A system and method is presented that uses software logic (executing in one or more servers) to inter-connect mobile devices and location-deriving signal generating devices to collectively act as an Imaging System that outputs a periodic succession of images containing information about the preferences and purchase and transaction history of consumers. The Imaging System so constructed is called a SoftCamera in a fashion analogous to a conventional light-based camera. Images output by the SoftCamera may be transmitted to third-party providers or used to send information and recommendations to consumers. The SoftCamera thus may be used as a Recommender System in certain embodiments.

A system, method, and non-transitory computer-readable medium are provided which track mobility of a user via a vehicle and/or a portable electronic device to automatically and proactively provide enhanced service information to the user based on changes in behavior of the user. According to the method, data indicating a behavior pattern of the user is received from a memory, the mobility of the user is continuously tracked, and a determination is made of whether a change occurs in the behavior pattern of the user based on the mobility of the user. When it is determined that a change has occurred, a determination is made of the type of change in the behavior pattern, and based on the type of change, the service information is outputted to the user and/or a third party such as a financial service provider and the behavior pattern is periodically adapted according to the user's feedback.

Offline consumer behavior and interactions are observed using beacons positioned at venues where consumers spend time and interact with each other. The beacons communicate with mobile computing devices that are carried by the observed consumers. The observed consumer behavior provides actionable insights into how consumers influence each other. For example, the people that a particular consumer spends time with form a circle of influence associated with that consumer. If the consumer makes a purchase, members of the circle of influence are observed to understand the degree to which they were influenced by the purchase, if at all. Metrics that quantify a consumer's influence over other consumers allow marketers to more effectively target both the influencing and influenced consumers. Also, if relatively little information is known about a particular consumer, that consumer's digital marketing profile can be supplemented using information known about the consumers with whom he/she often spends time.

Provided is a process of discovering psychographic segments of consumers with unsupervised machine learning, the process including: obtaining a first set of consumer-behavior records; converting the first set of consumer-behavior records into respective consumer-behavior vectors; determining psychographic segments of consumers by training an unsupervised machine learning model with the first set of consumer-behavior vectors; obtaining a second set of consumer-behavior records after determining the psychographic segments of consumers; converting the second set of consumer-behavior records into respective consumer-behavior vectors; classifying the second set of consumer-behavior vectors as each belonging to at least a respective one of psychographic segments with the trained machine learning model; and predicting based on the classification a likelihood of the respective consumer engaging in behavior associated with a corresponding one of the psychographic segments.

Provided is a process, including: obtaining geolocations histories of computing devices; assigning different subsets of the location histories to different computing devices in a compute cluster; querying a geographic information system (GIS) with geolocations in the geolocations histories to obtain identifiers of chain retail establishments; determining visit graphs for the individuals; and determining, for a given retail chain and a given individual, a score indicative of an affinity of the given individual to the given retail chain based on the visit graphs for more than 100 individuals including the given individual.

A method, computer system, and computer program product that aggregates sample data regarding a plurality of factors associated with income and geographic location; performs iterative analysis on the sample data using machine learning to construct a predictive model; populates, using the predictive model, a database with predicted values of average income for a selected set of predefined geographic regions; converts the predicted values of average income in the database into percentages of observed values of average income for geographic regions within the selected set over a specified time period to create indices of average income; and rank orders the regions within the selected set according to their indices of average income.

The disclosed embodiments provide systems, methods, and techniques for managing merchandising cards. A merchandising card may be, for example, a gift card, loyalty card, or the like. Consistent disclosed embodiments, a system for managing merchandising cards may include one or more memory devices storing instructions and one or more processors configured to acquire, from a device over a network, a plurality of locations associated with the device, the device locations being acquired at different instances in time within a predetermined period of time. Additionally, the one or more processors may be configured to calculate an overall merchant confidence rating for a merchant using the device locations. Further, the one or more processors may be configured to, based on the overall merchant confidence rating, determine that the merchant matches a merchant that is associated with merchandising card, and send a reminder a user of the device.

In embodiments, a computer system produces a first resource for a first dataset having a time indicator, by applying a first digital rule. A first notification can be caused to be transmitted about an aspect of the first resource to a remote device. A second dataset can be stored, which has values derived from the first dataset, and encodes a parameter of the first resource. A second digital rule may be stored to replace the first digital rule, at an updating time (Tupd). The second digital rule may have an effective time (Teff) prior to the actual updating time Tupd. A second resource may be produced by applying the second digital rule. A second notification can be caused to be transmitted about an aspect of the second resource to a remote device.

An auto-replenishment platform may receive retailer, manufacturer, and 3.sup.rd party consumer data on a regular time interval, via their e-commerce platforms. The auto-replenishment platform, via a harmonization engine, may aggregate all data sets, mine the aggregated data, and then cluster the data. Subsequently, the auto-replenishment platform may generate a consumer model for predicting the consumer demand for a product, factors that influence a consumer's perception of convenience or ease in purchasing that product, and for aggregating a consumer's purchased products for shipment or pickup. The auto-replenishment platform may send the consumer model to the retailer, manufacturer, and 3.sup.rd party e-commerce platforms to integrate the auto-replenishment platform into those platforms. Additionally, the auto-replenishment platform may group a consumer's products for shipment which provides additional efficiencies for the customer and retailer/manufacturer/3.sup.rd party in the form of time savings and/or reduced shipping and handling cost and related logistical advantages.

Systems, and methods for selecting advertisements based on party size and/or engagement are provided. An Internet-connected media display device may be detected as displaying media. An up-to-date party size in a monitored space may be determined based on frequency response data by a wireless access point located close to the space. An up-to-date engagement level may also be determined with respect to each individual in the space based on frequency response data by the wireless access point. An advertisement database may be filtered for a qualifying advertisement based on the identified party size and engagement levels.