Method and system for creating a predictive model for targeting web-page to a surfer
View Patent ↗A system and a method for creating a predictive model to select an object from a group of objects that can be associated with a requested web-page, wherein a configuration of the requested web-page defines a subgroup of one or more selected objects from the group of objects. Each web-page can include one or more links to be associated with content objects from the group. For each content object presented over a requested web-page, one or more predictive model with relevant predictive factors is processed such that the predicted objective, the probability of success for example, is calculated. A success is defined as a surfer responding to the presented content according to the preferences of the site owner. Each predicted model can be associated with a key-performance indicator (KPI). Further, a predictive model can reflect the number of times the surfer requested the web page during the surfer's visit.
1. A computer-implemented method, comprising:
generating, by a computing device, a plurality of predictive models for a web page of a website, wherein the web page includes a configuration defining one or more objects presented with the web page, wherein each object is associated with a predictive model, and wherein each predictive model is associated with one or more predictive model types;
determining the one more predictive model types that are associated with each predictive model in the plurality of predictive models;
determining a performance indicator that corresponds to each determined predictive model type, wherein performance indicators represent one or more benefits to a website;
selecting a predictive model out of the plurality of predictive models based on a performance indicator corresponding to a predictive model type of the selected predictive model; and
determining a configuration of the web page using the selected predictive model.
2. The method of claim 1 , wherein selecting the predictive model out of the plurality of predictive models is further based on a readiness of the selected predictive model.
3. The method of claim 1 , wherein performance indicators include a rate of clicking on an object, a rate of converting the object to a purchase, or a revenue rate generated by presenting a configuration of the web page.
4. The method of claim 1 , further comprising:
gradually migrating over time from using a first type of predictive model associated with a first performance indicator to using a second type of predictive model associated with a second performance indicator.
5. The method of claim 1 , further comprising:
receiving a request for the web page;
retrieving predictive information related to the request;
converting the predictive information into one or more predictive factors for an object presented with the web page;
defining a value for each of the one or more predictive factors; and
generating a predictive model for the object using the one or more predictive factors.
6. The method of claim 5 , wherein the predictive information includes behavioral information and information associated with the request for the web page.
7. The method of claim 6 , wherein the behavioral information includes a time of one or more previous visits in a domain that includes the 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.
8. The method of claim 7 , wherein the behavioral information is from a single resource.
9. The method of claim 7 , wherein the behavioral information is stored in a cookie.
10. The method of claim 6 , wherein the information associated with the request for the web page includes a receipt time of the request, a uniform resource locator key associated with the request, an internet protocol address, or a type of browser application.
11. 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 plurality of predictive models for a web page of a website, wherein the web page includes a configuration defining one or more objects presented with the web page, wherein each object is associated with a predictive model, and wherein each predictive model is associated with one or more predictive model types;
determining the one more predictive model types that are associated with each predictive model in the plurality of predictive models;
determining a performance indicator that corresponds to each determined predictive model type, wherein performance indicators represent one or more benefits to a website;
selecting a predictive model out of the plurality of predictive models based on a performance indicator corresponding to a predictive model type of the selected predictive model; and
determining a configuration of the web page using the selected predictive model.
12. The system of claim 11 , wherein selecting the predictive model out of the plurality of predictive models is further based on a readiness of the selected predictive model.
13. The system of claim 11 , wherein performance indicators include a rate of clicking on an object, a rate of converting the object to a purchase, or a revenue rate generated by presenting a configuration of the web page.
14. The system of claim 11 , further comprising instructions configured to cause the processor to perform operations including:
gradually migrating over time from using a first type of predictive model associated with a first performance indicator to using a second type of predictive model associated with a second performance indicator.
15. The system of claim 11 , further comprising instructions configured to cause the processor to perform operations including:
receiving a request for the web page;
retrieving predictive information related to the request;
converting the predictive information into one or more predictive factors for an object presented with the web page;
defining a value for each of the one or more predictive factors; and
generating a predictive model for the object using the one or more predictive factors.
16. The system of claim 15 , wherein the predictive information includes behavioral information and information associated with the request for the web page.
17. The system of claim 16 , wherein the behavioral information includes a time of one or more previous visits in a domain that includes the 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.
18. The system of claim 17 , wherein the behavioral information is from a single resource.
19. The system of claim 17 , wherein the behavioral information is stored in a cookie.
20. The system of claim 16 , wherein the information associated with the request for the web page includes a receipt time of the request, a uniform resource locator key associated with the request, an internet protocol address, or a type of browser application.
21. 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 plurality of predictive models for a web page of a website, wherein the web page includes a configuration defining one or more objects presented with the web page, wherein each object is associated with a predictive model, and wherein each predictive model is associated with one or more predictive model types;
determine the one more predictive model types that are associated with each predictive model in the plurality of predictive models;
determine a performance indicator that corresponds to each determined predictive model type, wherein performance indicators represent one or more benefits to a website;
select a predictive model out of the plurality of predictive models based on a performance indicator corresponding to a predictive model type of the selected predictive model; and
determine a configuration of the web page using the selected predictive model.
22. The computer-program product of claim 21 , wherein selecting the predictive model out of the plurality of predictive models is further based on a readiness of the selected predictive model.
23. The computer-program product of claim 21 , wherein performance indicators include a rate of clicking on an object, a rate of converting the object to a purchase, or a revenue rate generated by presenting a configuration of the web page.
24. The computer-program product of claim 21 , further comprising instructions configured to cause the data processing apparatus to:
gradually migrate over time from using a first type of predictive model associated with a first performance indicator to using a second type of predictive model associated with a second performance indicator.
25. The computer-program product of claim 21 , further comprising instructions configured to cause the data processing apparatus to:
receive a request for the web page;
retrieve predictive information related to the request;
convert the predictive information into one or more predictive factors for an object presented with the web page;
define a value for each of the one or more predictive factors; and
generate a predictive model for the object using the one or more predictive factors.
26. The computer-program product of claim 25 , wherein the predictive information includes behavioral information and information associated with the request for the web page.
27. The method of claim 26 , wherein the behavioral information includes a time of one or more previous visits in a domain that includes the 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.
28. The computer-program product of claim 27 , wherein the behavioral information is from a single resource.
29. The computer-program product of claim 27 , wherein the behavioral information is stored in a cookie.
30. The computer-program product of claim 26 , wherein the information associated with the request for the web page includes a receipt time of the request, a uniform resource locator key associated with the request, an internet protocol address, or a type of browser application.