Abstract: A processor may receive travel information and user travel query. The user travel query may be from a user. A processor may analyze the travel information and the user travel query. A processor may generate one or more operational condition predictions from the travel information and user query. A processor may generate one or more passenger satisfaction predictions from the travel information and user query. A processor may identify a user satisfaction score based, at least in part, on one or more feature variances. The one or more feature variances may be based, at least in part on the one or more operational condition predictions and the one or more passenger satisfaction predictions. A processor may output the user satisfaction score to the user.

Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include engaging a user in a primary activity; the primary activity may include a plurality of stages. The operations may include compiling at least one risk-reward score for an advertisement placement of an advertisement for at least one of the plurality of stages. The operations may include identifying a recommended stage for the advertisement; the recommended stage may be based on the risk-reward score. The operations may include displaying the advertisement to the user at the recommended stage.

Abstract: A computer-implemented method for generating an ordered list of craft departures from a known origin point based on an operational cost and a predicted passenger satisfaction cost. The method collects historical data about one or more passengers, wherein the historical data comprises one or more craft operations and associated passenger complaint and satisfaction data. The method further trains a passenger satisfaction prediction model based on the collected historical data and computes the predicted passenger satisfaction cost for each of the craft departures based on the trained passenger satisfaction prediction model. The method further generates an ordered list of craft departures based on a combination of the operational cost and the computed predicted passenger satisfaction cost.

Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include engaging a user in a primary activity; the primary activity may include a plurality of stages. The operations may include compiling at least one risk-reward score for an advertisement placement of an advertisement for at least one of the plurality of stages. The operations may include updating, dynamically, the at least one risk-reward score and identifying a recommended stage for the at least one advertisement; the recommended stage may be based on the risk-reward score. The operations may include displaying the at least one advertisement to the user at the recommended stage.

Abstract: A computer system includes a memory having computer readable instructions and a processor for executing the computer readable instructions. The computer readable instructions control the processor to determine an active workflow initiated by a user. The active workflow includes a plurality of individual workflow stages that are sequentially presented to the user to complete a task. The processor further receives a user input requesting execution of a deferrable marketing action located at a current workflow stage of the active workflow, and controls the deferrable marketing action in response to the user input so as to delay execution of the deferrable marketing action.

Abstract: Predictive analysis of customer relationship management elements by receiving service feature data associated with past services, receiving customer feature data, including customer interaction outcome data, for a set of customers associated with the past service, training a machine learning model according to the received feature data and customer feature data, and providing the trained machine learning model to a user, the model configured for predicting a future customer interaction outcome probability according to service feature data associated with a current service, and customer feature data associated with customers of the current service.

Abstract: A customer segmentation method, system, and computer program product, include inputting a set of characteristic features for each of a plurality of customers, defining a customer-event map that maps the characteristic features of each of the customers to a plurality of event categories, and estimating a likelihood of an event driven purchase for each product type and an event category combination.

Abstract: A market event identification method, system, and computer program product, include defining a likelihood function that maps a likelihood of a purchase of a product during an event by customers having similar customer features and estimating a likelihood of an event-driven purchase by the customers for each of a plurality of product-event combinations using the defined likelihood function.

Abstract: A market event identification method, system, and computer program product, include defining a likelihood function that maps a likelihood of a purchase of a product during an event by customers having similar customer features and estimating a likelihood of an event-driven purchase by the customers for each of a plurality of product-event combinations using the defined likelihood function.

Abstract: A event response pool identification method, system, and computer program product, include grouping segments of customers into a plurality of groups according to a measure of a similarity between the customers in the segments of customers, measuring a strength of an impact on a plurality of events for a group of the segments of customers by analyzing sales data across a full product set, and mapping each event to the plurality of groups that exhibit a strongest strength of the impact to the event.

Abstract: A customer segmentation method, system, and computer program product, include inputting a set of characteristic features for each of a plurality of customers, defining a customer-event map that maps the characteristic features of each of the customers to a plurality of event categories, and estimating a likelihood of an event driven purchase for each product type and an event category combination.

Abstract: A method and system that receives, as input data in a processor of a computer, an identification and location of a retail entity. Map data relevant for the retail entity is received and the retail entity is located on the map data. Data identifying at least one of a product, a product set, and a service or services is received as input data. A listing is received of one or more competitors that offer the product or one or more products of the product set or the service as a competitor of the retail entity for the product, product set or service. The one or more competitors are located on the map data. An affinity for consumers is calculated for the product, product set, or service for the retail entity and each of the one or more competitors.

Abstract: A method and system for retail forecasting includes accessing, from a database, retail data for past purchases of a customer at a retail entity and contextual data and generating, using a processor on a computer, at least one purchase forecasting model for a specific product for the customer.

Abstract: A method and system includes providing an electronic coupon to a customer, providing the customer an option to improve the coupon in exchange for a customer response, performing an analysis of at least one of information known about the customer, coupon issuer information, and contextual information, and identifying an information gap item which is at least one of missing, incomplete, and not updated within a time range, generating a customer response requirement based upon the information gap item, displaying the response requirement to the customer, and upon the customer providing a response which satisfies the response requirement, improving the coupon based on the customer response.

Abstract: A method and system for dynamically analyzing information relating to a store to determine product information to show on a display during a period, and displaying product information on the display based on the analyzed information for the period.

Abstract: A computer-implemented method for specifying the characteristics of a desired item includes specifying a plurality of items, each of which possess at least one but not all characteristics of the desired item, selecting a subset of characteristics from each of said plurality of items, combining selected subsets of characteristics into a characterization of the desired item, and validating an availability of the desired item.

Abstract: A system (and method) includes a seating platform, at least one sensor for detecting a state of the seating platform connected to a first wireless communications device, the first wireless communications device for conveying information on the state of the seating platform, and a second wireless communications device for receiving information from the first wireless communications device, and a computing system. The second wireless communications device is for receiving the information carrying signal and is connected to the computing system. The computing system is for initiating an action based upon the information.

Abstract: A system includes a mobile seating platform, a wireless communications system embedded within the seating platform, and a haptic system embedded in the seating platform. The haptic system includes a plurality of vibrators disposed at a plurality of positions in the seating platform for communicating information to the occupant of the seating platform and a plurality of deformable surfaces disposed at a plurality of positions in the seating platform for communicating information to the occupant of the seating platform.

Abstract: A system (and method) includes a seating platform, at least one sensor for detecting a state of the seating platform connected to a first wireless communications device, the first wireless communications device for conveying information on the state of the seating platform, and a second wireless communications device for receiving information from the first wireless communications device, and a computing system. The second wireless communications device is for receiving the information carrying signal and is connected to the computing system. The computing system is for initiating an action based upon the information.

Abstract: A system (and method) includes a seating platform, at least one sensor for detecting a state of the seating platform connected to a first wireless communications device, the first wireless communications device for conveying information on the state of the seating platform, and a second wireless communications device for receiving information from the first wireless communications device, and a computing system. The second wireless communications device is for receiving the information carrying signal and is connected to the computing system. The computing system is for initiating an action based upon the information.