Methods and apparatus to calculate video-on-demand and dynamically inserted advertisement viewing probability

• US 9,544,632 B2
• Filed: 02/16/2016
• Issued: 01/10/2017
• Est. Priority Date: 02/11/2014
• Status: Active Grant

• Current Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Original Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Inventors: Wood, Benjamin, Coughlin, John Charles, Poppie, Molly, Kramer, Marie, Fuhrer, Brian, Borawski, Albert T., Milavsky, Joseph G., Donato, Paul, Shankar, Balachander, Kurzynski, David J.
• Primary Examiner(s): Goodarzi, Nasser
• Assistant Examiner(s): Pierorazio, Michael B
• Application Number:
  US15/044,939
• Publication Number:
  US 20160165287A1
• Time in Patent Office: 329 Days
• Field of Search: 725/14
• US Class Current: 1/1
• CPC Class Codes: H04N 21/23424 involving splicing one content stream with another content stream, e.g. for inserting or substituting an advertisement
• CPC Class Codes: H04N 21/2407 Monitoring of transmitted content, e.g. distribution time, number of downloads arrangements for monitoring programmes for broadcast or for distribution combined with broadcast H04H20/14
• CPC Class Codes: H04N 21/251 Learning process for intelligent management, e.g. learning user preferences for recommending movies details of learning user preferences for the retrieval of video data in a video database G06F16/739; computer systems using learning methods G06N3/08
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• CPC Class Codes: H04N 21/25883 being end-user demographical data, e.g. age, family status or address arrangements for identifying locations of users in broadcast systems H04H60/52
• 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
• CPC Class Codes: H04N 21/44222 Analytics of user selections, e.g. selection of programs or purchase activity monitoring of user selections in data processing systems G06F11/34; arrangements for monitoring the user's behaviour or opinions in broadcast systems H04H60/33
• CPC Class Codes: H04N 21/4663 involving probabilistic networks, e.g. Bayesian networks
• CPC Class Codes: H04N 21/4667 Processing of monitored end-user data, e.g. trend analysis based on the log file of viewer selections
• CPC Class Codes: H04N 21/812 involving advertisement data advertising per se G06Q30/02

Abstract

Methods, apparatus, systems and articles of manufacture are disclosed to calculate video-on-demand viewing probability. Example methods disclosed herein include identifying a first set of households associated with a target set of categories that presented a first media having a first telecast delay, calculating first total tuning minutes and first total exposure minutes for the first set of households, identifying a second set of households that presented the first media having the first telecast delay and having a portion of the target set of categories, the second set of households having second total tuning minutes and second total exposure minutes for each category in the second set of households, calculating a household tuning proportion based on the first and second total tuning minutes, and calculating a household exposure proportion based on the first and second total exposure minutes, and calculating the panelist viewing probability associated with the first telecast delay based on a ratio of the household exposure proportion and the household tuning proportion.

Claims

1. A computer-implemented method to reduce waste of a first advertising targeting strategy for a first media, the method comprising:

identifying, by executing an instruction with a processor, a first set of households associated with a target set of categories associated with the first advertising targeting strategy, the first media presented in the first set of households with a first time shift delay;

calculating, by executing an instruction with the processor, a first viewing probability associated with the first time shift delay based on a ratio of (a) exposure minutes of the first media in the first set of households, and (b) tuning minutes of the first media in the first set of households;

identifying, by executing an instruction with the processor, a second set of households associated with the target set of categories associated with the first advertising targeting strategy, the first media presented in the second set of households with a second time shift delay; and

reducing, by executing an instruction with the processor, waste of the first advertising targeting strategy of the first media associated with the second time shift delay by selecting a second advertising targeting strategy for the first media in response to determining that the second time shift delay of the first media has a second viewing probability that is less than the first viewing probability, the determination being based on a ratio of (a) exposure minutes of the first media in the second set of households, and (b) tuning minutes of the first media in the second set of households.

2. The method as defined in claim 1, further including generating a list of viewing probabilities of the first media associated with subsequent time shift delay values from the first time shift delay.

