Abstract: A machine learning algorithm is trained to learn to cluster a plurality of original-destination routes in a network for transporting cargo into a plurality of clusters based on similarities of the original-destination routes, and to learn to cluster the plurality of clusters into a plurality of subgroups based on customer behavior. Influencing criteria associated with each of the subgroups may be determined and based on the influencing criteria, a price elasticity curve for each of the subgroups may be generated. Based on the price elasticity curve and current network traffic, cargo transportation price associated with each of the subgroups may be determined.

Abstract: Systems, methods, and computer-readable media for controlling the timing of customer interactions (e.g., targeted product or service offerings to customers) in order to determine optimally efficient usage of a seller's available inventory are disclosed. A customer selection problem (CSP) may be formulated and solved to implement a customer selection policy for controlling the timing with which customers from a customer pool will be targeted with offerings. The customer selection policy may include dynamic optimization to account for intertemporal effects of customer decisions.

Abstract: System and method that improves cargo logistics may be presented. For instance, shipping capacity in cargo logistics may be best utilized based on providing pricing and scheduling solutions that are jointly optimized and prices differentiated based on flexibility of service request. Scheduled service and pricing may be transmitted as a signal to control execution of the cargo logistics.

Abstract: System, method and computer program product for effective supply-side planning of inventories during product transitions. The system for a supply-side entity that generates recommendations that include personalized shaping actions to control each customer's rate of adoption of a new product to replace an older legacy product during a transition period, and optimize overall use of available supply. The method optimizes personalized shaping actions so that a customer is transitioned at a speed that suits their personal profile as well as the seller's production/inventory constraints for each product. Shaping actions are determined based on the trajectory of each product's lifecycle. Further, customer-level adoption patterns for transitioning products are predicted from past behavior.

Abstract: A method for projecting performance of a target asset compared to a benchmark, the method comprising receiving one or more target matrices corresponding to a target portfolio and one or more benchmark matrices corresponding to a benchmark portfolio, wherein the target matrices and benchmark matrices comprise elements corresponding to variables that influence portfolio performance trajectory, computing a target performance trajectory based on the one or more target matrices and a benchmark performance trajectory based on the benchmark matrices, identifying actions to bring the target performance trajectory above the benchmark performance trajectory; and communicating the identified actions.

Abstract: A machine learning algorithm is trained to learn to cluster a plurality of original-destination routes in a network for transporting cargo into a plurality of clusters based on similarities of the original-destination routes, and to learn to cluster the plurality of clusters into a plurality of subgroups based on customer behavior. Influencing criteria associated with each of the subgroups may be determined and based on the influencing criteria, a price elasticity curve for each of the subgroups may be generated. Based on the price elasticity curve and current network traffic, cargo transportation price associated with each of the subgroups may be determined.

Abstract: A machine learning algorithm is trained to learn to cluster a plurality of original-destination routes in a network for transporting cargo into a plurality of clusters based on similarities of the original-destination routes, and to learn to cluster the plurality of clusters into a plurality of subgroups based on customer behavior. Influencing criteria associated with each of the subgroups may be determined and based on the influencing criteria, a price elasticity curve for each of the subgroups may be generated. Based on the price elasticity curve and current network traffic, cargo transportation price associated with each of the subgroups may be determined.

Abstract: A machine learning algorithm is trained to learn to cluster a plurality of original-destination routes in a network for transporting cargo into a plurality of clusters based on similarities of the original-destination routes, and to learn to cluster the plurality of clusters into a plurality of subgroups based on customer behavior. Influencing criteria associated with each of the subgroups may be determined and based on the influencing criteria, a price elasticity curve for each of the subgroups may be generated. Based on the price elasticity curve and current network traffic, cargo transportation price associated with each of the subgroups may be determined.

Abstract: System and method that improves cargo logistics may be presented. For instance, shipping capacity in cargo logistics may be best utilized based on providing pricing and scheduling solutions that are jointly optimized and prices differentiated based on flexibility of service request. Scheduled service and pricing may be transmitted as a signal to control execution of the cargo logistics.

Abstract: Systems, methods, and computer-readable media for controlling the timing of customer interactions (e.g., targeted product or service offerings to customers) in order to determine optimally efficient usage of a seller's available inventory are disclosed. A customer selection problem (CSP) may be formulated and solved to implement a customer selection policy for controlling the timing with which customers from a customer pool will be targeted with offerings. The customer selection policy may include dynamic optimization to account for intertemporal effects of customer decisions.

Abstract: A method for projecting performance of a target asset compared to a benchmark, the method comprising receiving one or more target matrices corresponding to a target portfolio and one or more benchmark matrices corresponding to a benchmark portfolio, wherein the target matrices and benchmark matrices comprise elements corresponding to variables that influence portfolio performance trajectory, computing a target performance trajectory based on the one or more target matrices and a benchmark performance trajectory based on the benchmark matrices, identifying actions to bring the target performance trajectory above the benchmark performance trajectory; and communicating the identified actions.

Abstract: A method, system and computer program product for detecting an emerging life event and identifying an action plan to remediate affects of the life event are disclosed. In an embodiment, the method comprises specifying a group of emerging life events, and a group of behavior features that map to the emerging life events; receiving behavioral data identifying behavior of a person; and analyzing the behavioral data to determine if any of the specified behavior features are identified in the behavioral data. When one or more of the behavior feature are identified in the behavioral data as behavior features of the person, the identified behavior features are mapped to one or more of the specified emerging life events; and the mapped emerging life events is used to determine an action plan to remediate affects of that life event.

Abstract: System, method and computer program product for effective supply-side planning of inventories during product transitions. The system for a supply-side entity that generates recommendations that include personalized shaping actions to control each customer's rate of adoption of a new product to replace an older legacy product during a transition period, and optimize overall use of available supply. The method optimizes personalized shaping actions so that a customer is transitioned at a speed that suits their personal profile as well as the seller's production/inventory constraints for each product. Shaping actions are determined based on the trajectory of each product's lifecycle. Further, customer-level adoption patterns for transitioning products are predicted from past behavior.

Abstract: A method for balancing supply and demand for a product using demand-shaping action includes identifying an imbalance between supply and demand for a given product. A customer choice model is generated based on collected historical sales data pertaining to the given product and at least one product similar to the given product. The customer choice model is configured to estimate, for a given customer or group of customers, a likelihood of effecting a substitution between each product pair of the given product and the at least one product similar to the given product, for each of one or more available demand shaping actions. One or more of the available demand shaping actions are automatically selected to minimize an estimate of revenue shortfall or inventory holding costs resulting from the identified imbalance between supply and demand.

Abstract: A method for balancing supply and demand for a product using demand-shaping action includes identifying an imbalance between supply and demand for a given product. A customer choice model is generated based on collected historical sales data pertaining to the given product and at least one product similar to the given product. The customer choice model is configured to estimate, for a given customer or group of customers, a likelihood of effecting a substitution between each product pair of the given product and the at least one product similar to the given product, for each of one or more available demand shaping actions. One or more of the available demand shaping actions are automatically selected to minimize an estimate of revenue shortfall or inventory holding costs resulting from the identified imbalance between supply and demand.