SYSTEM FOR RATING QUALITY OF ONLINE VISITORS

• US 20080306830A1
• Filed: 06/07/2007
• Published: 12/11/2008
• Est. Priority Date: 06/07/2007
• Status: Abandoned Application

• Current Assignee: Cliquality, LLC
• Original Assignee: Cliquality, LLC
• Inventors: Lasa, Ricardo, Berndt, Donald
• Application Number:
  US11/759,889
• Publication Number:
  US 20080306830A1
• Time in Patent Office: Days
• US Class Current: 705/26
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0214 Referral reward systems
• CPC Class Codes: G06Q 30/0283 Price estimation or determination

Abstract

A system for determine session, visitor, advertiser and/or website click quality scores includes a data warehouse collected from a plurality of websites, a method of determining whether a goal established for a website is achieved, a data mining system for adjusting the value of certain actions taken by a visitor to a website in accomplishing the websites ultimate goal, and a subsystem for reporting click quality scores to users of the system. For example, the system uses a script included in each page of each website monitored by the system to capture data in the data warehouse. The method for determining whether a goal is achieved may include assigning a website goal associated with access to a category of a page and recording the achievement of the goal or goals, when a visitor in a session accesses a page or pages of the specified category. The subsystem for reporting may assist in analyzing the quality of visitors, the quality of visitors referred by a particular referral source, and the quality of a website, including any effects of changes made to the website or in comparison to other websites monitored by the system.

Claims

1. A system for rating click quality of websites, comprising:

assigning each of a plurality of website pages to one of a plurality of page categories, and assigning at least one of the plurality of page categories as a goal of the website;

monitoring the plurality of website pages of a plurality of websites;

determining the start of an online session by a visitor to one of the plurality of website pages;

assigning the visitor a visitor id;

identifying any referring website from which the visitor originated;

tracking the activity of the online session;

recording session data for each session and each page category visited, including a session id, a number of times that pages of each page category were accessed by the visitor, and at least one parameter related to the duration of access by the visitor to each of the page categories visited by the visitor during the online session.

2. The system of claim 1, wherein the step of recording includes recording a minimum access time for each page category visited during the session.

3. The system of claim 1, wherein the step of recording includes recording a maximum access time for each page category visited during the session.

4. The system of claim 1, wherein the step of recording includes recording a mean or median access time for each page category visited during the session.

5. The system of claim 4, wherein the step of recording includes recording the mean access time.

6. The system of claim 5, wherein the step of recording the mean access time includes summing the total duration of access by the visitor to all pages of the same page category and dividing the sum of the total duration of access by the number of times that pages of the same page category were accessed by the visitor during a session, and storing the result of the step of dividing in the database such that the result of the step of dividing is associated with the session id.

7. The system of claim 6, wherein the step of recording includes recording a standard deviation of the mean access time.

8. The system of claim 1, wherein the step of recording includes recording a minimum access time, a maximum access time, and an indicator of average access time for each page category accessed, the indicator of average access time selected from the group consisting of a mean access time, a median access time, and both a mean access time and a median access time for each page category visited during the session.

9. The system of claim 8, wherein the step of recording includes recording a mean access time.

10. The system of claim 9, wherein the step of recording includes saving the data to a field in a database.

11. The system of claim 10, further comprising:

repeating the steps of monitoring, determining, assigning, identifying, tracking, and recording for a plurality of online sessions of a plurality of websites;

recording the data for each of the plurality of online sessions in a database;

analyzing the data in the database; and

determining a session quality score.

12. The system of claim 11, wherein determining the session quality score includes associating data about a plurality of online sessions in the database to the achievement of the goal of the website, and calculating the session quality score using a data mining tool, a neural network, or both a data mining tool and a neural network.

13. The system of claim 12, wherein determining the session quality score includes limiting data to data for a single one of the plurality of websites.

14. The system of claim 12, wherein determining the session quality score includes using data recorded from a plurality of websites during the step of associating data about a plurality of online sessions.

15. The system of claim 14, wherein the plurality of websites used in the step of using data includes limiting the plurality of websites to websites of a single industry classification code or a single type of website.

16. The system of claim 15, wherein the plurality of websites used in the step of using data are all online retail websites.

17. The system of claim 1, further comprising:

repeating the steps of monitoring, determining, assigning, identifying, tracking, and recording for a plurality of online sessions of a plurality of websites;

recording the data for each of the plurality of online sessions in a database;

analyzing the data in the database; and

determining a session quality score.

18. The system of claim 17, further comprising determining a visitor quality score by comparing each of the plurality of online sessions associated with a single visitor id with a plurality of the plurality of online sessions associated with a plurality of visitor id'"'"'s, and calculating a comparative rating based on how closely associated the pattern of the plurality of online sessions associated with the single visitor id is with achieving at least one of the goals of at least one of the websites.

19. The system of claim 18, wherein the step of determining the visitor quality score calculates the visitor quality score as a comparative rating based on how closely associated the pattern of the plurality of online sessions associated with the single visitor id is with achieving at least one of the goals over a plurality of the websites.

20. The system of claim 19, wherein the plurality of the websites are limited to a same website type or a same industry code associated with the websites in the database.

21. The system of claim 17, further comprising:

calculating a referral website quality score.

22. The system of claim 18, further comprising:

calculating a referral website quality score.

23. The system of claim 19, further comprising:

calculating a referral website quality score.

24. The system of claim 20, further comprising:

calculating a referral website quality score.

25. The system of claim 21, further comprising:

establishing an advertising pricing rate based at least in part on the referral website quality score.

26. The system of claim 25, wherein the step of establishing includes adjusting the advertising pricing rate based on a ratio of the referral website quality score and a mean referral website quality store or a ratio of the referral website quality score and a median referral website quality score.

27. The system of claim 26, wherein the step of establishing uses the mean referral website quality store calculated from data limited to the same industry code or the same website type.

28. The system of claim 27, wherein the step of establishing uses the mean referral website quality score calculated from data limited to both the same industry code and the same website type.

29. The system of claim 17, further comprising:

ranking a plurality of referral sources by comparing the referral website quality score of each of the plurality of referral sources within a defined category of referral sources.

30. The system of claim 29, wherein the defined category of referral sources is selected from the categories consisting of search engines, news outlets, blogs, auction sites, and social networks.

31. The system of claim 11, further comprising:

establishing an advertising rate based at least in part on the session quality score.

32. The system of claim 19, further comprising:

blacklisting a visitor based, at least in part, on the visitor quality score of the visitor.

33. The system of claim 21, further comprising:

blacklisting an advertiser based, at least in part, on the referral website quality score.

34. The system of claim 19, further comprising:

weighting of factors used in determining the visitor quality score, distinguishing low quality visitors, who are unlikely to reach the goal of the website, from high quality visitors, who are most likely to reach the goal of the website.

35. The system of claim 34, wherein the step of weighting includes adjusting the weighting based on dynamic data analysis.

36. The system of claim 1, wherein the step of tracking includes at least one script embedded on each of the plurality of website pages, at least one of the at least one scripts capturing and reporting access by the visitor to one of the plurality of website pages to the system.

37. The system of claim 36, wherein at least one of the at least one scripts captures and reports to the system when a desired intermediate or a desired ultimate goal is achieved by accessing one of the plurality of the plurality of website pages.

38. The system of claim 37, wherein a session including access to the website page associated with an ultimate goal of the website achieves the highest session quality score.

39. The system of claim 38, further comprising:

training a neural network to provide a neural network score from 0 to 1; and

converting the neural network score to an integer quality score from 1 to 10.