Computer-Implemented Systems And Methods For Behavioral Identification Of Non-Human Web Sessions

• US 20100262457A1
• Filed: 04/09/2009
• Published: 10/14/2010
• Est. Priority Date: 04/09/2009
• Status: Active Grant

• Current Assignee: SAS Institute Incorporated
• Original Assignee: SAS Institute Incorporated
• Inventors: House, William Jeffrey
• Granted Patent: US 8,311,876 B2
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0251 Targeted advertisements

Abstract

Computer-implemented systems and methods are provided for analyzing session data generated by a website in response to a visitor requesting data from the website. A system and method can be configured for receiving the session data and analyzing the session data to determine a plurality of website interaction behavioral metrics of the session data. The website interaction behavioral metrics of the session data are compared to detection settings. A determination is made as to whether the visitor to the website was human or non-human based upon the comparing step.

Claims

1. A computer-implemented method for analyzing session data generated by a website in response to a visitor requesting data from the website, comprising:

executing instructions on a processor-implemented system for receiving the session data;

executing instructions on the processor-implemented system for analyzing the session data to determine a plurality of website interaction behavioral metrics of the session data;

wherein the website interaction behavioral metrics represent aspects of behavior related to the visitor from which the session results;

executing instructions on the processor-implemented system for comparing the website interaction behavioral metrics of the session data to detection settings;

wherein the detection settings are threshold values for detecting whether session data results from a human visitor or a non-human visitor; and

executing instructions on the processor-implemented system for generating a determination regarding whether the visitor to the website was human or non-human based upon said comparing;

wherein the generated determination is provided to a computer-readable storage medium and is indicative of whether website activity associated with the visitor comprises human or non-human website activity.

2. The method of claim 1, wherein the detection settings are tuned to alter how aggressively website interaction behavioral metrics are attributed to non-human visitors.

3. The method of claim 2, wherein the detection settings are tuned by comparing session data determined to result from a non-human visitor with known non-human visitor data

4. The method of claim 2, wherein the website interaction behavioral metrics of the session data are selected from the group:

average time between webpage requests;

total session event length; and

combinations thereof.

5. The method of claim 4, wherein the detection settings include minimum session requests (MSR), maximum time spacing (XTS), certain session requests (CSR), and combinations thereof.

6. The method of claim 1, wherein the session data is clickstream data.

7. The method of claim 1, further comprising:

selecting analytical session data based upon the determination whether the visitor to the website was human or non-human;

wherein the analytical session data is used to analyze activity on the website.

8. The method of claim 5, wherein the visitor is determined to be non-human.

9. The method of claim 8, wherein the non-human visitor is a bot, a smart bot, or a pinger.

10. The method of claim 9, wherein the non-human visitor, which transmits a request every eight seconds and transmits 10,000 requests overall to the website, is not detected by using the XTS detection setting, but is detected by using the CSR detection setting.

11. The method of claim 1, wherein a first data store, which is contained on a computer-readable storage medium, stores session data associated with visitors determined to be human visitors;

wherein a second data store, which is contained on a computer-readable storage medium, stores session data associated with visitors determined to be non-human visitors.

12. The method of claim 1, wherein a plurality of visitors is determined to be either human visitors or non-human visitors by using the detection settings.

13. The method of claim 1, wherein the data requested by the visitor includes a request for a webpage associated with the website.

14. The method of claim 1, wherein the processor-implemented system comprises a server or a stand-alone computer.

15. The method of claim 1, wherein the generated determination is for monitoring performance of the website or determining reimbursements for an advertising website that refers website visitors to the website.

16. The method of claim 1 further comprising:

generating a website usage assessment based upon the generated determination.

17. The method of claim 16, wherein the generated website usage assessment comprises statistics regarding customer activity on the website.

18. The method of claim 17, wherein a modification to the website is based upon the generated website usage assessment;

wherein the modification comprises providing different content on the website that includes different product or service offerings.

19. A system for operation upon a data processing device to analyze session data generated by a website in response to a visitor requesting data from the website, comprising:

instructions for execution on a processor-implemented system and for receiving the session data;

instructions for execution on the processor-implemented system and for analyzing the session data to determine a plurality of website interaction behavioral metrics of the session data;

wherein the website interaction behavioral metrics represent aspects of behavior related to the visitor from which the session results;

instructions for execution on the processor-implemented system and for comparing the website interaction behavioral metrics of the session data to detection settings;

wherein the detection settings are threshold values for detecting whether session data results from a human visitor or a non-human visitor; and

instructions for execution on a processor-implemented system and for generating a determination regarding whether the visitor to the website was human or non-human based upon said comparing;

wherein the generated determination is provided to a computer-readable storage medium and is indicative of whether website activity associated with the visitor comprises human or non-human website activity.

20. Computer-readable storage medium or mediums encoded with instructions that cause a computer to perform a method for analyzing session data generated by a website in response to a visitor requesting data from the website, said method comprising:

executing instructions on a processor-implemented system for receiving the session data;

executing instructions on the processor-implemented system for analyzing the session data to determine a plurality of website interaction behavioral metrics of the session data;

wherein the website interaction behavioral metrics represent aspects of behavior related to the visitor from which the session results;

executing instructions on the processor-implemented system for comparing the website interaction behavioral metrics of the session data to detection settings;

wherein the detection settings are threshold values for detecting whether session data results from a human visitor or a non-human visitor; and

executing instructions on the processor-implemented system for generating a determination regarding whether the visitor to the website was human or non-human based upon said comparing;

wherein the generated determination is provided to a computer-readable storage medium and is indicative of whether website activity associated with the visitor comprises human or non-human website activity.