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A method is provided for enterprise management and bundling of radio, outdoor and entertainment inventory to achieve maximum revenue on perishable products. An electronic data-mart or central information storage and data processing system is established to collect influencing factors for the probability and price sensitivity of a particular advertising buyer. The data-mart also collects business rules for inventory scaling, available inventory to sell, budget (goal) information, advertiser payment history, and station performance data to feed to a scenario planner. Once three or more variables exist, inventory and pricing fuzzy logic algorithms create scenario plans to present the most profitable bundle of offerings. The scenarios are typically pre-approved although presented to the local business units for an abnormality failsafe. Once processed by the local business units , the scenarios are presented to the advertising buyer.
Method For Computing Reach Of An Arbitrary Radio Advertising Schedule
Arthur Weinberger - Sunnyvale CA, US Marwan Shaban - Saint Cloud FL, US
Assignee:
Clear Channel Management Services, Inc. - San Antonio TX
International Classification:
G06Q 10/00 G06Q 30/00 H04H 60/33
US Classification:
705 729, 705 144, 455 201, 725 10
Abstract:
A radio station market analysis program extends Cume values for individual stations to multiple stations (for a particular geographic market, a particular demographic, and a particular daypart) according to the formula C=[1−Π(1−(C/P))]*P, where n is the number of media stations, P is the population, and Cis each Cume value. Cume values may be provided for a limited set of input dayparts from Arbitron and Nielson, and are translated to an arbitrary daypart. The arbitrary daypart can represent a sum of component dayparts in a proposed advertising schedule. The reach of the proposed advertising schedule can be further computed based on a hyperbolic function of spot count.
Inventory And Revenue Maximization Method And System
Allan Ginsburg - Rockville MD, US David Murray - Winter Garden FL, US Arthur Weinberger - Cary NC, US Jerome Williams - Durham NC, US
Assignee:
Clear Channel Communications, Inc. - San Antonio TX
International Classification:
G06F017/60
US Classification:
705/028000
Abstract:
A method is provided for enterprise management and bundling of radio, outdoor and entertainment inventory to achieve maximum revenue on perishable products. An electronic data-mart or central information storage and data processing system is established to collect influencing factors for the probability and price sensitivity of a particular advertising buyer . The data-mart also collects business rules for inventory scaling, available inventory to sell, budget (goal) information, advertiser payment history, and station performance data to feed to a scenario planner . Once three or more variables exist, inventory and pricing fuzzy logic algorithms create scenario plans to present the most profitable bundle of offerings. The scenarios are typically pre-approved although presented to the local business units for an abnormality failsafe. Once processed by the local business units , the scenarios are presented to the advertising buyer . Negotiations typically take place which cause for the process to restart. The main systems that interact to build these scenarios are: an enterprise data-mart , a scenario planner , a performance measure system , a rate or yield management subsystem , a traffic and accounts receivable system and a similarly configured local inventory booking system . A business rules engine provides the local rule definitions for scaling inventory and price to provide for the most profitable combination.
Inventory And Revenue Maximization Method And System
Allan Ginsburg - Rockville MD, US David R. Murray - Winter Garden FL, US Arthur Weinberger - Cary NC, US Jerome Williams - Durham NC, US
Assignee:
CLEAR CHANNEL MANAGEMENT SERVICES, INC. - San Antonio TX
International Classification:
G06Q 10/00
US Classification:
705 735
Abstract:
A method is provided for enterprise management and bundling of inventory to maximize revenue on perishable products. An electronic data-mart collects factors for the probability and price sensitivity of a buyer. The data-mart also collects rules for inventory scaling, available inventory to sell, budget (goal) information, advertiser payment history, and station performance data to feed to a scenario planner. Once three or more variables exist, algorithms create scenario plans to present the most profitable bundle of offerings. The scenarios are typically pre-approved although presented to local business units for an abnormality failsafe. Once processed by local business units, the scenarios are presented to the buyer. Negotiations typically cause the process to restart. The main systems that interact to build scenarios are: an enterprise data-mart, a scenario planner, a performance measurement system, a rate or yield management subsystem, a traffic and accounts receivable system, and a local inventory booking system.
Inventory And Revenue Maximization Method And System
Allan Ginsburg - Rockville MD, US David R. Murray - Winter Garden FL, US Arthur Weinberger - Cary NC, US Jerome Williams - Durham NC, US
Assignee:
CLEAR CHANNEL MANAGEMENT SERVICES, INC. - San Antonio TX
International Classification:
G06Q 30/00
US Classification:
705 1469
Abstract:
A method is provided for enterprise management and bundling of inventory to maximize revenue on perishable products. An electronic data-mart collects factors for the probability and price sensitivity of a buyer. The data-mart also collects rules for inventory scaling, available inventory to sell, budget (goal) information, advertiser payment history, and station performance data to feed to a scenario planner. Once three or more variables exist, algorithms create scenario plans to present the most profitable bundle of offerings. The scenarios are typically pre-approved although presented to local business units for an abnormality failsafe. Once processed by local business units, the scenarios are presented to the buyer. Negotiations typically cause the process to restart. The main systems that interact to build scenarios are: an enterprise data-mart, a scenario planner, a performance measurement system, a rate or yield management subsystem, a traffic and accounts receivable system, and a local inventory booking system.
Arthur Weinberger - Sunnyvale CA, US Sergio Marti - Sunnyvale CA, US Yegor Gennadiev Jbanov - Mountain View CA, US Liya Su - Sunnyvale CA, US Mohammadinamul Hasan Sheik - Santa Clara CA, US Anusha Iyer - Santa Clara CA, US
International Classification:
G06F 3/01
US Classification:
345156
Abstract:
A computerized method, system for, and computer-readable medium operable to: determine a set of coordinates corresponding to a user's gaze; determine a user interface (UI) element corresponding to the set of coordinates; return that UI element as being detected and again repeating the determination of the set of coordinates corresponding to the user's gaze; determine if the UI element being returned is the same for a predetermined threshold of time according to a started timer; if the UI element is not the same, reset the started timer and again repeating the determination of the set of coordinates corresponding to the user's gaze; and if the UI element is the same, making the UI element active without requiring any additional action from the user and currently selecting the UI element to receive input.
- Mountain View CA, US John Charles Simone - Sunnyvale CA, US Breen Baker - Redwood City CA, US Aaron Malenfant - Redwood City CA, US Arthur Weinberger - Santa Clara CA, US Jason Fedor - Sunnyvale CA, US Madhu Kallazhi Vasu - Mountain View CA, US Sean Michael Harrison - Seattle WA, US Jackson Roberts - Seattle WA, US
International Classification:
G06F 21/64 H04L 9/32 G06F 21/60
Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that protect analytics for resources of a publisher from traffic directed to such resources by malicious entities. An analytics server receives a first message that includes an encrypted token and analytics data for a publisher-provided resource. The token includes a portion of the analytics data and a trust score indicating a likelihood that activity on the resource is attributed to a human (rather than an automated process). The analytics server decrypts the token. The analytics server determines a trustworthiness measure for the analytics data included in the first message based on the trust score (in the decrypted token) and a comparison of the analytics data in the first message and the portion of the analytics data (in the decrypted token). Based on the measure of trustworthiness, the analytics server performs analytics operations using the analytics data.