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.

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.

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.

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 110 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 120. The data-mart 110 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 130. 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 150 for an abnormality failsafe. Once processed by the local business units 150, the scenarios are presented to the advertising buyer 120.

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 110 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 120. The data-mart 110 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 130. 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 150 for an abnormality failsafe. Once processed by the local business units 150, the scenarios are presented to the advertising buyer 120.

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 110 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 120. The data-mart 110 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 130. 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 150 for an abnormality failsafe. Once processed by the local business units 150, the scenarios are presented to the advertising buyer 120.

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 110 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 120. The data-mart 110 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 130. 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 150 for an abnormality failsafe. Once processed by the local business units 150, the scenarios are presented to the advertising buyer 120.