System and method for media play forecasting

• US 7,676,405 B2
• Filed: 10/18/2006
• Issued: 03/09/2010
• Est. Priority Date: 06/01/2005
• Status: Expired due to Fees

• Current Assignee: LOT Network Inc.
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Bergmans, Jos, Beauchamp, Scott, Gardner, Robert, Steelberg, Ryan, Steelberg, Chad
• Primary Examiner(s): Gart, Matthew S
• Assistant Examiner(s): HAYLES, ASHFORD S
• Application Number:
  US11/550,743
• Publication Number:
  US 20070162926A1
• Time in Patent Office: 1,238 Days
• Field of Search: 705/28, 725/32, 725/34, 725/35
• US Class Current: 705/28
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: H04H 20/14 for monitoring programmes
• CPC Class Codes: H04H 60/06 Arrangements for scheduling broadcast services or broadcast-related services
• CPC Class Codes: H04L 63/0428 wherein the data content is protected, e.g. by encrypting or encapsulating the payload
• CPC Class Codes: H04L 65/762 at the source reformatting of additional data in video distribution servers H04N21/2355
• CPC Class Codes: H04L 67/53 using third party service providers
• CPC Class Codes: H04L 67/60 Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources admission control or resource allocation H04L47/70
• CPC Class Codes: H04L 67/63 Routing a service request depending on the request content or context
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• CPC Class Codes: H04N 21/25891 being end-user preferences retrieval of video data in a video database based on user preferences G06F16/739; arrangements for recognizing users' preferences H04H60/46; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/2668 Creating a channel for a dedicated end-user group, e.g. insertion of targeted commercials based on end-user profiles information retrieval from the Internet by querying with filtering and personalisation G06F16/9535; arrangements for replacing or switching information during the broadcast H04H20/10; push services over packet-switching network H04L12/1859; adaptation of message content in packet-switching networks H04L51/063

Abstract

Systems and methods are described for forecasting media play on a broadcast station. The technique involves collecting media play data from a broadcast station for a period just ended. The collected media play data is used to update historical media play data for the broadcast station. The updated historical media play data is then used to forecast spot inventory for the broadcast station for a next time period.

Claims

1. A computer-implemented method of forecasting inventory for media play on a broadcast station, the method comprising:

collecting, by an updater module executing on one or more processors, media play data for a previous time period just ended; and

updating, by the updater module, a set of historical media play data, stored by a data store, based on the collected media play data;

automatedly generating, by a forecast engine module executing on the one or more processors, inventory forecast based on the updated historical media play data and a schedule of the broadcast station for a next time period, wherein the inventory forecast includes an estimated number of spots available for media play on the broadcast station during the next time period;

adjusting, by a manager module executing on the one or more processors, spots available for media play during the next time period based on the inventory forecast, wherein the adjusting comprises adjusting a play time of a spot for media play; and

pricing, by the manager module, the spots available for media play during the next time period based on a result of the adjusting.

2. The computer-implemented method of claim 1, wherein the automatedly generating the inventory forecast is dependent on a business input.

3. The computer-implemented method of claim 1, wherein the automatedly generating the inventory forecast is dependent on a media play format of the broadcast station.

4. The computer-implemented method of claim 1, wherein the adjusting further comprises at least one of adding a spot for media play, and removing a spot for media play.

5. The computer-implemented method of claim 1, wherein the updating comprises:

computing a historical average based on the collected media play data, wherein the historical average is for at least one of a day, a week, and a month.

6. The computer-implemented method of claim 1, wherein the collecting occurs regularly.

7. The computer-implemented method of claim 1, further comprising:

determining a reliability of the inventory forecast based on the collected media play data and a previous inventory forecast.

8. The computer-implemented method of claim 1, further comprising:

providing the inventory forecast to a station inventory manager, wherein the station inventory manager assigns a spot in the inventory forecast to an advertising campaign for subsequent media play.

9. The computer-implemented method of claim 1, wherein the automated inventory forecast is dependent on a type of broadcast station for which the automated inventory forecast is provided.

23. The method of claim 1, wherein the previous time period comprises a time interval since the forecast engine module has automatedly generated a previous inventory forecast.

24. The method of claim 1, wherein the previous time period has a predetermined duration.

25. The method of claim 24, wherein the predetermined duration of the previous time period comprises one day.

26. The method of claim 1, wherein the next time period comprises one of a day, a week, a month, and a year.

27. The method of claim 1, wherein the automatedly generating by the forecast engine module of inventory forecast for a given daypart is based on:

a historical spot average for the given daypart,

a historical spot average for a given week of a given month to which the forecasted daypart belongs, and

a historical spot average for the given month to which the forecasted daypart belongs, wherein

the historical spot averages are estimated over the previous time period.

