Systems and methods for webpage personalization
A system can include one or more processing modules and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processing modules and perform receiving, from an electronic device, a search query from a user of a plurality of users; processing first data; and facilitating displaying a set of items. Processing the first data can comprise determining one or more keywords by capturing the one or more keywords during a time window; creating a feature set of second data associated with at least a portion of the plurality of users; determining a set of items of the item set as being based at least in part on an item vector representation and a keyword vector representation; determining a respective purchase probability associated with each item of the set of items of the item set; ranking the set of items.
1. A system comprising:
one or more processing modules; and
one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processing modules and perform:
receiving, from an electronic device, a search query from a user of a plurality of users;
processing first data associated with the search query by:
determining one or more keywords by capturing the one or more keywords associated with the search query during a time window;
determining two or more items by:
capturing the two or more items associated with the search query; and
forming an item set comprising the two or more items associated with the search query;
creating a feature set of second data associated with at least a portion of the plurality of users;
determining a set of items of the item set as being associated with the search query based at least in part on an item vector representation and a keyword vector representation;
determining a respective purchase probability associated with each item of the set of items of the item set based at least in part on a respective score for the each item; and
ranking the set of items based at least in part on the respective purchase probability; and
facilitating displaying, on a display screen of the electronic device, of the set of items, as ranked.
2. The system of claim 1 , wherein:
the computing instructions are further configured to perform:
creating a text corpus comprising:
the search query of the user of the plurality of users; and
an item activity associated with a browse session.
3. The system of claim 1 , wherein:
the computing instructions are further configured to perform:
determining a user purchase probability that the user will purchase a first item of the two or more items at a particular time based at least in part on a first item score for the first item and based at least in part on an item activity associated with a browse session.
4. The system of claim 1 , wherein:
the computing instructions are further configured to perform:
clustering a search set based at least in part on the one or more keywords, wherein the keyword vector representation is representative of the search set; and
clustering the item set comprising the two or more items, wherein the item vector representation is representative of the item set.
5. The system of claim 1 , wherein the second data comprises historical online behavior of the at least the portion of the plurality of users.
6. The system of claim 5 , wherein the historical online behavior comprises:
respective lengths of time that users of the at least the portion of the plurality of users viewed each item of the item set.
7. The system of claim 1 , wherein the second data comprises one or more user profiles associated with the at least the portion of the plurality of users.
8. The system of claim 1 , wherein the search query comprises an item activity associated with a browse session.
9. The system of claim 8 , wherein:
the computing instructions are further configured to perform:
creating a text corpus comprising the item activity associated with the browse session, the item activity comprising at least one of:
a view of an item of the item set;
a click on the item of the item set;
an add-to-cart of the item of the item set; or
a purchase of the item of the item set.
10. The system of claim 1 , wherein:
receiving the search query from the user comprises receiving the search query during the time window; and
the time window comprises a number of subsequent actions associated with an item activity associated with a browse session.
11. A method being implemented via execution of computing instructions configured to run at one or more processors and stored at one or more non-transitory computer-readable media, the method comprising:
receiving, from an electronic device, a search query from a user of a plurality of users;
processing first data associated with the search query by:
determining one or more keywords by capturing the one or more keywords associated with the search query during a time window;
determining two or more items by:
capturing the two or more items associated with the search query; and
forming an item set comprising the two or more items associated with the search query;
creating a feature set of second data associated with at least a portion of the plurality of users;
determining a set of items of the item set as being associated with the search query based at least in part on an item vector representation and a keyword vector representation;
determining a respective purchase probability associated with each item of the set of items of the item set based at least in part on a respective score for the each item; and
ranking the set of items based at least in part on the respective purchase probability; and
facilitating displaying, on a display screen of the electronic device, of the set of items, as ranked.
12. The method of claim 11 , further comprising:
creating a text corpus comprising:
the search query of the user of the plurality of users; and
an item activity associated with a browse session.
13. The method of claim 11 , further comprising:
determining a user purchase probability that the user will purchase a first item of the two or more items at a particular time based at least in part on a first item score for the first item and based at least in part on an item activity associated with a browse session.
14. The method of claim 11 , further comprising:
clustering a search set based at least in part on the one or more keywords, wherein the keyword vector representation is representative of the search set; and
clustering the item set comprising the two or more items, wherein the item vector representation is representative of the item set.
15. The method of claim 11 , wherein the second data comprises historical online behavior of the at least the portion of the plurality of users.
16. The method of claim 15 , wherein the historical online behavior comprises respective lengths of time that users of the at least the portion of the plurality of users viewed each item of the item set.
17. The method of claim 11 , wherein the second data comprises one or more user profiles associated with the at least the portion of the plurality of users.
18. The method of claim 11 , wherein the search query comprises an item activity associated with a browse session.
19. The method of claim 18 , further comprising:
creating a text corpus comprising the item activity associated with the browse session, the item activity comprising at least one of:
a view of an item of the item set;
a click on the item of the item set;
an add-to-cart of the item of the item set; or
a purchase of the item of the item set.
20. The method of claim 11 , wherein:
receiving the search query from the user comprises receiving the search query during the time window; and
the time window comprises a number of subsequent actions associated with an item activity associated with a browse session.