Systems and methods for aggregating transactions and optimization data related to energy and energy credits include a transaction-enabling system including a resource requirement circuit structured to aggregate a resource requirement for a fleet of machines to perform a task, wherein the resource requirement comprises an energy credit requirement; a forward resource market circuit structured to access a forward market for energy; and a machine resource acquisition circuit structured to execute a transaction on the forward market for energy in response to the aggregated resource requirement.

Systems and methods for forward market price prediction and sale of energy storage capacity are disclosed. An example transaction-enabling system may include a fleet of machines having an aggregate energy storage capacity; and a controller, comprising: an external data circuit structured to monitor an external data source and collect data from the external data source; an expert system circuit structured to predict a forward market price for energy storage capacity based on the collected data and the aggregate energy storage capacity; and a smart contract circuit structured to automatically sell at least a subset of the aggregate energy storage capacity on a forward market for energy storage capacity in response to the predicted forward market price.

A system for analyzing user consumption of content on web pages or determining user engagement with content comprising a data collection script and an content-engagement-inference engine. The data collection script determines one or more content elements to be measured from a web page and collects description data associated with the one or more content elements. The description data describes information about the one or more content elements. The content-engagement-inference engine creates an inference or analytics result based on the description data. The inference or analytics result describes how the one or more content elements have been consumed by users and then provides the inference or analytics result for users to designated entities.

Methods and systems for determining an individual gaze value are disclosed herein. An exemplary method involves: (a) receiving gaze data for a first wearable computing device, wherein the gaze data is indicative of a wearer-view associated with the first wearable computing device, and wherein the first wearable computing device is associated with a first user-account; (b) analyzing the gaze data from the first wearable computing device to detect one or more occurrences of one or more advertisement spaces in the gaze data; (c) based at least in part on the one or more detected advertisement-space occurrences, determining an individual gaze value for the first user-account; and (d) sending a gaze-value indication, wherein the gaze-value indication indicates the individual gaze value for the first user-account.

Systems and methods for controlling contacts with a client's users make use of segment-based contact limits. A contact limit sets a maximum number of contacts that a client can have with a user within a predetermined time window. A segment-based contact limit only applies the contact limit to a subset of all the client's users. The type of contact being limited could include messages that are sent to the user or advertising or sales campaigns that are conducted for the user. A segment is a subset of all of the client's users, and a segment may be defined based on one or more filters.

An example transaction-enabled system may include a smart contract wrapper to access a distributed ledger comprising intellectual property (IP) licensing terms corresponding to IP assets, wherein the IP licensing terms include an apportionment of royalties among owning entities in the distributed ledger. The smart contract wrapper may interpret an IP description value and an IP addition request, and, in response to the IP addition request and the IP description value, to add the apportionment of royalties corresponding to the IP description value. At least one of the plurality of IP assets comprises an instruction set and an operation on the distributed ledger provides provable access to the instruction set. A royalty apportionment wrapper apportions royalties from at least one royalty generating element to owning entities in response to the IP licensing terms.

Systems and methods for forward market renewable energy credit prediction from business entity behavior data are disclosed. An example transaction-enabling system may include a forward market circuit to access a forward energy credit market and a market forecasting circuit to automatically generate a forecast for a forward market price of an energy credit in the forward energy credit market. The example system may include wherein the forecast is based at least in part on a business entity behavior collected from at least one business entity behavioral data source, and wherein the energy credit comprises a renewable energy credit associated a renewable energy system. The example system may further include a smart contract circuit to perform at least one of selling the renewable energy credit or purchasing the renewable energy credit on the forward energy credit market in response to the forecasted forward market price.

Transaction-enabling systems and methods are disclosed. A system may include a controller with an attention market access circuit to interpret a plurality of attention-related resources available on an attention market and an intelligent agent circuit to determine an attention-related resource acquisition value based on a cost parameter of at least one of the plurality of attention-related resources. An attention acquisition circuit may then solicit an attention-related resource in response to the attention-related resource acquisition value

Automatic item placement recommendation is described. An item placement configuration system receives an item for which a recommended placement is to be generated and identifies an entity associated with the item. The item placement configuration system then identifies a multi-domain taxonomy that describes relationships between different entities based on items associated with the different entities published among different domains. A representation of the entity associated with the item to be placed is then identified within the multi-domain taxonomy, along with a representation of at least one similar entity. Upon identifying a similar entity, historic item placement metrics for the similar entity are leveraged to generate a placement recommendation for the received item. In some implementations, the placement recommendation is output with a visual indication of a similar entity and associated performance metrics that were considered in generating the recommended placement.

A computing system is configured to analyze historic data generated by an optimization system to provide recommended weightings for placement of creatives on publisher's pages. The weightings may be generated by providing forecasting the likelihood that a particular creative will lead to greater conversion or revenue compared to other creatives. The creatives may be grouped into one or more phases based on the amount of statistical data available for analyzing the particular creatives such that new creatives are given sufficient weighting to receive impressions despite the lack of historical data for a creative. Performance of placed creatives may be tracked by the passing of URLs with information attached to identify the particular creative and placement.