Method for adjusting content of a webpage in real time based on users online behavior and profile
A method and system for providing adjusted content in a webpage are described. The system monitors traffic to a website and tracks users that are visiting the website to identify one or more parameters relating to relating to the user, including parameters associated with an identity of the user, navigation behavior for the user within the website, and usage of content by the user within the website. The system analyzes the parameters and selects at least one statistical algorithm for a type of the parameter, and based on the analysis, identifies an organization to which the user belongs. The system selects and presents content for the website to be presented to the user based on the analysis.
1. A method comprising:
monitoring traffic from a plurality of users to a website;
tracking a user from the plurality of users visiting the web site to identify a plurality of parameters relating to the user, including a first parameter associated with an identity of the user and a second parameter associated with navigation behavior for the user within the website;
based on selecting a statistical algorithm for each of the plurality of parameters corresponding to a type of parameter, applying a first statistical algorithm to analyze the first parameter associated with the identity of the user and a second statistical algorithm to analyze the second parameter associated with the navigation behavior for the user within the website;
based on applying the first statistical algorithm and the second statistical algorithm, identifying an organization to which the user belongs;
selecting content for the website to be presented to the user based on an analysis of each of the plurality of parameters according to the selected statistical algorithm, the organization to which the user belongs, and a marketing stage in a sale process for the user, wherein the content is selected from a plurality of content items stored in a content database; and
presenting the selected content in a webpage of the website to the user.
2. The method of claim 1 , wherein the first statistical algorithm or the second statistical algorithm comprises a clustering algorithm for classifying the user into one of a plurality of groups based on at least one of the plurality of parameters.
3. The method of claim 1 , wherein the second statistical algorithm comprises a probability algorithm for creating a probability tree based on identification of statistical correlation between a sequence of the navigation behavior of the user and content selections on the website.
4. The method of claim 1 , further comprising:
identifying a third parameter associated with usage of content by the user within the website; and
based on selecting the statistical algorithm for each of the plurality of parameters corresponding to the type of parameter, applying a third statistical algorithm to analyze the third parameter associated with usage of content by the user within the website.
5. The method of claim 4 , wherein the third statistical algorithm comprises a nearest neighbor algorithm for applying a collaborative filtering and classifying users into neighborhood groups based on content usage parameters.
6. The method of claim 1 , wherein the selected content is presented in a part of the webpage selected by parsing the webpage in real time.
7. The method of claim 1 , further comprising analyzing actions of the user interacting with the web site in relation to an increment of time between the actions of the user.
8. The method of claim 1 , further comprising:
generating an anonymous user profile for the user, the anonymous user profile including at least one of the plurality of parameters; and
storing the anonymous user profile corresponding to the user in a profile database.
9. The method of claim 1 , further comprising storing an analysis of each of the plurality of parameters according to the selected statistical algorithm in a unique caching repository and enabling real time statistics and data retrieval for user engagement.
10. The method of claim 1 , wherein selecting the content for the website comprises selecting the content based on a content-items-clustering algorithm, including classifying the plurality of content items into groups and analyzing a plurality of attributes of each one of the plurality of users who consumed each one of the plurality content items.
11. A system comprising:
at least one processor;
at least one non-transitory computer readable medium comprising instructions that, when executed by the at least one processor, cause the system to:
monitor traffic from a plurality of users to a website;
track a user from the plurality of users visiting the website to identify a plurality of parameters relating to the user, including a first parameter associated with an identity of the user and a second parameter associated with navigation behavior for the user within the website;
based on selecting a statistical algorithm for each of the plurality of parameters corresponding to a type of parameter, apply a first statistical algorithm to analyze the first parameter associated with the identity of the user and a second statistical algorithm to analyze the second parameter associated with the navigation behavior for the user within the website;
based on applying the first statistical algorithm and the second statistical algorithm, identify an organization to which the user belongs; and
select content for the website to be presented to the user based on an analysis of each of the plurality of parameters according to the selected statistical algorithm, the organization to which the user belongs, and a marketing stage in a sale process for the user, wherein the content is selected from a plurality of content items stored in a content database; and
present the selected content in a webpage of a website to the user.
12. The system of claim 11 , wherein the first statistical algorithm or the second statistical algorithm comprises a clustering algorithm for classifying the user into one of a plurality of groups based on at least one of the plurality of parameters.
13. The system of claim 11 , wherein the second statistical algorithm comprises a probability algorithm for creating a probability tree based on identification of statistical correlation between a sequence of the navigation behavior of the user and content selections on the website.
14. The system of claim 11 , further comprising instructions that, when executed by the at least one processor, cause the system to:
identify a third parameter associated with usage of content by the user within the website; and
based on selecting the statistical algorithm for each of the plurality of parameters corresponding to the type of parameter, apply a third statistical algorithm to analyze the third parameter associated with usage of content by the user within the website.
15. The system of claim 14 , wherein the third statistical algorithm comprises a nearest neighbor algorithm for applying a collaborative filtering and classifying users into neighborhood groups based on content usage parameters.
16. The system of claim 11 , wherein the selected content is presented in a part of the webpage selected by parsing the webpage in real time.
17. The system of claim 11 , further comprising instructions that, when executed by the at least one processor, cause the system to analyze actions of the user interacting with the website in relation to an increment of time between the actions of the user.
18. The system of claim 11 , further comprising instructions that, when executed by the at least one processor, cause the system to:
generate an anonymous user profile for the user, the anonymous user profile including at least one of the plurality of parameters; and
store the anonymous user profile corresponding to the user in a profile database.
19. The system of claim 11 , further comprising instructions that, when executed by the at least one processor, cause the system to:
store an analysis of each of the plurality of parameters according to the selected statistical algorithm in a unique caching repository; and
enable real time statistics and data retrieval for user engagement.
20. A non-transitory computer readable medium storing instructions thereon that, when executed by at least one processor, cause a computer system to:
monitor traffic from a plurality of users to a website;
track a user from the plurality of users visiting the website to identify a plurality of parameters relating to the user, including a first parameter associated with an identity of the user and a second parameter associated with navigation behavior for the user within the website;
based on selecting a statistical algorithm for each of the plurality of parameters corresponding to a type of parameter, apply a first statistical algorithm to analyze the first parameter associated with the identity of the user and a second statistical algorithm to analyze the second parameter associated with the navigation behavior for the user within the website;
based on applying the first statistical algorithm and the second statistical algorithm, identify an organization to which the user belongs; and
select content for the website to be presented to the user based on an analysis of each of the plurality of parameters according to the selected statistical algorithm, the organization to which the user belongs, and a marketing stage in a sale process for the user, wherein the content is selected from a plurality of content items stored in a content database; and
present the selected content in a webpage of the website to the user.