Systems and methods for webpage personalization
In some embodiments, a method can comprise receiving a search query from a search by a user during a browse session, receiving one or more items from an item database in response to the search query, and receiving one or more previous search queries from a search database, the one or more previous search queries related to the search query. In many embodiments, the method can further comprise determining a purchase probability associated with a first item of the one or more items based at least in part on a first item score for the first item, ranking the one or more items based at least in part on the purchase probability associated with the first item of the one or more items, and facilitating display of the ranking of the one or more items. Other embodiments of related methods and systems are also provided.
1. A method comprising:
processing data associated with a user of a plurality of users from a browse session by:
determining one or more first keywords by capturing the one or more first keywords associated with a search query of the user of the plurality of users during a time window;
determining two or more items by capturing the two or more items associated with the search query of the user of the plurality of users;
creating a feature set of second data associated with at least a portion of the plurality of users;
creating a text corpus comprising:
the search query of the user of the plurality of users; and
an item activity associated with the browse session;
clustering a search set based at least in part on the one or more first keywords;
clustering an item set comprising the two or more items;
determining an item vector representation representing the item set;
determining a keyword vector representation representing the search set;
determining a first set of items of the item set as being associated with the search query based at least in part on the item vector representation and the keyword vector representation, wherein the first set of items comprises at least two items;
determining a purchase probability associated with a first item of the first set of items of the item set based at least in part on a first item score for the first item;
ranking the first set of items based at least in part on the purchase probability associated with the first item of the first set of items of the item set; and
facilitating display of the ranking of the first set of items.
2. The method of claim 1 , wherein:
the second data associated with the at least the portion of the plurality of users comprises historical online behavior associated with the at least the portion of the plurality of users.
3. The method of claim 2 , wherein:
the historical online behavior comprises at least one of:
a search query;
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.
4. The method of claim 2 , wherein:
the historical online behavior comprises a length of time a user of the at least the portion of the plurality of users viewed an item of the item set.
5. The method of claim 1 , wherein:
the second data associated with the at least the portion of the plurality of users comprises one or more user profiles associated with the at least the portion of the plurality of users.
6. The method of claim 1 , wherein:
the item activity comprises 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.