IP Library Granted Patent US 11,973,576
Granted Patent B2
US 11,973,576 · App. 17/952,054 · Granted Apr 30, 2024

Methods, systems and apparatus to determine panel attrition

Inventors: Michael Sheppard (Holland, MI); Christie Nicole Summers (Baltimore, MD); Molly Poppie (Arlington Heights, IL)
Assignee: The Nielsen Company (US), LLC
H04H60/33H04N21/4622H04N21/4667
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Quick Facts
Patent No.
US 11,973,576
App. No.
17/952,054
Granted
Apr 30, 2024
Kind
B2
Abstract

Methods, apparatus, and systems are disclosed for estimating panel attrition. An example apparatus includes at least one memory, machine readable instructions, and processor circuitry to execute the machine readable instructions to determine a beta distribution of a non-parametric survival curve estimate based on panel meter data associated with a cohort of panelists, determine confidence intervals for a set of beta distribution parameters associated with the survival curve estimate, and output a panelist attrition estimate generated based on the confidence intervals for the survival curve estimate, the panelist attrition estimate to represent panelist retention over time based on an installation date of the panel meter.

Claims (31)

1. An audience measurement computing system for estimating panelist attrition, the audience measurement computing system comprising:

a processor;

at least one memory; memory having stored therein machine readable instructions that, when executed by the processor, cause the audience measurement computing system to perform operations comprising:

determining a beta distribution of a non-parametric survival curve estimate based on panel meter data associated with a cohort of panelists;

determining confidence intervals for a set of beta distribution parameters associated with the non-parametric survival curve estimate; and

outputting a panelist attrition estimate generated based on the confidence intervals, the panelist attrition estimate representing panelist retention over time based on an installation date associated with the panel meter data.

2. The audience measurement computing system of claim 1 , wherein the panel meter data includes at least one of a panel meter install date, a panel meter uninstall date, or activity log submission data.

3. The audience measurement computing system of claim 1 , wherein the operations further include applying a method of moments to estimate the set of beta distribution parameters when a variance of the non-parametric survival curve estimate is known.

4. The audience measurement computing system of claim 1 , wherein the non-parametric survival curve estimate matches a Kaplan-Meier point estimate.

5. The audience measurement computing system of claim 1 , wherein the operations further include determining the non-parametric survival curve estimate for censored and non-censored panel meter data.

6. The audience measurement computing system of claim 1 , wherein the panelist attrition estimate includes expected attrition rates for panelists based on a demographic attribute including at least one of an age, a gender, or a household size.

7. The audience measurement computing system of claim 1 , wherein the operations further include determining the non-parametric survival curve estimate based on a Haldane's prior distribution within the beta distribution.

8. A method for estimating panelist attrition, the method comprising:

determining a beta distribution of a non-parametric survival curve estimate based on panel meter data associated with a cohort of panelists;

determining confidence intervals for a set of beta distribution parameters associated with the non-parametric survival curve estimate; and

outputting a panelist attrition estimate generated based on the confidence, the panelist attrition estimate representing panelist retention over time based on an installation date associated with the panel meter data.

9. The method of claim 8 , wherein the panel meter data includes at least one of a panel meter install date, a panel meter uninstall date, or activity log submission data.

10. The method of claim 8 , further including applying a method of moments to estimate the beta distribution parameters when a variance of the non-parametric survival curve estimate is known.

11. The method of claim 8 , wherein the non-parametric survival curve estimate matches a Kaplan-Meier point estimate.

12. The method of claim 8 , further including determining the non-parametric survival curve estimate for censored and non-censored panel meter data.

13. The method of claim 8 , wherein the panelist attrition estimate includes expected attrition rates for panelists based on a demographic attribute including at least one of an age, a gender, or a household size.

14. The method of claim 8 , further including determining the non-parametric survival curve estimate based on a Haldane's prior distribution within the beta distribution.

15. A non-transitory computer readable storage medium having stored thereon instructions that, when executed by a processor of a computing system, cause the computing system to be configured to at least:

determine a beta distribution of a non-parametric survival curve estimate based on panel meter data associated with a cohort of panelists;

determine confidence intervals for a set of beta distribution parameters associated with the non-parametric survival curve estimate; and

output a panelist attrition estimate generated based on the confidence intervals, the panelist attrition estimate representing panelist retention over time based on an installation date associated with the panel meter data.

16. The non-transitory computer readable storage medium of claim 15 , wherein the instructions, when executed by the processor, cause the computing system to be configured to apply a method of moments to estimate the beta distribution parameters when a variance of the non-parametric survival curve estimate is known.

17. The non-transitory computer readable medium of claim 15 , wherein the non-parametric survival curve estimate matches a Kaplan-Meier point estimate.

18. The non-transitory computer readable medium of claim 15 , wherein the instructions, when executed by the processor, cause the computing system to be configured to determine the non-parametric survival curve estimate for censored and non-censored panel meter data.

19. The non-transitory computer readable medium of claim 15 , wherein the panelist attrition estimate includes expected attrition rates for panelists based on a demographic attribute including at least one of an age, a gender, or a household size.

20. The non-transitory computer readable medium of claim 15 , wherein the instructions, when executed by the processor, cause the computing system to be configured to determine the non-parametric survival curve estimate based on a Haldane's prior distribution within the beta distribution.

Assignments (4)
SECURITY INTEREST Recorded May 8, 2023
From: GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE, INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC
To: ARES CAPITAL CORPORATION
Reel/Frame 063574/0632 →
SECURITY INTEREST Recorded Apr 28, 2023
From: GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE, INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC
To: CITIBANK, N.A.
Reel/Frame 063561/0381 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 11, 2023
From: SHEPPARD, MICHAEL; SUMMERS, CHRISTIE NICOLE; POPPIE, MOLLY
To: THE NIELSEN COMPANY (US), LLC
Reel/Frame 063055/0961 →
SECURITY AGREEMENT Recorded Jan 31, 2023
From: GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE, INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC
To: BANK OF AMERICA, N.A.
Reel/Frame 063560/0547 →
Continuity (2)
Provisional Application 63294768 · Dec 29, 2021
Related Publication 20230208540A1 · Jun 29, 2023