METHOD AND SYSTEM FOR CREATING A PREDICTIVE MODEL FOR TARGETING WEB-PAGE TO A SURFER

• US 20170011146A1
• Filed: 06/14/2016
• Published: 01/12/2017
• Est. Priority Date: 07/25/2008
• Status: Active Grant

• Current Assignee: LivePerson Incorporated
• Original Assignee: LivePerson Incorporated
• Inventors: LAHAV, Shlomo, RON, Ofer
• Granted Patent: US 11,263,548 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/046 Forward inferencing; Production systems
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Systems and methods for determining predictive model types are provided. A method may include generating a predictive model for a web page of a web site, wherein the web page includes a configuration defining one or more objects presented with the web page, and wherein each object is associated with a predictive model. The method may include determining one or more predictive model types that are associated with the predictive model, determining one or more performance indicators that correspond to each determined predictive model type, wherein performance indicators represent one or more benefits to a website, selecting a predictive model type of the predictive model out of the one or more predictive model types, wherein the predictive model type is selected based on a performance indicator corresponding to the selected predictive model type, and determining a configuration of the web page using the selected predictive model type of the predictive model.

Claims

1. (canceled)

2. A computer-implemented method, comprising:

generating, by a computing device, a plurality of predictive models for an application, wherein the application is associated with a configuration defining one or more objects for presentation in a window of the application, wherein an object is associated with a predictive model including one or more predictive factors, wherein a predictive factor of a predictive model is used to calculate a predictive value for the predictive model, and wherein the predictive value predicts a property of an object associated with the predictive model;

receiving a request for content associated with the application, wherein the request includes predictive information;

determining the predictive information associated with the request;

determining values of predictive factors for the plurality of predictive models, wherein the values are determined using the predictive information;

determining multiple configurations of the application, wherein each configuration includes one or more different objects for presentation with the content;

determining predictive values for the multiple configurations of the application using the determined values of the predictive factors, wherein a predictive value of a configuration includes a combination of predictive values of predictive models associated with objects making up the configuration;

selecting a configuration from the multiple configurations with a highest predictive value; and

providing the selected configuration for presentation by the application.

3. The method of claim 2, wherein determining the multiple configurations of the application includes determining one or more objects to present in each configuration.

4. The method of claim 2, wherein the predictive information includes behavioral information and information associated with one or more responses to one or more objects.

5. The method of claim 4, wherein the behavioral information includes a time of a previous request associated with content of the application, a time that the content was last requested, a number of visits to the application, a number of times that an object has been presented, and a number of times that the object has been selected.

6. The method of claim 4, wherein the information associated with the one or more responses to the one or more content objects includes a receipt time of a response, a uniform resource locator key associated with the response, an internet protocol address, or a type of application.

7. The method of claim 2, wherein the application includes a mobile website.

8. The method of claim 2, wherein the application includes a mobile application.

9. A system, comprising:

a processor;

a non-transitory computer-readable storage medium containing instructions which when executed on the processor, cause the processor to perform operations including;

generating a plurality of predictive models for an application, wherein the application is associated with a configuration defining one or more objects for presentation in a window of the application, wherein an object is associated with a predictive model including one or more predictive factors, wherein a predictive factor of a predictive model is used to calculate a predictive value for the predictive model, and wherein the predictive value predicts a property of an object associated with the predictive model;

receiving a request for content associated with the application, wherein the request includes predictive information;

determining the predictive information associated with the request;

determining values of predictive factors for the plurality of predictive models, wherein the values are determined using the predictive information;

determining multiple configurations of the application, wherein each configuration includes one or more different objects for presentation with the content;

determining predictive values for the multiple configurations of the application using the determined values of the predictive factors, wherein a predictive value of a configuration includes a combination of predictive values of predictive models associated with objects making up the configuration;

selecting a configuration from the multiple configurations with a highest predictive value; and

providing the selected configuration for presentation by the application.

10. The system of claim 9, wherein determining the multiple configurations of the application includes determining one or more objects to present in each configuration.

11. The system of claim 9, wherein the predictive information includes behavioral information and information associated with one or more responses to one or more objects.

12. The system of claim 11, wherein the behavioral information includes a time of a previous request associated with content of the application, a time that the content was last requested, a number of visits to the application, a number of times that an object has been presented, and a number of times that the object has been selected.

13. The system of claim 11, wherein the information associated with the one or more responses to the one or more content objects includes a receipt time of a response, a uniform resource locator key associated with the response, an internet protocol address, or a type of application.

14. The system of claim 9, wherein the application includes a mobile website.

15. The system of claim 9, wherein the application includes a mobile application.

16. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause a data processing apparatus to:

generate a plurality of predictive models for an application, wherein the application is associated with a configuration defining one or more objects for presentation in a window of the application, wherein an object is associated with a predictive model including one or more predictive factors, wherein a predictive factor of a predictive model is used to calculate a predictive value for the predictive model, and wherein the predictive value predicts a property of an object associated with the predictive model;

receive a request for content associated with the application, wherein the request includes predictive information;

determine the predictive information associated with the request;

determine values of predictive factors for the plurality of predictive models, wherein the values are determined using the predictive information;

determine multiple configurations of the application, wherein each configuration includes one or more different objects for presentation with the content;

determine predictive values for the multiple configurations of the application using the determined values of the predictive factors, wherein a predictive value of a configuration includes a combination of predictive values of predictive models associated with objects making up the configuration;

select a configuration from the multiple configurations with a highest predictive value; and

provide the selected configuration for presentation by the application.

17. The computer-program product of claim 16, wherein the predictive information includes behavioral information and information associated with one or more responses to one or more objects.

18. The computer-program product of claim 17, wherein the behavioral information includes a time of a previous request associated with content of the application, a time that the content was last requested, a number of visits to the application, a number of times that an object has been presented, and a number of times that the object has been selected.

19. The computer-program product of claim 17, wherein the information associated with the one or more responses to the one or more content objects includes a receipt time of a response, a uniform resource locator key associated with the response, an internet protocol address, or a type of application.

20. The computer-program product of claim 16, wherein the application includes a mobile website.

21. The computer-program product of claim 16, wherein the application includes a mobile application.