Method and system for providing targeted content to a surfer

• US 9,396,436 B2
• Filed: 12/24/2014
• Issued: 07/19/2016
• Est. Priority Date: 07/25/2008
• Status: Active Grant

• Current Assignee: LivePerson Incorporated
• Original Assignee: LivePerson Incorporated
• Inventors: Lahav, Shlomo
• Primary Examiner(s): BILGRAMI, ASGHAR H
• Application Number:
  US14/582,550
• Publication Number:
  US 20150213363A1
• Time in Patent Office: 573 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/9577 Optimising the visualization of content, e.g. distillation of HTML documents
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0251 Targeted advertisements

Abstract

A system and method for providing targeted content to a surfer is disclosed. Exemplary embodiments of the present invention seek to provide novel solutions for determining which content object, taken from a group of content objects, will be best suited for presentation in association with a link on a web page that has been requested by a certain surfer. Exemplary types of content objects may comprise the text, topic, font, color or other attribute of an external advertisement or internal advertisement. Still other content objects may comprise the specific design of the object, an image, the design of the page in which the object is presented, etc. The decision process for selecting a content object can be based on predictive information that is associated with the request, such as a common HTTP request, or historical information about the surfer. Exemplary associated predictive information may include the day and time of receipt of the request for the web page, the IP address and\or domain from which the request was sent, the type and the version of the browser application that is used for requesting the web page, or the URL used by a surfer for requesting the web page with the parameters that are attached to the URL.

Claims

1. A computer-implemented method, comprising:

generating a predictive model for a content object, wherein a predictive model is generated using predictive information related to a selected content object, wherein a predictive model includes a predictive factor used to calculate a predictive value, and wherein a predictive value corresponds to a likelihood that an object will be selected when presented within a web page;

designating a first set of sources as control sources and designating a second set of sources as common sources, wherein a control source includes a source for which a content object is randomly selected for presentation, and wherein a common source includes a source for which a content object is selected for presentation using a predictive model for that content object;

monitoring a performance of the predictive model, wherein monitoring includes determining selection or non-selection of the content object associated with the predictive model, and wherein monitoring includes determining whether the content object is selected by a control source or a common source;

generating a comparison table for the predictive model, wherein the comparison table includes a probability of success value associated with a control source and a probability of success value associated with a common source, and wherein a probability of success value represents a probability that a content object associated with a predictive model will be selected;

comparing the probability of success value associated with the control source and the probability of success value associated with the common source to one or more predetermined values; and

determining whether to use the predictive model to select the content object for inclusion in a configuration of content objects presented within the web page, wherein the predictive model is used when the probability of success value associated with the control source and the probability of success value associated with the common source exceed the one or more predetermined values.

2. The method of claim 1, further comprising:

selecting the content object for presentation within a web page, wherein the content object is randomly selected for presentation within the web page from a group of content objects;

monitoring responses to the content object, wherein responses to a content object include selection of the content object from the web page or non-selection of the content object;

retrieving the predictive information related to a selected content object, wherein the selected content object is selected from the web page; and

generating the predictive model for the selected content object using the retrieved predictive information.

3. The method of claim 1, wherein the predictive information includes behavioral information and information associated with the one or more responses to the one or more content objects.

4. The method of claim 3, wherein the behavioral information includes a time of one or more previous visits in a domain that includes a requested web page, a time that the web page was last requested, a number of visits in the domain, a number of times that the object has been presented, and a number of times that the object has been selected.

