Television Traffic Estimation

• US 20090150224A1
• Filed: 12/10/2008
• Published: 06/11/2009
• Est. Priority Date: 12/10/2007
• Status: Abandoned Application

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google LLC (Alphabet Inc.)
• Inventors: Lu, Jeff T., Bridgwater, Thomas B., Bhambani, Ajoy
• Application Number:
  US12/332,024
• Publication Number:
  US 20090150224A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0226 Incentive systems for frequent usage, e.g. frequent flyer miles programs or point systems
• CPC Class Codes: G06Q 30/0283 Price estimation or determination

Abstract

A computer-implemented advertising management process includes receiving one or more indicators for a daypart or network on which to run a broadcast advertisement, and a proposed impression-based payment amount for running the advertisement, identifying one or more historical advertisement slots associated with the one or more indicators and applying the impression-based payment amount to advertising data for the one or more historical advertisement slots, and reporting an estimated advertising cost of running the advertisement using the impression-based payment amount and impression estimates derived from the advertising data for the one or more historical advertisement slots.

Claims

1. A computer-implemented advertising management process, comprising:

receiving one or more indicators for a daypart or network on which to run a broadcast advertisement, and a proposed impression-based payment amount for running the advertisement;

identifying one or more historical advertisement slots associated with the one or more indicators and applying the impression-based payment amount to advertising data for the one or more historical advertisement slots; and

reporting an estimated advertising cost of running the advertisement using the impression-based payment amount and impression estimates derived from the advertising data for the one or more historical advertisement slots.

2. The method of claim 1, wherein the historical advertisement slots match the received daypart.

3. The method of claim 2, wherein the historical advertisement slots match the received network.

4. The method of claim 1, wherein the historical advertisement slots match a program associated with the received daypart and network, and an episode of a program having a close match to the daypart or network.

5. The method of claim 1, wherein applying the impression-based payment amount to advertising data for the one or more historical advertisement slots comprises submitting the payment amount against payment amounts for advertisements that ran in the one or more historical advertisement slots to determine an auction-based payment amount for running the advertisement.

6. The method of claim 5, further comprising, multiplying the auction-based payment amount by an impressions level corresponding to the one or more historical advertisement slots.

7. The method of claim 6, wherein the one or more historical advertisement slots comprise an advertisement pod having approximately the same daypart as the received daypart, on the received network.

8. The method of claim 6, wherein the impressions level is computed by adjusting a number of impressions for the one or more historical advertisement slots by a seasonal modifier.

9. The method of claim 1, further comprising generating a bid estimate for providing a determined likelihood of winning an auction for the received daypart or network, using bids of advertisements that ran in the one or more historical advertisement slots.

10. The method of claim 9, wherein generating the bid estimate comprises computing a value between a highest and a lowest bid of advertisements that ran in the one or more historical advertisement slots.

11. The method of claim 1, further comprising determining a charge for an advertiser using a bid winning amount that is based on the impression-based payment amount, multiplied by measured, actual estimated impressions of the advertisement.

12. The method of claim 11, wherein the determined charge is capped at an amount higher than the bid amount multiplied by the estimated impressions.

13. A computer-implemented advertising cost estimation system, comprising:

an ad estimator interface to receive user input regarding advertising slots for the display of future advertisements, and bid amounts associated with the future advertisements;

a historical impressions database storing impressions data associated with timeslots and networks; and

a viewer estimator adapted to identify historical data, in the historical impressions database, associated with the user input regarding advertising slots, and to estimate a number of impressions for the future advertisements using the historical data.

14. The system of claim 13, wherein the timeslots in the historical impressions database correspond to advertising pods.

15. The system of claim 14, wherein the viewer estimator is adapted to compute an average impression level for a pod corresponding to the advertising slot.

16. The system of claim 13, further comprising an auction simulator adapted to apply the bid amounts associated with the future advertisements against bid amounts from the historical impressions database to determine an advertising position for the future advertisements.

17. The system of claim 13, further comprising an auction simulator adapted to compute a suggested bid amount that is likely to generate a winning bid for the future advertisements.

18. A computer-implemented advertising cost estimation system, comprising:

an ad estimator interface to receive user input regarding advertising slots for the display of future advertisements, and bid amounts associated with the future advertisements;

a historical impressions database storing impressions data associated with timeslots and networks; and

means for computing estimated impression-based costs for the future advertisements.