3. The method as defined in claim 2, further including identifying viewing probability trend information for the first advertising strategy based on the list of viewing probabilities.

4. The method as defined in claim 1, wherein the first time shift delay is associated with live viewing.

5. The method as defined in claim 1, wherein the first advertising targeting strategy includes targeting a first demographic of interest.

6. The method as defined in claim 1, wherein the second advertising targeting strategy includes a second demographic of interest.

7. The method as defined in claim 6, wherein the second demographic of interest is different from the first demographic of interest and includes an alternate viewing probability that is greater than the second viewing probability.

8. The method as defined in claim 1, wherein the first time shift delay includes a telecast delay.

9. An apparatus to reduce waste of a first advertising targeting strategy for a first media, the apparatus comprising:

a category manager to;

identify a first set of households associated with a target set of categories associated with the first advertising targeting strategy, the first media presented in the first set of households with a first time shift delay; and

identify a second set of households associated with the target set of categories associated with the first advertising targeting strategy, the first media presented in the second set of households with a second time shift delay;

a probability engine to;

calculate a first viewing probability associated with the first time shift delay based on a ratio of (a) exposure minutes of the first media in the first set of households, and (b) tuning minutes of the first media in the first set of households; and

reduce waste of the first advertising targeting strategy of the first media associated with the second time shift delay by selecting a second advertising targeting strategy for the first media in response to determining that the second time shift delay of the first media has a second viewing probability that is less than the first viewing probability, the determination being based on a ratio of (a) exposure minutes of the first media in the second set of households, and (b) tuning minutes of the first media in the second set of households.

10. The apparatus as defined in claim 9, wherein the category manager is to generate a list of viewing probabilities of the first media associated with subsequent time shift delay values from the first time shift delay.

11. The apparatus as defined in claim 10, wherein the category manager is to identify viewing probability trend information for the first advertising strategy based on the list of viewing probabilities.

12. The apparatus as defined in claim 9, wherein the first time shift delay is associated with live viewing.

13. The apparatus as defined in claim 9, wherein the probability engine is to target a first demographic of interest with the first advertising targeting strategy.

14. The apparatus as defined in claim 9, wherein the probability engine is to target a second demographic of interest with the second advertising targeting strategy.

15. A tangible computer-readable storage medium comprising instructions that, when executed, cause a processor to, at least:

identify a first set of households associated with a target set of categories associated with a first advertising targeting strategy, a first media presented in the first set of households with a first time shift delay;

calculate a first viewing probability associated with the first time shift delay based on a ratio of (a) exposure minutes of the first media in the first set of households, and (b) tuning minutes of the first media in the first set of households;

identify a second set of households associated with the target set of categories associated with the first advertising targeting strategy, the first media presented in the second set of households with a second time shift delay; and

reduce waste of the first advertising targeting strategy of the first media associated with the second time shift delay by selecting a second advertising targeting strategy for the first media in response to determining that the second time shift delay of the first media has a second viewing probability that is less than the first viewing probability, the determination being based on a ratio of (a) exposure minutes of the first media in the second set of households, and (b) tuning minutes of the first media in the second set of households.

16. The computer-readable instructions as defined in claim 15 that, when executed, cause the processor to generate a list of viewing probabilities of the first media associated with subsequent time shift delay values from the first time shift delay.

17. The computer-readable instructions as defined in claim 16 that, when executed, cause the processor to identify viewing probability trend information for the first advertising strategy based on the list of viewing probabilities.

18. The computer-readable instructions as defined in claim 15 that, when executed, cause the processor to associate the first time shift delay with live viewing activity.

19. The computer-readable instructions as defined in claim 15 that, when executed, cause the processor to target a second demographic of interest during the second advertising targeting strategy.

20. The computer-readable instructions as defined in claim 19 that, when executed, cause the processor to identify that the second demographic of interest is different from the first demographic of interest and includes an alternate viewing probability that is greater than the second viewing probability.