5. The method of claim 4, wherein the behavioral information is from a single resource.

6. The method of claim 4, wherein the behavioral information is stored in a cookie.

7. The method of claim 3, 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 browser application.

8. A system, comprising:

a processor; and

a non-transitory computer-readable storage medium containing instructions configured to cause the processor to perform operations including;

generating a predictive model for a content object, wherein a predictive model is generated using predictive information related to a selected content object, wherein a predictive model includes a predictive factor used to calculate a predictive value, and wherein a predictive value corresponds to a likelihood that an object will be selected when presented within a web page;

designating a first set of sources as control sources and designating a second set of sources as common sources, wherein a control source includes a source for which a content object is randomly selected for presentation, and wherein a common source includes a source for which a content object is selected for presentation using a predictive model for that content object;

monitoring a performance of the predictive model, wherein monitoring includes determining selection or non-selection of the content object associated with the predictive model, and wherein monitoring includes determining whether the content object is selected by a control source or a common source;

generating a comparison table for the predictive model, wherein the comparison table includes a probability of success value associated with a control source and a probability of success value associated with a common source, and wherein a probability of success value represents a probability that a content object associated with a predictive model will be selected;

comparing the probability of success value associated with the control source and the probability of success value associated with the common source to one or more predetermined values; and

determining whether to use the predictive model to select the content object for inclusion in a configuration of content objects presented within the web page, wherein the predictive model is used when the probability of success value associated with the control source and the probability of success value associated with the common source exceed the one or more predetermined values.

9. The system of claim 8, further comprising instructions configured to cause the processor to perform operations including:

selecting the content object for presentation within a web page, wherein the content object is randomly selected for presentation within the web page from a group of content objects;

monitoring responses to the content object, wherein responses to a content object include selection of the content object from the web page or non-selection of the content object;

retrieving the predictive information related to a selected content object, wherein the selected content object is selected from the web page; and

generating the predictive model for the selected content object using the retrieved predictive information.

10. The system of claim 8, wherein the predictive information includes behavioral information and information associated with the one or more responses to the one or more content objects.

11. The system of claim 10, wherein the behavioral information includes a time of one or more previous visits in a domain that includes a requested web page, a time that the web page was last requested, a number of visits in the domain, a number of times that the object has been presented, and a number of times that the object has been selected.

12. The system of claim 11, wherein the behavioral information is from a single resource.

13. The system of claim 11, wherein the behavioral information is stored in a cookie.

14. The system of claim 10, 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 browser application.

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

generate a predictive model for a content object, wherein a predictive model is generated using predictive information related to a selected content object, wherein a predictive model includes a predictive factor used to calculate a predictive value, and wherein a predictive value corresponds to a likelihood that an object will be selected when presented within a web page;

designate a first set of sources as control sources and designating a second set of sources as common sources, wherein a control source includes a source for which a content object is randomly selected for presentation, and wherein a common source includes a source for which a content object is selected for presentation using a predictive model for that content object;

monitor a performance of the predictive model, wherein monitoring includes determining selection or non-selection of the content object associated with the predictive model, and wherein monitoring includes determining whether the content object is selected by a control source or a common source;

generate a comparison table for the predictive model, wherein the comparison table includes a probability of success value associated with a control source and a probability of success value associated with a common source, and wherein a probability of success value represents a probability that a content object associated with a predictive model will be selected;

compare the probability of success value associated with the control source and the probability of success value associated with the common source to one or more predetermined values; and

determine whether to use the predictive model to select the content object for inclusion in a configuration of content objects presented within the web page, wherein the predictive model is used when the probability of success value associated with the control source and the probability of success value associated with the common source exceed the one or more predetermined values.

16. The computer-program product of claim 15, further comprising instructions configured to cause the data processing apparatus to:

select the content object for presentation within a web page, wherein the content object is randomly selected for presentation within the web page from a group of content objects;

monitor responses to the content object, wherein responses to a content object include selection of the content object from the web page or non-selection of the content object;

retrieve the predictive information related to a selected content object, wherein the selected content object is selected from the web page; and

generate the predictive model for the selected content object using the retrieved predictive information.

17. The computer-program product of claim 15, wherein the predictive information includes behavioral information and information associated with the one or more responses to the one or more content objects.

18. The computer-program product of claim 17, wherein the behavioral information includes a time of one or more previous visits in a domain that includes a requested web page, a time that the web page was last requested, a number of visits in the domain, a number of times that the object has been presented, and a number of times that the object has been selected.

19. The computer-program product of claim 18, wherein the behavioral information is stored in a cookie.

20. 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 browser application.