Abstract: Aggregating viewership data is disclosed. Initially, household viewership data assigned to a tuning event in multiple households is accessed. Then, the household viewership data for the tuning event in the multiple households representing the same episode is aggregated to generate episode viewership data. Next, episode viewership data representing multiple episodes of the same program is aggregated to generate program viewership data. Next, the program viewership data for multiple programs of the same network is aggregated to generate network viewership data. Finally, the network viewership data for multiple commonly-owned networks is aggregated to generate entity viewership data.

Abstract: An identifier associated with a client machine is accessed, and parameters that define a control group of client machines for a particular advertising campaign are accessed. The advertising campaign is associated with one or more standard advertisements. Whether the client machine is a member of the control group based on the identifier associated with the client machine and the parameters that define the control group is determined. If the determination of whether the client machine is a member of the control group indicates that the client machine is a member of the control group, a control advertisement is caused to be presented on the client machine. The control advertisement is an advertisement not associated with the advertising campaign.

Abstract: Determining the effectiveness of an advertising campaign includes determining metrics that indicate the relative effectiveness of the different elements of the campaign. A model may be generated by the system using information about the manner in which consumers are exposed to advertisements. The information, for example, can include a history of exposures to advertisements in the campaign that occur before a user submits input, such as a survey response. In addition, the information also can include a history of exposures to advertisements in the campaign that occur after the user submits input, such as a survey response. As a result, the effectiveness can be distributed across multiple exposures experienced by consumers rather than a single exposure.

Abstract: Several ways of identifying users and collecting demographic information and market information are disclosed, including branding a browser with a unique identification in each user request, identifying a user by his key strokes or mouse clicks, gathering demographic information using multiple data sets and by monitoring network traffic. Additionally, user requested content is distinguished from other, non-user content, and the performance of a server can be monitor and analyzed from a client a client perspective. Further, an Internet user's Internet data is routed to a known domain on the Internet, from which it is routed on to the intended recipient. The domain includes proxy servers which proxy the user's data requests to the domain, and database servers, which filter and build a database of the user's Internet usage. Particular data concerning certain behaviors of interest, such as purchasing data, is filtered into the database, and can form the basis for numerous market measures.

Abstract: Aggregating viewership data is disclosed. Initially, household viewership data assigned to a tuning event in multiple households is accessed. Then, the household viewership data for the tuning event in the multiple households representing the same episode is aggregated to generate episode viewership data. Next, episode viewership data representing multiple episodes of the same program is aggregated to generate program viewership data. Next, the program viewership data for multiple programs of the same network is aggregated to generate network viewership data. Finally, the network viewership data for multiple commonly-owned networks is aggregated to generate entity viewership data.

Abstract: Systems and methods for estimating media audience are disclosed. In one aspect, a method includes receiving a media signal to be transmitted via a media distribution system, the media signal including multiple pieces of media content that each contain video and audio signals. One of the multiple pieces of media content within the received media signal are identified. It is determined that the identified piece of media content exceeds a threshold length, and, in response to determining that the identified piece of media content exceeds a threshold length, the audio signal of the identified piece of media content is encoded with a sequence of discrete codes. Each discrete code has a period that includes a set of sequential frequency components imperceptible to humans. The threshold length is greater than the period of a discrete code multiplied by the number of discrete codes in the sequence.

Abstract: Tuning data representing a television viewing event associated with a particular household is accessed. Household member data representing information on individual members of the particular household is accessed. Viewing profile data representing information on individual members of other households regarding viewership by the individual members of the other households is accessed. Fractional viewership values for the individual members of the particular household are determined based on the tuning data, the household member data, and the viewing profile data. Household viewership data is determined based on the fractional viewership values.

Abstract: A copy of a request for content from a content provider is initially received from a client device. The copy of the request indicates a unique identifier of the client device, an originating network address of the client device, and a destination network address of the content provider. The client device is associated with a network provider based on the originating network address. It is determined that the network provider belongs to a predetermined class. Activation of a private network switch is enabled on the client device to provide an encrypted connection between the client device and a private network server before the request is forwarded to the content provider based on the determination that the network provider belongs to the predetermined class.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for audience measurement using a mobile device accessory are disclosed. In one aspect, a mobile device accessory includes a power source configured to provide power to the mobile device. The mobile device accessory further includes an audio capturing device configured to capture an ambient sound, and a microprocessor coupled to the audio capturing device and configured to identify distinctive features of the ambient sound and generate a digital representation of the ambient sound. The mobile device accessory further includes a memory coupled to the microprocessor and configured to store at least the digital representation, and a transmitter coupled to the microprocessor and configured to transmit at least the digital representation.

