Use of behavioral portraits in web site analysis

• US 9,646,322 B2
• Filed: 01/17/2014
• Issued: 05/09/2017
• Est. Priority Date: 02/01/2007
• Status: Active Grant

• Current Assignee: III Holdings 4, LLC (Intellectual Ventures LLC)
• Original Assignee: III Holdings 4, LLC (Intellectual Ventures LLC)
• Inventors: Minnis, William Charles, Nagaitis, Mark, Pokorney, Trevor, Cowin, Richard, Gugliemetti, Brian, Miers, Steven, Schank, Eric
• Primary Examiner(s): Civan, Ethan D
• Application Number:
  US14/158,245
• Publication Number:
  US 20140214483A1
• Time in Patent Office: 1,208 Days
• Field of Search: 705 261- 272
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• 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 30/0244 Optimization
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0641 Shopping interfaces
• 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 method is provided for determining a website user behavioral portrait based on navigation on the website and dynamically reconfiguring web pages based on those portraits. In accordance with the method, data relating to the progress of a user through a website is recorded, and an ongoing behavioral portrait of the user is built based on the data. The portrait is then used to dynamically reconfigure web content.

Claims

1. A non-transitory computer readable medium storing instructions that, in response to execution, cause a system comprising a processor to perform operations, comprising:

recording clickstream data relating to online behavior associated with input from accounts interacting with a website;

generating respective behavioral portraits for the accounts based on applying psychological portrait scoring to the clickstream data, wherein the generating the respective behavioral portraits comprises applying psychological behavior model scoring to a set of actions taken in association with one of the accounts during the interacting with the website, and wherein the set of actions includes at least one of a navigation to a page during the interacting with the website, a clicking on of an item during the interacting with the website, an entering of a search term during the interacting with the website, a receipt of check-out information relating to a check out transaction that occurred during the interacting with the website, an abandonment of a page during the interacting with the website, or a selection of a top set of items during the interacting with the website;

categorizing the respective behavioral portraits into portrait types;

analyzing the online behavior of the accounts as a function of the portrait types;

based on the analyzing, identifying a portrait type of the portrait types where the online behavior yields an expected result;

from content associated with the website, generating modified content for the portrait type; and

in response to an account associated with the portrait type being determined to be associated with an interaction of the interacting with the website from a device, transmitting to the device the modified content during the interaction.

2. The non-transitory computer readable medium of claim 1, wherein the set of actions further relates to at least one of a number of times the website is abandoned, a number of return visits to the website, a number of online purchases made during the navigation of the web site, an average time spent on the website during the navigation, or a number of pages visited on the website during the navigation.

3. The non-transitory computer readable medium of claim 1, wherein the clickstream data is measured over a defined period of time.

4. The non-transitory computer readable medium of claim 1, wherein the analyzing the online behavior of the accounts as the function of the portrait types comprises determining a relative frequency with which the items are clicked on as the function of the portrait types.

5. The non-transitory computer readable medium of claim 1, wherein the analyzing the online behavior of the accounts as the function of the portrait types comprises determining a relative frequency with which the website is abandoned as the function of the portrait types.

6. The non-transitory computer readable medium of claim 1, wherein the analyzing the online behavior of the accounts as the function of the portrait types comprises determining a relative frequency of return visits to the website as the function of the portrait types.

7. The non-transitory computer readable medium of claim 1, wherein the analyzing the online behavior of the accounts as the function of the portrait types comprises determining a relative frequency of online purchases on the website as the function of the portrait types.

8. The non-transitory computer readable medium of claim 1, wherein the analyzing the online behavior of the accounts as the function of the portrait types comprises determining an average time spent on the website as the function of the portrait types.

9. The non-transitory computer readable medium of claim 1, wherein the analyzing the online behavior of the accounts as the function of the portrait types comprises determining an average number of pages visited on the website as the function of the portrait types.

10. The non-transitory computer readable medium of claim 1, wherein the operations further comprise outputting graphical information representing the clickstream data as the function of the portrait types.

