Implementations of the disclosed subject matter may provide a method of retrieving a data record including historic utility bill statements of a customer, determining a historic energy usage rate of the customer based on the retrieved data record, and determining whether the customer is eligible to subscribe to a community solar energy generating system based on geographic location of the community solar energy generating system, the determined historic energy usage rate of the customer, and the customer's geographic location. The method may determine an allocation of energy produced by the community solar energy generating system when the eligible customer is enrolled in a subscription to the community solar energy generating system. The method may generate a customer data record for the user based on credits for the allocation of energy of the community solar energy generating system and receiving energy from another energy generating system.

This document describes the collection, generation, distribution, and management of online web content. The devices, systems, and methods described herein can be used to collect and generate online web content and communications. Specifically, the disclosed devices and systems may be employed to produce one or more marketing and/or advertising campaigns, as well as for monitoring, managing, defining the efficiency, effectiveness, and workability of the campaign with respect to generating user engagement, thereby accurately determining the cost benefits of the campaign. The analytic results provided may then be used to guide the generation of original web content, such as for the purposes of enhancing customer or follower experience, driving business, and for driving advertising campaigns. Alternatively, web content that is in the public domain, and determined to perform well, can be reproduced, referenced, or otherwise referred to, in the context of promoting or presenting the user's web content.

Member outreach services to be offered to members of a health plan based on predictions generated by a prediction engine using data associated with the members. The prediction engine can include an ensemble of different base predictive models, and the prediction engine can use a weighted combination of base predictions produced by the different base predictive models to generate a final prediction associated with a member. A representative can attempt to contact the member based on an outreach ticket associated with the final prediction. The representative can also provide ticket feedback associated with the outreach, and the prediction engine can use the ticket feedback to adjust the weights associated with the different base predictive models.

A system, method, and computer program are provided for a path-finding analytic tool that operates on customer data. In use, customer data that includes a plurality of customer profiles stored for a plurality of customers of a business entity is accessed. Each customer profile includes values for: one or more non-actionable features, and one or more actionable features. At least a 3D map is generated from the customer data, where each point on the map represents a different customer profile, and where at least one dimension of the map represents a target feature. A path is determined between a first point on the map representing a first customer profile and a second point on the map representing a second customer profile, for identifying at least one actionable feature in the first customer profile capable of having its value modified to optimize the target feature corresponding to the first customer profile.

In an example embodiment, multiple machine learned models are used to continually learn from data to update various prediction models. Prediction of item prices, at the production and distribution point level, and utilizing this information along with other item information, such as crop yield, operational cost, and storage cost in the case of arming, may be used to solve the long- and short-term planning problems of farmers and help in decision making based on daily and the most up-to-date forecasts.

An artificial intelligence (AI)-based content communications system leverages microtrends identified from conversations in real-time to support targeted content mapped to the identified microtrends. The communications system receives conversation information of participants, including text of conversation, timestamp, and, optionally, geographical information, from a listening service authorized to capture the conversation information; determines one or more topic microtrends having above-threshold activity; retrieves content with tags having generated keywords associated with a corresponding topic microtrend; and generates a message comprising the content and, optionally, a topic microtrend dashboard to provide to an identified contact associated with the topic microtrend. In some cases, the content is directly pushed to a social media handle associated with the content.

The present disclosure provides a computerized method for item distribution, including retrieving, from a data structure, an inventory of a SKU at each of a plurality of destinations; determining a buffer of each of the destinations; determining an average buffer across the destinations; identifying at least one high utilization destination and at least one low utilization destination based on differences from the average buffer; and redistributing a network inventory by, iteratively and for each of the high utilization destinations: finding, in the data structure, a low utilization destination having a common attribute with the high utilization destination; and sending, to a user device for display, an instruction to transfer a redistribution quantity of the SKU from the low utilization destination to the high utilization destination.

Systems, methods, and techniques are disclosed whereby locational marginal emission rates may be determined for each location (or node) of an electric power generation and distribution system using Real-Time Market data provided by a power system market operator, along with marginal offer estimate data and generator emission data. Noisy and incomplete input data can be appropriately handled to allow use of Real-Time Market data. The effect of congestion (violated constraints) can also be removed.

The disclosed subject matter relates to a system and method for personalizing customer experience at a retailer's physical location in order to increase sales and customer satisfaction. The personalization is based upon classification of customer's online interaction with the retailer. Upon detecting the customer's presence at the retailer's physical location, data of the customer's online interactions is retrieved and classified based on the type of online interactions and temporal characteristics. Push content is transmitted to the customer, the push content being based upon at least the classification and data associated with retailer's physical location.

Systems and methods for determining an optimal delivery location based on delivery address and delivery time are provided. An example method includes receiving an online order from a user application installed on a user device; generating a map comprising a dynamic display of a local service area polygon associated with the online order and transmitting the map to the user application; transmitting to the user application a request for a delivery address; upon receipt of the delivery address, querying the delivery address to determine whether the local service area polygon includes the delivery address; transmitting to the user application a request for a delivery time; upon receipt of the delivery time, automatically recommending an optimal delivery location and time within the local service area polygon based on the delivery address and delivery time; and executing a delivery of the online order based on the optimal delivery location and time.