Methods and apparatus to determine synthetic respondent level data

Patent metadata

Field	Value
Publication number	US-11758229-B2
Application number	US-202217902612-A
Country	US
Kind code	B2
Filing date	Sep 2, 2022
Priority date	Feb 28, 2017
Publication date	Sep 12, 2023
Grant date	Sep 12, 2023

Abstract

Methods, apparatus, systems, and articles of manufacture are disclosed to generate synthetic respondent level data. An example apparatus includes at least one memory; processor circuitry to execute instructions to: identify locations corresponding to monitored panelists; when a location of the identified locations corresponds to two or more affiliates, sum tuning minutes of the two or more affiliates; generate an affiliate probability based on the sum; convert first data of households in the location to a candidate receivability session based on the affiliate probability; generate a seed panel, the seed panel to include at least one of the monitored panelists selected based on a population associated with return path data; and donate second data associated with a donor pool of first panelists to second panelists included in the seed panel when the second panelists are included in the seed panel, the second panelists corresponds to faulty media monitoring equipment.

First claim

What is claimed is:

1. An apparatus comprising:
at least one memory;
instructions; and
programmable circuitry to execute the instructions to:
identify locations corresponding to monitored panelists;
when a first one of the identified locations corresponds to an affiliate, assign first data of households in the first one of the identified locations to the affiliate;
generate a seed panel, the seed panel to include at least one of the monitored panelists selected based on a population associated with return path data; and
donate second data associated with a donor pool of first panelists to second panelists included in the seed panel, the second panelists associated with faulty media monitoring equipment.

2. The apparatus of claim 1 , wherein the first data is at least one of tuning data or viewing data of the households.

3. The apparatus of claim 1 , wherein the programmable circuitry is to assign at least one of geography data or income data to the return path data based on demographics associated with the population.

4. The apparatus of claim 3 , wherein the programmable circuitry is to:
select a first group of the monitored panelists to be seed panelists based on a comparison of the monitored panelists and the at least one of the geography data or the income data assigned to the return path data; and
weight the seed panelists based on a universe estimate of media users.

5. The apparatus of claim 1 , wherein the programmable circuitry is to at least one of replicate or down-sample seed panelists.

6. The apparatus of claim 1 , wherein the programmable circuitry to:
compare a target rating to a computed rating determined based on the seed panel; and
adjust the seed panel based on the comparison to reduce an error between the target rating and the computed rating.

7. An apparatus comprising:
station translation circuitry to:
identify locations corresponding to monitored panelists; and
when a first one of the identified locations corresponds to an affiliate, assign first data of households in the first one of the identified locations to the affiliate; and seed panel generation circuitry to:
generate a seed panel, the seed panel to include at least one of the monitored panelists selected based on a population associated with return path data; and
donate second data associated with a donor pool of first panelists to second panelists included in the seed panel when the second panelists are included in the seed panel, the second panelists associated with faulty media monitoring equipment.

8. The apparatus of claim 7 , wherein the first data is at least one of tuning data or viewing data of the households.

9. The apparatus of claim 7 , wherein the seed panel generation circuitry is to assign at least one of geography data or income data to the return path data based on demographics associated with the population.

10. The apparatus of claim 9 , wherein the seed panel generation circuitry is to:
select a first group of the monitored panelists to be seed panelists based on a comparison of the monitored panelists and the at least one of the geography data or the income data assigned to the return path data; and
weight the seed panelists based on a universe estimate of media users.

11. The apparatus of claim 7 , wherein the seed panel generation circuitry is to at least one of replicate or down-sample seed panelists.

12. The apparatus of claim 7 , further including seed panel optimization circuitry to:
compare a target rating to a computed rating determined based on the seed panel; and
adjust the seed panel based on the comparison to reduce an error between the target rating and the computed rating.

13. A non-transitory computer readable medium comprising instructions which, when executed, cause one or more processors to at least:
identify locations corresponding to monitored panelists;
when a first one of the identified locations corresponds to an affiliate, assign first data of households in the first one of the identified locations to the affiliate;
generate a seed panel, the seed panel to include at least one of the monitored panelists selected based on a population associated with return path data; and
donate second data associated with a donor pool of first panelists to second panelists included in the seed panel when the second panelists are included in the seed panel, the second panelists corresponds to faulty media monitoring equipment.

14. The non-transitory computer readable medium of claim 13 , wherein the first data is at least one of tuning data or viewing data of the households.

15. The non-transitory computer readable medium of claim 13 , wherein the instructions cause the one or more processors to assign at least one of geography data or income data to the return path data based on demographics associated with the population.

16. The non-transitory computer readable medium of claim 15 , wherein the instructions cause the one or more processors to:
select a first group of the monitored panelists to be seed panelists based on a comparison of the monitored panelists and the at least one of the geography data or the income data assigned to the return path data; and
weight the seed panelists based on a universe estimate of media users.

17. The non-transitory computer readable medium of claim 15 , wherein the instructions cause the one or more processors to at least one of replicate or down-sample seed panelists.

18. A method comprising:
identifying, by executing instructions with one or more processors, locations corresponding to monitored panelists;
when a first one of the identified locations corresponds to an affiliate, ascribing, by executing instructions with the one or more processors, first data of households in the first one of the identified locations to the affiliate;
generating, by executing instructions with the one or more processors, a seed panel, the seed panel to include at least one of the monitored panelists selected based on a population associated with return path data; and
donating, by executing instructions with the one or more processors, second data associated with a donor pool of first panelists to second panelists included in the seed panel when the second panelists are included in the seed panel, the second panelists corresponds to faulty media monitoring equipment.

19. The method of claim 18 , further including assigning at least one of geography data or income data to the return path data based on demographics associated with the population.

20. The method of claim 19 , further including:
selecting a first group of the monitored panelists to be seed panelists based on a comparison of the monitored panelists and the at least one of the geography data or the income data assigned to the return path data; and
weighting the seed panelists based on a universe estimate of media users.

Assignees

• Nielsen Co Us Llc

Inventors

• Sullivan Jonathan
• Morgan Michael D
• Shankar Balachander
• Murphy Edward
• Sheppard Michael
• Downing Frank

Classifications

• H04N21/44222 Primary

  Analytics of user selections, e.g. selection of programmes 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 title

• H04N21/4667 Primary

  Processing of monitored end-user data, e.g. trend analysis based on the log file of viewer selections · CPC title

• H04N21/239

  Interfacing the upstream path of the transmission network, e.g. prioritizing client {content} requests (hybrid fiber coaxial [HFC] networks for upstream channel allocation for video distribution H04L12/2801; flow control in data networks H04L47/10; real-time communication protocols in data switching networks H04L65/00; scheduling or organising the servicing of application requests H04L67/60) · CPC title

• H04N21/25891

  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 title

• H04N21/6156

  specially adapted to the upstream path of the transmission network · CPC title