Clear Channel Management Services, Inc.

Clear Channel Communications, Inc.

Arthur Weinberger

David R Murray

Allan Ginsburg

Jerome Williams

Marwan Shaban

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

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&#x2212;&#x3a0;(1&#x2212;(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.

Method for computing reach of an arbitrary radio advertising schedule

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-martor 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-martalso 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 unitsfor 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 systemand 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.

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Cary, NC, United States of America

Arthur Weinberger