11. A method, comprising:

categorizing, by a system comprising a processor, features appearing on a web page in terms of at least one behavioral trait indicative of selection of the features by input associated with accounts, wherein the categorizing of the features includes at least one of categorizing pages to which were navigated during a navigation of the web page, categorizing a feature as one determined to have been clicked on, categorizing a search term received by the web page, categorizing check-out information related to a check out conducted via the web page, categorizing pages determined to have been abandoned during the navigation of the web page, or categorizing a selection of a top number of items that satisfy a criterion during the navigation of the web page;

creating, by the system, a graphical overlay that which reflects results of the categorizing of the features, wherein the graphical overlay depicts a mapping of the features of the web page to rules for generating behavioral portraits;

using, by the system, the results of the categorizing of the features to create respective behavioral portraits of the accounts determined to be accessing the web page, wherein the respective behavioral portraits are generated by applying psychological portrait scoring to the selection of the features and the rules; and

displaying, by the system on a display device, the web page with the graphical overlay superimposed on the web page.

12. The method of claim 11, wherein the mapping is a color-coded map.

13. The method of claim 11, wherein the features comprise links on the web page.

14. The method of claim 11, wherein the respective behavioral portraits are further generated by applying a psychological behavior model scoring to actions taken as represented by the input.

15. The method of claim 11, wherein a behavioral portrait of the respective behavioral portraits is a numerical score derived from applying meta linguistic psychological analysis to the clickstream data.

16. The method of claim 11, wherein a behavioral portrait of the respective behavioral portraits is a numerical score derived from actions as represented by the input resulting in progress through the website, wherein the actions are weighted with weights by category and lexical analysis, and wherein the weights are based on possible actions that are able to be taken as the progress through the web page occurs.

17. The method of claim 11, wherein the operations further comprise recommending changes to a manner in which content is presented on the web page in association with a subset of the accounts of a specified portrait type.

18. The method of claim 11, wherein the respective behavioral portraits are respective psychological portraits.

19. The method of claim 11, wherein the respective behavioral portraits for the accounts comprise respective psychological profiles as pertaining to preferences in a defined situation during the navigation of the web page.

20. The method of claim 11, wherein the respective behavioral portraits for the accounts comprise respective preferred decision-making approaches to be employed during the navigation of the web page.

21. The method of claim 11, wherein the respective behavioral portraits for the accounts comprise respective motivations for making a purchase via the web page.

22. The method of claim 11, wherein the respective behavioral portraits for the accounts comprise respective preferred manners in which to present information.

23. The method of claim 11, wherein the respective behavioral portraits for the accounts comprise respective preferred manners in which to present information, respective preferred decision-making approaches, and respective motivations for making a purchase via the web page.

24. A system, comprising:

a processor; and

a memory communicatively coupled to the processor, the memory having stored therein computer-executable instructions, comprising;

a customer portrait engine configured to;

record data relating to online behavior associated with accounts during interactions with a website;

create respective behavioral portraits for the accounts based on the data, wherein the respective behavioral portraits are generated by applying psychological behavior model scoring to a set of actions taken in association with an account of the accounts during one of the interactions with the website, and wherein the set of actions includes at least one of navigation to pages during the interactions with the website, items clicked on during the interactions with the website, search terms entered during the interactions with the website, generation of check-out information relating to a check out transaction that occurred during the interactions with the website, abandonment of pages during the interactions with the website, or a selection of top set of items during the interactions with the website;

categorize the behavioral portraits into respective portrait types;

analyze the online behavior associated with the accounts on the website as a function of the respective portrait types;

based on the analysis, identify a portrait type where the online behavior does meet an expected result;

generate modified content, from content associated with the website, for the portrait type; and

in response to an account of the accounts associated with the portrait type being determined to be associated with an interaction of the interactions with the website from a device, initiate a transmission of the modified content to the device during the interaction.

25. The system of claim 24, wherein the customer portrait engine is further configured to analyze the online behavior of the accounts as the function of the portrait types by determining, for the accounts, respective preferred manners in which to make decisions during the interactions with the website, and ascertaining respective degrees to which the website accommodates the respective preferred manners in which to make decisions during the interactions with the website.