Inventory and Revenue Maximization Method and System

• US 20110202389A1
• Filed: 04/28/2011
• Published: 08/18/2011
• Est. Priority Date: 01/15/2002
• Status: Active Grant

• Current Assignee: iHeartMedia Management Services, Inc. (iHeartMedia, Inc.)
• Original Assignee: Clear Channel Management Services LP (iHeartMedia, Inc.)
• Inventors: Ginsburg, Allan, Weinberger, Arthur, Murray, David R., Williams, Jerome
• Granted Patent: US 8,799,095 B2
• Time in Patent Office: Days
• US Class Current: 705/7.35
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 10/0875 Itemisation or classification of parts, supplies or services, e.g. bill of materials
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors
• CPC Class Codes: G06Q 30/0273 Determination of fees for advertising
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/123 Tax preparation or submission

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.

Claims

1. An advertisement inventory management system, comprising:

a performance measurement system for measuring performance of a medium selected from a group consisting of radio, television, and print, in which advertisement units are used;

a revenue maximization system which determines a price for the advertisement units based on predetermined pricing considerations wherein the revenue maximization system utilizes economic factors which influence demand and at least one measurement noise is filtered out of the economic factors;

an information storage system for receiving information from the performance measurement system and revenue maximization system to generate scenarios wherein combinations of advertisement units are grouped together to meet a buyer'"'"'s criteria wherein the buyer'"'"'s criteria includes a number of people and frequency people will be exposed to the advertisement units; and

a scenario planner to display a scenario generated by the information storage system to a prospective buyer of advertisement units.

2. The advertisement inventory management system according to claim 1, the performance measurement system receiving information related to an extent of an audience to which the advertisement units are exposed.

3. The advertisement inventory management system according to claim 1, the predetermined pricing consideration including at least three considerations selected from a group consisting of total number of unsold advertisement units, category of buyer attempting to purchase the advertisement units, the buyer'"'"'s history in purchasing similar advertisement units, and budget of a seller of the advertisement units.

4. The advertisement inventory management system according to claim 3, the revenue maximization system managing yield by using functions of sell-out forecasting, revenue forecasting, fuzzy rules, and pricing adjustment.

5. The advertisement inventory management system according to claim 1, the buyer'"'"'s criteria including a desired budget for purchase of the advertisement units, performance measurements from the performance measurement system, number of people and frequency people will be exposed to the advertisement units.

6. The advertisement inventory management system according to claim 1, the revenue maximization system changing a quantity of advertisement units available.

7. A method comprising:

at a performance measurement system, measuring performance of a communication medium in which advertisement units are used, the communication medium selected from a group consisting of radio, television, and print;

at a revenue maximization system, determining prices for the advertisement units based on predetermined pricing considerations, wherein the predetermined pricing considerations include economic factors filtered to remove measurement noise;

at an information storage system, receiving performance measurements from the performance measurement system and prices from the revenue maximization system;

at the information storage system, generating scenarios based on the performance measurements and the prices, the scenarios including combinations of the advertisement units grouped together according to criteria specified by a prospective buyer, wherein the criteria includes a number of people and a frequency at which people will be exposed to the advertisement units;

providing the scenarios generated by the information storage system to a prospective buyer.

8. The method of claim 7, comprising receiving information related to an extent of an audience to which the advertisement units are exposed.

9. The method of claim 7, the predetermined pricing considerations including at least three considerations selected from the group consisting of total number of unsold advertisement units, category of buyer attempting to purchase the advertisement units, the buyer'"'"'s history in purchasing similar advertisement units, and budget of a seller of the advertisement units.

10. The method of claim 7, the buyer'"'"'s criteria including a desired budget for purchase of the advertisement units, performance measurements, number of people and frequency people will be exposed to the advertisement units.

11. The method of claim 8, comprising managing yield by using functions of sell-out forecasting, revenue forecasting, fuzzy rules, and pricing adjustment.

12. The method of claim 7, comprising changing a quantity of advertisement units available.

13. The method of claim 7, comprising:

assigning a probability that the buyer will make a purchase from the unsold inventory; and

wherein prices for the advertisement units are based on at least the probability.

14. A computer readable medium tangibly embodying a program of computer executable instructions, the program of instructions comprising:

at least one instruction to measure performance of a communication medium in which advertisement units are used, the communication medium selected from a group consisting of radio, television, and print;

at least one instruction to determine prices for the advertisement units based on predetermined pricing considerations, wherein the predetermined pricing considerations include economic factors filtered to remove measurement noise;

at least one instruction to receive performance measurements and prices associated with the advertisement units;

at least one instruction to generate scenarios based on the performance measurements and the prices, the scenarios including combinations of the advertisement units grouped together according to criteria specified by a prospective buyer, wherein the criteria includes a number of people and a frequency at which people will be exposed to the advertisement units;

at least one instruction to provide the scenarios generated by the information storage system to a prospective buyer.

15. The computer readable medium of claim 14, the program of instructions comprising at least one instruction to receive information related to an extent of an audience to which the advertisement units are exposed.

16. The computer readable medium of claim 14, the predetermined pricing considerations including at least three considerations selected from a group consisting of total number of unsold advertisement units, category of buyer attempting to purchase the advertisement units, the buyer'"'"'s history in purchasing similar advertisement units, and budget of a seller of the advertisement units.

17. The computer readable medium of claim 14, the buyer'"'"'s criteria including the desired budget for purchase of the units, performance measurements, number of people and frequency people will be exposed to the advertisement units.

18. The computer readable medium of claim 14, the at least one instruction to determine a price including at least one instruction to manage yield by using functions of sell-out forecasting, revenue forecasting, fuzzy rules, and pricing adjustment.

19. The computer readable medium of claim 14, the at least one instruction to determine a price including at least one instruction to change a quantity of advertisement units available.

20. The computer readable medium of claim 14, the program of instructions comprising:

at least one instruction to assign a probability that the buyer will make a purchase from the unsold inventory; and

at least one instruction to determine a price for the advertisement units based on at least the probability.