Methods and apparatus to generate audience metrics using third-party privacy-protected cloud environments. In some examples, an apparatus comprising a model generator to generate an individualization model based on truth data indicating first true users exposed to media via first panelist client devices, a model analyzer to produce user probabilities for second panelist client devices based on the individualization model, the user probabilities indicating likelihoods of second true users being exposed to media via the second panelist client devices, a data modifier to: select a user probability from the user probabilities based on an impression, the impression associated with at least one feature and a selected device from the second panelist client devices, the user probability associated with the at least one feature and the selected device, the user probability indicating a likelihood of a set of second true users being exposed to media corresponding to the impression via the selected device, and assign the impression to the set of second true users.

A method for attribution determination in a system including a plurality of vehicles having exteriors configured to convey messaging to occupants of other vehicles. Communication signals including information relating to time-stamped locations of the vehicles are received. Time-stamped location data including a plurality of the time-stamped locations is provided to a mobile location data aggregator. Anonymized identifiers associated with mobile device users within exposure zones associated with the time-stamped locations are received from the mobile location data aggregator. A control set of anonymized identifiers associated with users within a geo-fenced area but not within the exposure zones is also received. A record of conversion events is compiled. The conversion events include a first set of conversion events performed by the exposed audience and a second set of conversion events performed by the control audience. An attribution metric is determined based upon the first and second sets of conversion events.

A method of selecting and presenting content based on learned user preferences is provided. The method includes providing a content system including a set of content items organized by genre characterizing the content items, and wherein the set of content items contains microgenre metadata further characterizing the content items. The method also includes receiving search input from the user for identifying desired content items and, in response, presenting a subset of content items to the user. The method further includes receiving content item selection actions from the user and analyzing the microgenre metadata within the selected content items to learn the preferred microgenres of the user. The method includes, in response to receiving subsequent user search input, selecting and presenting content items in an order that portrays as relatively more relevant those content items containing microgenre metadata that more closely match the learned microgenre preferences of the user.

A subscription-based system for providing commerce information for one or more mobile devices for one or more merchants. Some techniques employed feature a subscription-based method for presenting commercial resources to a mobile device. The method involves receiving mobile device user information relating to a geographic location to locate one or more merchants within a subscription-based shopping network, and receiving mobile device user information relating to a merchant type within the subscription-based shopping network. The method also involves receiving, from a database over a communication network, information for one or more merchants associated with the mobile device user information for the geographic location and the merchant type, and presenting the associated merchant information on the mobile device. The associated merchant information can include a merchant name and address, a merchant telephone number, a merchant advertisement, a merchant coupon, or a merchant product or service offering to subscribers of the shopping network.

Example methods and apparatus for associating media devices with a demographic composition of a geographic area are disclosed. Disclosed example apparatus are to obtain a plurality of Internet Protocol addresses assigned to a media device associated with a panel member. Disclosed example apparatus are also to determine a most used Internet Protocol address from the plurality of Internet Protocol addresses, determine a geographic location corresponding to the most used Internet Protocol address, associate a geographic area with the media device in response to a determination that the geographic location corresponds to a location of an internet service provider, determine a demographic profile associated with the geographic area, and associate the demographic profile with the media device.

Various embodiments of the present technology generally relate to data delivery. More specifically, some embodiments of the present technology relate to systems and methods for using spatial and temporal analysis to associate data sources with mobile devices. The delivery of data to support a wide variety of services for and about mobile devices that are based on data stored in corporate, commercial, and government databases which is not currently linked to individual mobile devices. Some embodiments allow advertisers to better target their ads to relevant target audience with greater accuracy.

Systems and methods for on demand local commerce are described. One example embodiment includes a device gathering location information and product interest associated with clients and client devices. The system may use location information in determining that the first plurality of client devices are within a first geographic area during a first time period, and may further use the interest information in calculating an interest level for a first product. A threshold may be identified and used in determining that the interest level for the first product exceeds the threshold. When the calculated interest level exceeds the threshold, a local commerce action is initiated. In various embodiments, the local commerce action may be a live on demand auction at a particular location, an offer associated with a geofenced area, a sales location recommendation to a merchant, or any other such local commerce action.

A social networking system receives information describing locations associated with a plurality of its users. Based on information identifying each user and a location associated with each user, the social networking system generates and stores hash values. For example, the social networking system maintains various geo-tiles that each identify geographic areas and generates a hash value based on a user identifier and an identifier of a geo-tile including the location associated with the user. Based on the hash values and locations associated with one or more users, the online system determines a number of unique users associated with locations included in a geographic region. When determining the number of unique users, the online system accounts for a rate at which the online system updates location information associated with various users.

The disclosed technology includes system and method for impressing publicly displayed information on mobile devices. The method comprises determining at least a first place and a second place for a mobile device based on locations associated with the mobile device. Each of the first place and the second place being a place where the mobile device is regularly located as indicated by densities of the locations mapped over a geographical region and the corresponding time stamps. The first place and second place are used to determine one or more travel routes routinely taken by a user of the mobile device, and to build an association database, where the mobile device is associated with one or more information documents, each of the one or more information documents including information publicly displayed along the one or more routes.

To determine an impression metric for an organization, a server device generates a statistical model for estimating the impression metric using machine learning techniques. The server device obtains training data for the statistical model by randomly selecting geographic locations within a geographic area and determining the number of users eligible to receive a particular type of advertisement for each randomly selected geographic location. For example, a user may be deemed eligible when displaying the geographic location via a mapping application. When an organization requests an estimate of a number of impressions for an advertising campaign, the server device applies data included in the request (e.g., the time period for the advertising campaign, the number of organization locations, identifiers for the organization locations such as geographic coordinates or an address, etc.) to the statistical model to estimate an impression metric for the organization.