Granted Patent B2

US 12,689,799 · App. 18/808,153 · Granted Jul 21, 2026

Inventors: Michael Sheppard (Holland, MI); Ludo Daemen (Duffel, BE); Edward Murphy (North Stonington, CT); Molly Poppie (Arlington Heights, IL)

Assignee: The Nielsen Company (US), LLC

H04N21/44222G06Q30/0201H04N21/25883

Abstract

Claims (40)

1 . An audience population subset size estimation computing system comprising:

memory having stored therein computer readable instructions;

at least one processor configured to, upon execution of the computer readable instructions, cause performance of a set of operations comprising:

identifying ones of a plurality of respondents included in an audience sample that are associated with a particular characteristic corresponding to an audience population subset;

determining a first sample quantity of the identified ones of the plurality of respondents;

determining a second unique sample quantity of the identified ones of the plurality of respondents having respondent identifiers unique amongst a set of stored respondent identifiers;

incrementing a third unique capture quantity by the second unique sample quantity;

determining a seed population estimate based on the third unique capture quantity, wherein the seed population estimate is greater than the third unique capture quantity; and

estimating the audience population subset size based on the first sample quantity, the third unique capture quantity, and the seed population estimate.

2 . The audience population subset size estimation computing system of claim 1 , wherein the operations further include:

accessing respondent identifiers of the identified ones of the plurality of respondents; and

updating the set of stored respondent identifiers to include the identified ones of the plurality of respondents having respondent identifiers unique amongst the set of stored respondent identifiers.

3 . The audience population subset size estimation computing system of claim 2 , wherein the respondent identifiers include at least one of an internet cookie, a MAC address, or an IP address.

4 . The audience population subset size estimation computing system of claim 1 , wherein the operations further include estimating a recapture probability of the respondents.

5 . The audience population subset size estimation computing system of claim 4 , wherein the recapture probability of the respondents varies with time.

6 . A method for estimating an audience population subset size, the method comprising:

identifying ones of a plurality of respondents included in an audience sample that are associated with a particular characteristic corresponding to an audience population subset;

determining a first sample quantity of the identified ones of the plurality of respondents;

determining a second unique sample quantity of the identified ones of the plurality of respondents having respondent identifiers unique amongst a set of stored respondent identifiers;

incrementing a third unique capture quantity by the second unique sample quantity;

determining a seed population estimate based on the third unique capture quantity, wherein the seed population estimate is greater than the third unique capture quantity; and

estimating the audience population subset size based on the first sample quantity, the third unique capture quantity, and the seed population estimate.

7 . The method of claim 6 , further comprising:

accessing respondent identifiers of the identified ones of the plurality of respondents; and

updating the set of stored respondent identifiers to include the identified ones of the plurality of respondents having respondent identifiers unique amongst the set of stored respondent identifiers.

8 . The method of claim 7 , wherein the respondent identifiers include at least one of an internet cookie, a MAC address, or an IP address.

9 . The method of claim 6 , further comprising estimating a recapture probability of the respondents.

10 . The method of claim 9 , wherein the recapture probability of the respondents varies with time.

11 . A non-transitory computer readable storage medium comprising instructions that, when executed, cause at least one processor to cause performance of:

identifying ones of a plurality of respondents included in an audience sample that are associated with a particular characteristic corresponding to an audience population subset;

determining a first sample quantity of the identified ones of the plurality of respondents;

determining a second unique sample quantity of the identified ones of the plurality of respondents having respondent identifiers unique amongst a set of stored respondent identifiers;

incrementing a third unique capture quantity by the second unique sample quantity;

determining a seed population estimate based on the third unique capture quantity, wherein the seed population estimate is greater than the third unique capture quantity; and

estimating an audience population subset size based on the first sample quantity, the third unique capture quantity, and the seed population estimate.

12 . The non-transitory computer readable storage medium of claim 11 , wherein the instructions, when executed, further cause the at least one processor to cause performance of:

accessing respondent identifiers of the identified ones of the plurality of respondents; and

updating the set of stored respondent identifiers to include the identified ones of the plurality of respondents having respondent identifiers unique amongst the set of stored respondent identifiers.

13 . The non-transitory computer readable storage medium of claim 11 , wherein the instructions, when executed, further cause the at least one processor to cause performance of estimating a recapture probability of the respondents.

14 . The non-transitory computer readable storage medium of claim 13 , wherein the recapture probability of the respondents varies with time.

Continuity (4)

References Cited (21)