Aspects of the subject disclosure may include, for example, obtaining a first indication of a user of a communication device browsing a first website associated with a first vendor, obtaining a second indication of the user of the communication device browsing a second website associated with a second vendor that is different from the first vendor, determining, in accordance with the first indication and the second indication, that the first vendor and the second vendor operate in a common marketplace, responsive to the determining, obtaining an advertisement of the first vendor to provide to the communication device, and providing the advertisement to the communication device. Other embodiments are disclosed.

In selected embodiments a recommendation generator builds a network of interrelationships between venues, reviewers and users based on attributes and reviewer and user reviews of the venues. Each interrelationship or link may be positive or negative and may accumulate with other links (or anti-links) to provide nodal links the strength of which are based on commonality of attributes among the linked nodes and/or common preferences that one node, such as a reviewer, expresses for other nodes, such as venues. The links may be first order (based on a direct relationship between, for instance, a reviewer and a venue) or higher order (based on, for instance, the fact that two venue are both liked by a given reviewer). The recommendation engine in certain embodiments determines recommended venues based on user attributes and venue preferences by aggregating the link matrices and determining the venues which are most strongly coupled to the user.

A method for generating a singularity recommendation includes receiving structured and unstructured data for a user, where the structured and unstructured data for the user provide a first context for generating a singularity recommendation. The method, responsive to identifying a location for the user, determines ecosystem data based on the location for the user, where the ecosystem data provides a second context for generating the singularity recommendation. The method determines environmental data based on the location for the user, where the environmental data provides a second context for generating the singularity recommendation. The method generates the singularity recommendation based on the first context, the second context, and the third context directed to the user. The method displays the singularity recommendation in a user interface on a client device associated with the user.

A system for delivering targeted content to a wireless handset is described. The system comprises a beacon and a wireless handset communicatively coupled to a network. The wireless handset receives a signal from the beacon. A user profile associated with the wireless handset comprises at least one user attribute. The system further comprises a content administration interface configured to store an association between a content item and a user attribute. The system further comprises a content delivery module configured to filter stored content items to retrieve content items associated with a user attribute. The content delivery module transmits at least one retrieved content item to the wireless handset via the network. A handset content interface displays the at least one transmitted content item on the wireless handset.

A computed-implemented method and system for recommending business applications on a network-based marketplace are described. A user's listings, representing items for sale on the marketplace, are harvested to calculate segmentation data and metrics that form a user profile. The user profile is compared with other similar users who have subscribed to various applications, and the impact those applications have had on the metrics of the similar users is calculated in order to determine what impact the applications will have on the user in question. The impact, combined with user preferences, is used to suggest appropriate applications, which are displayed to the user within the marketplace. If the user selects one of the applications, the application is added to the user's profile and relevant listings are updated with the new application.

An app server receives a device token from a software application on a mobile device. The device token identifies the mobile device for pushing notification messages of the software application to the mobile device via a push notification system. The mobile device is monitored while accessing the Internet in order to detect when the user may benefit from upgraded access to the Internet. The app server then sends one or more notification message(s) to the user such as by sending a message to the device token of the mobile device via the push notification system or to a display device associated with the user at the hospitality establishment. The notification message invites the user to upgrade their Internet access. The push notification system alerts the user to the notification message via the user interface of the mobile device even when the software application is not running on the mobile device.

According to some aspects, disclosed methods and systems may include storing, in a local storage of a device, a plurality of advertisements; and outputting for display first content comprising a first portion of a first set of advertisements associated with a first campaign period. The disclosed methods and system may also include, in response to an expiration of the first campaign period, outputting for display second content comprising a second portion of the first set of advertisements based on a first set of one or more advertising rules.

A system includes a set of crawlers that find and retrieve documents from an information network, an information extraction system, a knowledge graph storing nodes and edges that connect them, wherein each node represents a respective entity of a corresponding entity type of a plurality of entity types, and wherein the knowledge graph further stores event data relating to events detected by the information extraction system, a machine learning system that trains models that are used in connection with at least one of entity extraction, event extraction, recipient identification, and content generation, a lead scoring system that scores the relevance of information to an individual and references information in the knowledge graph, and a content generation system that generates content of a personalized message to a recipient who is an individual for which the lead scoring system has determined a threshold level of relevance.

Disclosed herein are system, method, and computer program product embodiments for analyzing second party advertising data. An embodiment operates by determining a set of dimensions that a source uses to aggregate data for an advertising campaign. The embodiment creates a subunit advertising campaign based at least in part on the advertising campaign, the determined set of dimensions, and a dimension of interest. The embodiment receives measurement data associated with an execution of the subunit advertising campaign. The embodiment then analyzes the measurement data.

Technology that facilitates the encouragement of conversion of customers during their online journeys is disclosed. Exemplary implementations may: monitor an online journey of a customer with an entity; profile the customer to select a persona of a plurality of personas; predict a lack of conversion by the customer during the monitored online journey of the customer; and in response to the prediction, offer an optional online path forward for the customer's online journey to the customer.