10. A system for media play on a broadcast station, comprising:

a manager module arranged to invoke a mechanism for forecasting inventory for media play;

a data store arranged to store historical media play data for the broadcast station;

an updater module arranged to receive media play data for a previous time period just ended, wherein the updater module is further arranged to update the historical media play data with the received media play data; and

a forecast engine module arranged to generate the inventory forecast based on the updated historical media play data and a schedule of the broadcast station for a next time period, wherein the inventory forecast includes an estimated number of spots available for media play on the broadcast station during the next time period, wherein

the manager module is further arranged to;

adjust spots available for media play based on the inventory forecast, and wherein the adjustment comprises adjustment to a play time of a spot for subsequent media play; and

price the spots available for media play during the next time period based the adjustment.

11. The system of claim 10, wherein the forecast engine module is further arranged to generate the inventory forecast based on a business input.

12. The system of claim 10, wherein the manager module is further arranged to compute a reliability of at least part of the inventory forecast based on the received media play data and a previous inventory forecast.

13. The system of claim 10, wherein the historical media play data comprises media play spot averages for at least one of a previous day corresponding to the day for which the inventory forecast is generated, a previous week containing the previous day, and a previous month containing the previous week.

14. The system of claim 10, wherein the adjustment further comprises at least one of addition of a spot for subsequent media play, and removal of a spot from media play.

15. The system of claim 10, wherein the inventory forecast is dependent on ownership of media play spots by an entity other than the broadcast station.

28. The system of claim 10, wherein the previous time period comprises a time interval since the forecast engine module has automatedly generated a previous inventory forecast.

29. The system of claim 10, wherein the previous time period has a predetermined duration.

30. The system of claim 10, wherein the predetermined duration of the previous time period comprises one day.

31. The system of claim 10, wherein the next time period comprises one of a day, a week, a month, and a year.

32. The system of claim 10, wherein the forecast engine module is arranged to automatedly generate the inventory forecast for a given daypart based on:

a historical spot average for the given daypart,

a historical spot average for a given week of a given month to which the forecasted daypart belongs, and

a historical spot average for the given month to which the forecasted daypart belongs, wherein

the historical spot averages are estimated over the previous time period.

16. A computer-readable medium having instructions stored therein and executable by a processor, the instructions comprising instructions to:

receive, by an updater module, media play data for a broadcast station for a first time period;

update, by the updater module, a store of historical media play data for the broadcast station based on the received media play data;

automatedly generate, by a forecast engine module, inventory forecast based on a schedule of the broadcast station for a next time period and further based on the updated historical media play data, wherein the inventory forecast includes an estimated number of spots available for media play on the broadcast station during the next time period;

adjust, by a manager module, media play spots based on the inventory forecast, wherein the adjustment comprises adjustment of a play time of a spot for subsequent media play; and

price, by the manager module, the spots available for media play during the next time period based on the adjustment.

17. The computer-readable medium of claim 16, further comprising instructions to:

compute a confidence factor for the inventory forecast based on the received media play data and a previous inventory forecast.

18. The computer-readable medium of claim 16, the instructions to adjust media play spots further comprising instructions to:

at least one of add a spot for media play, and remove a spot from media play.

19. The computer-readable medium of claim 16, wherein the instructions to update comprise instructions to at least one of:

calculate a spot average of a previous same day as a day for which the inventory forecast is to be generated;

calculate a spot average of a previous week containing the day; and

calculate a spot average of a previous month containing the week.

20. The computer-readable medium of claim 16, wherein the instructions to automatedly generate inventory forecast are dependent on ownership of media play spots by an entity other than the broadcast station.

21. The computer-readable medium of claim 16, wherein the instructions to update are at least one of systematically invoked, manually invoked, and dynamically invoked.

22. The computer-readable medium of claim 16, wherein the instructions to automatedly generate inventory forecast are dependent on a media play format of the broadcast station.

33. The computer-readable medium of claim 16, wherein the first time period comprises a time interval since the forecast engine module has automatedly generated a previous inventory forecast.

34. The computer-readable medium of claim 16, wherein the first time period has a predetermined duration.

35. The computer-readable medium of claim 34, wherein the predetermined duration of the first time period comprises one day.

36. The computer-readable medium of claim 16, wherein the next time period comprises one of a day, a week, a month, and a year.

37. The computer-readable medium of claim 16, wherein the instructions to automatedly generate the inventory forecast for a given daypart are based on:

a historical spot average for the given daypart,

a historical spot average for a given week of a given month to which the forecasted daypart belongs, and

a historical spot average for the given month to which the forecasted daypart belongs, wherein

the historical spot averages are estimated over the first time period.