Systems and methods are disclosed for targeting of advertising content for a consumer product, by obtaining consumer demographic data, the consumer demographic data including a plurality of demographic attributes for each person; identifying a plurality of media slots; and obtaining program information for a respective identified program aired in each media slot among the plurality of media slots, the program information including viewing data of a plurality of viewing persons viewing the program and each viewing person being among the plurality of persons. The methods also include enriching the viewing data with the consumer demographic data; identifying a plurality of advertiser industries; enriching the product purchaser data with the consumer demographic data; calculating a relevance of each advertiser industry among the plurality of advertiser industries for each identified program based on demographic attributes of the product purchasers in each advertiser industry and demographic attributes of the viewing persons.

A valid combination of products is constructed from a set of products identified by a retailing backend system. The valid combination satisfies a condition of an offer. A product in the combination of product is a physical product located in a physical store. A social sentiment towards the product in social media data of a shopper is evaluated, and a rating of the product is computed using the evaluation. A location of the product in the store is obtained from the retailing backend system. The location of the product is overlaid on a view of the store, where the view is from a perspective of a location of the shopper, the shopper being physically situated in the store.

Disclosed embodiments provide a framework to solicit and evaluate responses from brands and other users to the intents communicated by customers. In response to obtaining an intent, an intent messaging service provides the intent to an application implemented on a computing device of a user to solicit a response to the intent. In response to obtaining an intent response, the intent messaging service prohibits the user from generating further intent responses and provides the obtained intent response to the customer. The intent messaging service establishes a communications channel between the customer and the user in response to another request corresponding to the intent. This allows for additional responses to be provided to the customer by the user identified by the intent messaging service.

A classification based notification system is disclosed which performs operations that include: accessing user profile data associated with a user account associated with a client device, the user profile data including a list of user connections; designating a notification type to a portion of the list of user connections, the notification type corresponding to an alert attribute; receiving a notification from a user connection from among the portion of the list of user connections at the client device; and presenting an alert based on the alert attribute that corresponds with the notification type associated with the portion of the list of user connections at the client device.

Machine learning (ML) can be used to gather data on prospective customers from publicly available online sources. The ML can provide data on a likelihood of near future, customers and subscribers and a list of people with low interest in the company's products. The ML system can be recursively updated as new public data becomes available online. Thus, the ML system can be used to generate targeted advertising and root cause analysis based on a relationship between people's statuses and their respective interests in certain products and/or services.

A coupon system is disclosed that allows for the issuance of a personalized electronic coupon book. A user may communicate with the coupon system via a computer. Using this computer, the user may review a list of coupon sponsors on the coupon system, and may select a plurality of coupon sponsors for inclusion in the user's electronic coupon book.

In selected embodiments a recommendation generator builds a network of interrelationships between venues, reviewers and users based on their 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.

Embodiments of the present disclosure provide mechanisms for selection of a user survey data object from a set of user data objects, and processing of survey engagement data associated with a selected user survey data object. The user survey data object selected is appropriate for providing associated with a particular user data object, and the survey engagement data received associated therewith enables programmatic selection and use of particular ranking model(s) for use in generating and providing an output ranked item data object set. Example embodiments utilize selected ranking model(s) of a set of ranking models to programmatically generate and output an output ranked item data object set for a particular user profile.

Systems and methods for targeted advertising are described. The method may include receiving information regarding a future event. The information may include a time and a user identification. Receiving local additional information regarding the user from the one or more databases; requesting third party additional information regarding the user from one or more third party databases; accessing advertiser information from the one or more databases; selecting one or more advertisements based on the advertiser information, information regarding the future event, the local additional information, and the third party additional information; creating a communication template for the one or more selected advertisers; and sending the communication template.

Systems and methods are described for identifying a subset of interest from a general population and for monitoring a database of daily activity logs associated with the general population in order to identify database entries indicative of an occurrence of a pre-defined trigger event that is associated with a member of the subset of interest. In particular, systems and methods are described that allow a massive database of daily activity logs to be monitored to identify trigger events that have occurred within the past twenty-four hours or other very recent time period. Embodiments are described that may be advantageously used by a provider of credit-related products and/or services who wishes to accurately target prospective customers, identified by the system, based on occurrence of a trigger event, as being in a decision-making phase of credit shopping, for purposes of making a timely and targeted offering relevant to the customers' current activities.