Out of home media measurement

• US 10,235,695 B2
• Filed: 07/05/2016
• Issued: 03/19/2019
• Est. Priority Date: 09/18/2013
• Status: Active Grant

• Current Assignee: Cellco Partnership, Inc. (Verizon Communications Inc.)
• Original Assignee: Cellco Partnership, Inc. (Verizon Communications Inc.)
• Inventors: Shaik, Altaff M., Polavarapu, Narendra, Applegate, Dustin L., Stemper, Richard, Hosanagara, Satish K.
• Primary Examiner(s): Weng, Pei Yong
• Application Number:
  US15/202,360
• Publication Number:
  US 20160314499A1
• Time in Patent Office: 987 Days
• CPC Class Codes: G06F 16/254 Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

A system may include at least one data source configured to provide network usage data indicative of the existence of communications with subscriber devices, and web and application usage data indicative of data usage of the subscriber network by the subscriber devices. The system may also include a data warehouse server configured to perform operations including correlating the network usage data and web and application usage data into subscriber-level data; associating, with the subscriber-level data, subscriber attributes indicative of a preference of the subscriber for content in a particular category of content, and profile attributes indicative of demographic characteristics of the subscriber; matching the subscriber-level data with a set of subscriber profiles, each of the set of subscriber profiles including a set of subscriber attributes and profile attributes associated with the respective subscriber profile; and aggregating the subscriber-level data into aggregate-level data according to the matching subscriber profiles.

Claims

1. A system, comprising:

a server in communication with at least one data source device having network usage data and web and application usage data of a subscriber network, the server performing operations including;

correlating network usage data and web and application usage data to generate subscriber-level data;

associating, with the subscriber-level data, subscriber attributes indicative of a preference of a subscriber for content in a particular category of content, and profile attributes indicative of demographic characteristics of the subscriber;

matching the subscriber-level data with a set of subscriber profiles, each of the set of subscriber profiles including a set of subscriber attributes and profile attributes associated with the respective subscriber profile; and

applying an adjustment factor to the subscriber-level data in response to aggregating the subscriber-level data into aggregate-level data according to the matching subscriber profiles.

2. The system of claim 1, wherein the adjustment factor includes:

a usage adjustment factor adjusting for relative usage levels of different subscribers of the subscriber network, and

a non-usage adjustment factor accounting for individuals not performing device usage.

3. The system of claim 1, the operations further including:

receiving a request for a report from a portal device, the request associated with criteria including a subscriber attribute and a profile attribute; and

providing the aggregate-level data in a report to the portal device in response to the request.

4. The system of claim 1, the operations further including:

determining the adjustment factor to apply to the subscriber-level data to weigh and extrapolate the subscriber-level data to be representative of the population at large; and

performing a weighted aggregation of the subscriber-level data according to the determined adjustment factor.

5. The system of claim 1, wherein the adjustment factor includes at least two of:

(i) a subscriber weight adjustment factor accounting for differences in composition of a pool of subscribers of the network service provider as compared to the population in general;

(ii) a national weight adjustment factor accounting for differences in in size and distribution of the pool of subscribers of the network service provider as compared to the population in general;

(iii) a usage adjustment factor adjusting for relative usage levels of different subscribers of the network service provider, and (iv) a non-usage adjustment factor accounting for individuals at a location not performing device usage.

6. The system of claim 3, the operations further including:

preventing the providing of aggregate-level data in a report according to a predefined aggregation threshold.

7. The system of claim 1, the operations further including:

matching the subscriber-level data to the set of subscriber profiles using a profile mapping, the profile mapping including an association of subscriber identifiers with subscriber profiles; and

using the adjustment factor associated with the subscribers in the profile mapping to weigh subscriber transactions being aggregated to determine extrapolated counts for subscribers matching the subscriber profiles.

8. The system of claim 1, the operations further including:

filtering the network usage data and the web and application usage data according to an inclusion list to remove usage data associated with ineligible subscribers.

9. A method comprising:

receiving network usage data indicative network usage and web and application usage data of a subscriber network;

correlating the network usage data and web and application usage data to generate subscriber-level data;

associating, with the subscriber-level data, subscriber attributes indicative of a preference of a subscriber for content in a particular category of content, and profile attributes indicative of demographic characteristics of the subscriber;

matching the subscriber-level data with a set of subscriber profiles, each of the set of subscriber profiles including a set of subscriber attributes and profile attributes associated with the respective subscriber profile; and

applying an adjustment factor to the subscriber-level data in response to aggregating the subscriber-level data into aggregate-level data according to the matching subscriber profiles.

10. The method of claim 9, further comprising:

receiving a request for a report from a portal device, the request associated with criteria including a subscriber attribute and a profile attribute; and

providing the aggregate-level data in a report to the portal device in response to the request.

11. The method of claim 9, further comprising:

determining the adjustment factor to apply to the subscriber-level data to weigh and extrapolate the subscriber-level data to be representative of the population at large; and

performing a weighted aggregation of the subscriber-level data according to the determined adjustment factor.

12. The method of claim 9, further comprising:

preventing publishing of aggregate-level data for a profile according to a predefined aggregation threshold.

13. The method of claim 9, further comprising:

matching the subscriber-level data to the set of subscriber profiles using a profile mapping, the profile mapping including an association of subscriber identifiers with subscriber profiles; and

using the adjustment factor associated with the subscribers in the profile mapping to weigh subscriber transactions being aggregated to determine extrapolated counts for subscribers matching the subscriber profiles.

14. The system of claim 9, further comprising:

filtering the network usage data and the web and application usage data according to an inclusion list to remove usage data associated with ineligible subscribers.

15. A non-transitory computer readable medium storing computer-executable instructions executable by a computing device to provide operations comprising:

receiving network usage data and web and application usage data of a subscriber network;

correlating the network usage data and web and application usage data to generate subscriber-level data;

associating, with the subscriber-level data, subscriber attributes indicative of a preference of the subscriber for content in a particular category of content, and profile attributes indicative of demographic characteristics of the subscriber;

matching the subscriber-level data with a set of subscriber profiles, each of the set of subscriber profiles including a set of subscriber attributes and profile attributes associated with the respective subscriber profile; and

applying an adjustment factor to the subscriber-level data in response to aggregating the subscriber-level data into aggregate-level data according to the matching subscriber profiles.

16. The non-transitory computer readable medium of claim 15, the operations further comprising:

receiving a request for a report from a portal device, the request associated with criteria including a subscriber attribute and a profile attribute; and

providing the aggregate-level data in a report to the portal device in response to the request.

17. The non-transitory computer readable medium of claim 15, the operations further comprising:

determining the adjustment factor to apply to the subscriber-level data to weigh and extrapolate the subscriber-level data to be representative of the population at large; and

performing a weighted aggregation of the subscriber-level data according to the determined adjustment factor.

18. The non-transitory computer readable medium of claim 15, the operations further comprising:

preventing publishing of aggregate-level data for a profile according to a predefined aggregation threshold.

19. The non-transitory computer readable medium of claim 15, the operations further comprising:

matching the subscriber-level data to the set of subscriber profiles using a profile mapping, the profile mapping including an association of subscriber identifiers with subscriber profiles; and

using the adjustment factor associated with the subscribers in the profile mapping to weigh subscriber transactions being aggregated to determine extrapolated counts for subscribers matching the subscriber profiles.

20. The non-transitory computer readable medium of claim 15, the operations further comprising:

filtering the network usage data and the web and application usage data according to an inclusion list to remove usage data associated with ineligible subscribers.