Out of home media measurement

• US 9,418,126 B2
• Filed: 09/18/2013
• Issued: 08/16/2016
• 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 Mohiddin, Polavarapu, Narendra, Applegate, Dustin Logan, Hosanagara, Satish Kumar, Stemper, Richard
• Primary Examiner(s): Weng, Peiyong
• Application Number:
  US14/030,443
• Publication Number:
  US 20150081617A1
• Time in Patent Office: 1,063 Days
• US Class Current: 1/1
• 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:

at least one data source device configured to provide network usage data at an event location indicative of the existence of communications through a subscriber network of a network service provider and with subscriber devices, and web and application usage data indicative of data usage of the subscriber network by the subscriber devices; and

a data warehouse server configured to perform operations comprising;

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;

applying at least two adjustment factors to the subscriber-level data, wherein the at least two adjustment factors include a usage adjustment factor adjusting for relative usage levels of different subscribers of the network service provider and a non-usage adjustment factor accounting for individuals at the event location not performing device usage; and

providing a graphical map of attendance at the event location responsive to aggregating the subscriber-level data into aggregate-level data according to the matching subscriber profiles.

2. The system of claim 1, further comprising a data mart configured to perform operations comprising:

receiving the aggregate-level data from the data warehouse server;

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

retrieving aggregate-level data matching the criteria; and

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

3. The system of claim 1, wherein the data warehouse server is further configured to perform operations comprising:

determining adjustment factors 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 factors.

4. The system of claim 1, wherein the data warehouse server is further configured to perform operations comprising preventing the providing of aggregate-level data in a report for which the aggregation is of fewer than a predefined threshold of records greater than one.

5. The system of claim 1, wherein the data warehouse server is further configured perform operations 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 adjustment factors associated with the subscribers in the profile mapping to weigh subscriber transactions being aggregated to determine extrapolated counts for subscribers matching the subscriber profiles.

6. The system of claim 1, wherein the at least one data source device is further configured to perform operations 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.

7. The system of claim 1, wherein the data warehouse server is further configured to perform field adjustments of the received usage records including at least one of:

(i) parsing information in the web and application usage data to create data fields including at least one of device operating system, browser version, and browser type;

(ii) including total page counts visited by subscribers in the web and application usage data;

(iii) including, in the received usage records, identifiers of websites that were visited before and after the respective received usage records; and

(iv) removing, from the usage data, information regarding websites including at least one of inappropriate content, obscene content, and banking or financial content.

13. The system of claim 1, 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.

14. The system of claim 1, wherein the data warehouse server is further configured to perform field adjustments of the received usage records including at least two of:

(i) parsing information in the web and application usage data to create separate data fields at least one of device operating system, browser version, and browser type;

(ii) determine a total number of page counts that a subscriber has visited in the web and application usage data;

(iii) include in the received usage records identifiers of websites that were visited before and after a usage records; and

(iv) remove from the usage data information regarding websites including at least one of inappropriate content, obscene content, and banking or financial content.

8. A method, comprising:

receiving network usage data indicative network usage data at an event location indicative of the existence of communications through a subscriber network of a network service provider and with subscriber devices and web and application usage data indicative of data usage of the subscriber network by the subscriber devices;

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;

applying at least two adjustment factors to the subscriber-level data, wherein the at least two adjustment factors include a usage adjustment factor adjusting for relative usage levels of different subscribers of the network service provider and a non-usage adjustment factor accounting for individuals at the event location not performing device usage; and

providing a graphical map of attendance at the event location responsive to aggregating the subscriber-level data into aggregate-level data according to the matching subscriber profiles.

9. The method of claim 8, further comprising:

receiving the aggregate-level data from the data warehouse server;

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

retrieving aggregate-level data matching the criteria; and

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

10. The method of claim 8, further comprising:

determining adjustment factors 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 factors.

11. The method of claim 8, further comprising preventing the publishing of aggregate-level data for a profile for which the aggregation is of fewer than a predefined threshold of records greater than one.

12. The method of claim 8, 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 adjustment factors associated with the subscribers in the profile mapping to weigh subscriber transactions being aggregated to determine extrapolated counts for subscribers matching the subscriber profiles.

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

receiving network usage data indicative network usage data at an event location 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;

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;

applying at least two adjustment factors to the subscriber-level data, wherein the at least two adjustment factors include a usage adjustment factor adjusting for relative usage levels of different subscribers of the network service provider and a non-usage adjustment factor accounting for individuals at the event location not performing device usage; and

providing a graphical map of attendance at the event location responsive 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, further providing for operations comprising:

receiving the aggregate-level data from the data warehouse server;

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

retrieving aggregate-level data matching the criteria; and

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

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

determining adjustment factors 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 factors.

18. The non-transitory computer readable medium of claim 15, further providing for operations comprising preventing the publishing of aggregate-level data for a profile for which the aggregation is of fewer than a predefined threshold of records greater than one.

19. The non-transitory computer readable medium of claim 15, further providing for operations 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 adjustment factors 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, further providing for operations 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.

21. The non-transitory computer readable medium of claim 15, further providing for operations comprising performing field adjustments of the received usage records including at least two of:

(i) parsing information in the web and application usage data to create separate data fields at least one of device operating system, browser version, and browser type;

(ii) determine a total number of page counts that a subscriber has visited in the web and application usage data;

(iii) include in the received usage records identifiers of websites that were visited before and after a usage records; and

(iv) remove from the usage data information regarding websites including at least one of inappropriate content, obscene content, and banking or financial content.