Abstract: Requests for data received from multiple subscribers are accessed. At least some of the requests for data originate from one or more addresses associated with a particular subscriber of the multiple subscribers. The accessed requests for data are organized into sets of requests based on the one or more addresses such that a set of requests corresponds to the particular subscriber, and a characteristic of the particular subscriber is determined based on aspects of the set of requests corresponding to the particular subscriber and a behavior model.

Abstract: Tuning data representing a television viewing event associated with a particular household is accessed. Household member data representing information on individual members of the particular household is accessed. Viewing profile data representing information on individual members of other households regarding viewership by the individual members of the other households is accessed. Fractional viewership values for the individual members of the particular household are determined based on the tuning data, the household member data, and the viewing profile data. Household viewership data is determined based on the fractional viewership values.

Abstract: A copy of a request for content from a content provider is initially received from a client device. The copy of the request indicates a unique identifier of the client device, an originating network address of the client device, and a destination network address of the content provider. The client device is associated with a network provider based on the originating network address. It is determined that the network provider belongs to a predetermined class. Activation of a private network switch is enabled on the client device to provide an encrypted connection between the client device and a private network server before the request is forwarded to the content provider based on the determination that the network provider belongs to the predetermined class.

Abstract: Tuning data representing a television viewing event associated with a particular household is accessed. Household member data representing information on individual members of the particular household is accessed. Viewing profile data representing information on individual members of other households regarding viewership by the individual members of the other households is accessed. Fractional viewership values for the individual members of the particular household are determined based on the tuning data, the household member data, and the viewing profile data. Household viewership data is determined based on the fractional viewership values.

Abstract: The present disclosure describes techniques for projecting person-level viewership from household-level tuning events. One example method includes accessing tuning data representing television tuning events associated with particular households; accessing panelist viewing data representing television viewing events associated with panelists; and for at least one tuning event represented by the tuning data: accessing household member data associated with the tuning event; determining a member minutes value associated with each individual member of the particular household for the tuning event; and determining a fractional viewership value for each individual member of the particular household associated with the tuning event.

Abstract: The present disclosure describes techniques for projecting person-level viewership from household-level tuning events. One example method includes accessing tuning data representing television tuning events associated with particular households; accessing panelist viewing data representing television viewing events associated with panelists; and for at least one tuning event represented by the tuning data: accessing household member data associated with the tuning event; determining a member minutes value associated with each individual member of the particular household for the tuning event; and determining a fractional viewership value for each individual member of the particular household associated with the tuning event.

Abstract: Tuning data representing a television viewing event associated with a particular household is accessed. Household member data representing information on individual members of the particular household is accessed. Viewing profile data representing information on individual members of other households regarding viewership by the individual members of the other households is accessed. Fractional viewership values for the individual members of the particular household are determined based on the tuning data, the household member data, and the viewing profile data. Household viewership data is determined based on the fractional viewership values.

Abstract: An identifier associated with a client machine is accessed, and parameters that define a control group of client machines for a particular advertising campaign are accessed. The advertising campaign is associated with one or more standard advertisements. Whether the client machine is a member of the control group based on the identifier associated with the client machine and the parameters that define the control group is determined. If the determination of whether the client machine is a member of the control group indicates that the client machine is a member of the control group, a control advertisement is caused to be presented on the client machine. The control advertisement is an advertisement not associated with the advertising campaign.

Abstract: Requests for data received from multiple subscribers are accessed. At least some of the requests for data originate from one or more addresses associated with a particular subscriber of the multiple subscribers. The accessed requests for data are organized into sets of requests based on the one or more addresses such that a set of requests corresponds to the particular subscriber, and a characteristic of the particular subscriber is determined based on aspects of the set of requests corresponding to the particular subscriber and a behavior model.

Abstract: An identifier associated with a client machine is accessed, and parameters that define a control group of client machines for a particular advertising campaign are accessed. The advertising campaign is associated with one or more standard advertisements. Whether the client machine is a member of the control group based on the identifier associated with the client machine and the parameters that define the control group is determined. If the determination of whether the client machine is a member of the control group indicates that the client machine is a member of the control group, a control advertisement is caused to be presented on the client machine. The control advertisement is an advertisement not associated with the advertising campaign.

Abstract: Several ways of identifying users and collecting demographic information and market information are disclosed, including branding a browser with a unique identification in each user request, identifying a user by his key strokes or mouse clicks, gathering demographic information using multiple data sets and by monitoring network traffic. Additionally, user requested content is distinguished from other, non-user content, and the performance of a server can be monitor and analyzed from a client a client perspective. Further, an Internet user's Internet data is routed to a known domain on the Internet, from which it is routed on to the intended recipient. The domain includes proxy servers which proxy the user's data requests to the domain, and database servers, which filter and build a database of the user's Internet usage. Particular data concerning certain behaviors of interest, such as purchasing data, is filtered into the database, and can form the basis for numerous market measures.