Techniques are described for determining visit locations on a per-user basis. In a disclosed method, user-location data, from a plurality of distinct data sources, is received over one or more network systems. The user-location data includes a plurality of user-location records and indicate visits made by the plurality of users to the plurality of locations. Each user-location record includes at least: user-identification data that uniquely identifies a user; location data that identifies a location visited by the user identified in the user-location record; and time data that indicates when the user identified in the user-location record visited the location identified ion the user-location record. Based on the plurality of user-location records, for each user of the plurality of users, whether any location visited by the user qualifies as a home-location for the user is determined. Locations visited by each user that do not quality as the home-location for the user are away-locations of the user.

An audience measurement computing system for monitoring a media presentation device in a monitored environment is described and includes a network interface, at least one processor, and a non-transitory computer-readable medium comprising instructions executable by the processor(s). The computing system is configured to obtain, via a cable connected to an input port of the media presentation device, a voltage signal generated by the media presentation device based on an operational state of the media presentation device; compare voltage indicated by the voltage signal to a threshold; based on the comparing, generate timestamped operational state data comprising a record indicative of when the media presentation device is in an on-state; obtain audience measurement data representing one or more media signals communicated to the media presentation device; and transmit, via the network interface over a network and to a central facility, the timestamped operational state data and the audience measurement data.

Methods and apparatus to estimate census-level audience sizes and duration data across dimensions and/or demographics are disclosed. An example apparatus includes constraint equation control circuitry to select at least one constraint equation corresponding to one or more events, the one or more events corresponding to first audience members and second audience members, the first audience members to include the second audience members, constraint parameter estimation circuitry to solve the at least one constraint equation to determine one or more constraint parameter values, the one or more constraint parameter values corresponding to the one or more events, and output generation circuitry to determine, based on one or more intermediate equations and the one or more constraint parameter values, an event audience size and an event duration corresponding to (a) the first audience members and (b) a combination of the one or more events and one or more demographics.

A system is provided for cross-platform proposal creation, optimization, and deal management. The system generates a proposal plan corresponding to a distribution of target audience across a set of delivery platforms based on an adjustment of a request parameter associated with a request. The proposal plan is executed for a first time period in a flight on a first delivery platform from the set of delivery platforms based on a plurality of client-defined requirements corresponding to the request. The proposal plan is optimized for a second time period in the flight by an in-flight re-distribution of the target audience across the set of delivery platforms. Execution of the optimized proposal plan is controlled for the second time period in the flight on the first delivery platform.

Systems and methods for content selection and presentation are disclosed. Training data including indicating one or more interactions with one or more content elements and associated with one of a plurality of individual contexts is received. A selection model is trained by applying a reinforcement learning mechanism and an individual explore-exploit mechanism. A context for a user is selected by applying the selection model, which is configured to determine an expected future reward value of at least one of the plurality of individual contexts, determine an expected future reward value of a global context based on a past click-through rate, a reward value, and a future click-through rate, and, select the global context or one of the one or more individual contexts based on a comparison of the expected future reward values.

A method is disclosed for tracking advertisement effectiveness. First information associated with desired advertising information is broadcast from at least one of a plurality of fixed information nodes. A mobile unit receives the broadcast information and outputs the desired advertising information. An advertisement counter is started at the time of receipt of the broadcast information and presence information is broadcast from at least one of a plurality of fixed monitoring nodes over a restricted broadcast range, which at least one fixed monitoring node is disposed in a predetermined fixed physical proximity with a vendor location. The broadcast presence information is received at the mobile unit and a presence counter is started in response to receipt of the presence information. At the mobile unit loss of receipt of the broadcast presence information, the presence counter is stopped.

A system and methods are disclosed for scoring audience responsiveness or exposure to viewing of paid content or advertising via connected television devices (CTV) and/or over-the-top (OTT) delivery mechanisms. The scoring system and method determines relevant data and creates and records the relevant data in an Ad Exposure File and an Advertiser Outcome File and at regular intervals compares them to identify matches via overlapping combinations of IP Address/DID, Timestamp (for confirmation of appropriate recency) and recording a conversion event to the Exposed Household Record. of the appropriate household on the Ad Exposure File.

Aspects of the present disclosure involve a system and a method for performing operations comprising: receiving, by a messaging application, content from a given user; selecting a metric for measuring performance of the content on the messaging application; measuring performance of the content on the messaging application; computing a value of the performance of the content on the messaging application based on the selected metric; and updating a restricted use token wallet stored in a profile for the given user based on the computed value of the performance of the content.

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: receiving transaction data comprising items previously purchased; comparing the first item to the second item; identifying the first item to be related to the second item; aggregating the first product type and the second product type into a first category bundle having a first theme defined by the first and second product types; assigning a first affinity score to the first and second items based on the transaction data; detecting the first item as being a first item of interest; and when the first affinity score of the first item exceeds a threshold, displaying, to the user while browsing the one or more websites, the first category bundle comprising the first and second items. Other embodiments are described.

A performance internet marketing self-optimizing, anthropomorphic, artificial intelligence-based system and method to quote, compare and purchase benefits products from a benefits provider. The system and method collects information from an online advertising platform during the process and returns the collected information to the online advertising platform for optimization of the online advertising platform.