Clickstream analysis methods and systems related to improvements in online stores and media content

• US 9,501,781 B2
• Filed: 03/14/2016
• Issued: 11/22/2016
• Est. Priority Date: 03/07/2002
• Status: Expired due to Term

• Current Assignee: comScore, Inc.
• Original Assignee: comScore, Inc.
• Inventors: Singh, Man Jit, Cancel, David
• Primary Examiner(s): Williams, Jenee
• Application Number:
  US15/069,005
• Publication Number:
  US 20160196567A1
• Time in Patent Office: 253 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 15/16 Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs coordinating program control therefor G06F9/52; in regulating and control system G05B
• CPC Class Codes: G06F 15/17 using an input/output type connection, e.g. channel, I/O port
• CPC Class Codes: G06F 16/95 Retrieval from the web
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9566 URL specific, e.g. using aliases, detecting broken or misspelled links
• CPC Class Codes: G06Q 20/20 Point-of-sale [POS] network systems
• CPC Class Codes: G06Q 20/201 Price look-up processing, e.g. updating
• CPC Class Codes: G06Q 20/203 Inventory monitoring
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0224 based on user history
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 30/0243 Comparative campaigns
• CPC Class Codes: G06Q 30/0244 Optimization
• CPC Class Codes: G06Q 30/0246 Traffic
• CPC Class Codes: G06Q 30/0251 Targeted advertisements
• CPC Class Codes: G06Q 30/0633 Lists, e.g. purchase orders, compilation or processing
• CPC Class Codes: H04H 60/45 for identifying users
• CPC Class Codes: H04H 60/46 for recognising users' preferences
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/146 : Markers for unambiguous identification of a particular session, e.g. session cookie or URL-encoding
• CPC Class Codes: H04L 67/535 : Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

Methods and systems are provided herein for the analysis of clickstream data of online users. The analysis methods and systems allow for the creation of new online and offline business methods based on online consumer behavior.

Claims

1. A system comprising:

one or more processors;

a memory bearing instructions that, when executed, cause the one or more processors to;

identify demographic information about members of a target population;

based at least in part on the demographic information, identify a group of participants in the target population;

identify Uniform Resource Locators (URLs) in one or more clickstreams of the group of participants;

decompose and hash each URL in the one or more clickstreams;

calculate, based at least in part on the decomposed hashed URLs, a metric of cross-shopping behavior of the group of participants between different consumer goods; and

transmit the metric of cross-shopping behavior through a communication facility to a remote machine for use in a determination of where consumer goods should be presented in an online store.

2. The system of claim 1, wherein identifying demographic information includes performing a random digit dial survey of the target population.

3. The system of claim 1, wherein the metric of cross-shopping behavior is transmitted to the remote machine for use in determining an order to present the consumer goods in the online store.

4. The system of claim 1, wherein the metric of cross-shopping behavior is transmitted to the remote machine for use in determining that certain consumer goods should be presented together in the online store.

5. The system of claim 1, wherein the memory further bears instructions that, when executed, cause the one or more processors to adjust a structure of the online store based on the determination.

6. The system of claim 1, wherein the memory further bears instructions that, when executed, cause the one or more processors to adjust a content of the online store based on the determination.

7. The system of claim 1, wherein the metric of cross-shopping behavior includes an order in which one or more participants in the group of participants has viewed one or more consumer goods included in the different consumer goods.

8. The system of claim 1, wherein the metric of cross-shopping behavior includes an order in which one or more participants in the group of participants has viewed one or more vendors that offer one or more consumer goods included in the different consumer goods.

9. A system comprising:

one or more processors;

a memory bearing instructions that, when executed, cause the one or more processors to;

identify demographic information about members of a target population;

based at least in part on the demographic information, identify a group of participants in the target population;

identify Uniform Resource Locators (URLs) in one or more clickstreams of the group of participants;

decompose and hash each URL in the one or more clickstreams;

calculate, based at least in part on the decomposed hashed URLs, a metric of cross-shopping behavior of the group of participants between different consumer goods; and

transmit the metric of cross-shopping behavior through a communication facility to a remote machine for use in improving channels of distribution for media content based on the metric of cross-shopping behavior.

10. The system of claim 9, wherein identifying demographic information includes performing a random digit dial survey of the target population.

11. The system of claim 9, wherein improving channels of distribution for media content includes adjusting content of a website of a vendor based on the metric of cross-shopping behavior.

12. The system of claim 11, wherein the content of the website of the vendor is adjusted to include content similar to that offered by a different vendor.

13. The system of claim 11, wherein the content of the website includes media content.

14. The system of claim 9, wherein the metric of cross-shopping behavior includes a demographic interest regarding a consumer good.

15. The system of claim 9, wherein the metric of cross-shopping behavior includes a demographic interest regarding media content.

16. The system of claim 9, wherein the channels of distribution for media content are online channels of distribution.

17. The system of claim 9, wherein the channels of distribution for media content are offline channels of distribution.