods and computer readable media for classification and tagging of textual data. An example method may include accessing a corpus comprising a plurality of documents, each document having one or more labels indicative of services offered by a merchant, generating a query based on extracted features and the documents, generating a precision score for at least a portion of the generated query and selecting a subset of the generated queries based on an assigned precision score satisfying a precision score threshold, the selected subset of the generated queries configured to provide an indication of one or more labels to be applied to machine readable text. A second example method, utilized for tagging machine readable text with unknown labels, may include assigning a label to textual portions of the machine readable text based on results of the application of the queries.

A method, apparatus and computer program product are provided for calculating closing metrics regarding a contract between a promotion service and provider. A promotional system may calculate a probability of closing, and an estimated time to close. The promotion service may offer a promotion to consumers for a discounted product or service, to be honored by the provider. A category, lead source, historical data, stage in sales, and/or size of the provider may be used in calculating a probability of close and/or time to close. An example method may comprise supplying a classifying model with a dataset, wherein the dataset comprises an identification of a provider and attributes corresponding to the provider and identifying a class of the provider in accordance with the plurality of corresponding attributes, wherein the identification is determined based on one or more patterns determinative of a return rate by the classifying model.

Embodiments of the present disclosure provide methods, systems, and apparatuses for computing a channel incrementality ratio using a machine learning model.