Systems and methods for predicting user intent

A system comprising:

• at least one processor;
• and
• a non-transitory computer-readable storage medium having instructions stored which, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
• receiving a list of items, where each item in the list of items has a similar purpose and can be substituted with other items in the list of items;
• identifying a plurality of keywords that users of the system associate with items in the list of items;
• identifying a plurality of websites with content that is relevant to the plurality of keywords associated with the items in the list of items;
• identifying, using network traffic data, at least one user that accessed at least one of the plurality of websites, resulting in a set of at least one interested users;
• generating, for each user in the set of at least one interested users, a user intent score, the user intent score indicating a user interest level of the each user in the items in the list of items;
• and
• modifying a previously planned interaction with the each user based on the user intent score.

A non-transitory computer-readable storage medium having instructions stored which, when executed by at least one processor, cause the at least one processor to perform operations comprising:

• receiving a list of items, where each item in the list of items has a similar purpose and can be substituted with other items in the list of items;
• identifying a plurality of keywords that users associate with items in the list of items;
• identifying a plurality of websites with content that is relevant to the plurality of keywords associated with the items in the list of items;
• identifying, using network traffic data, at least one user that accessed at least one of the plurality of websites, resulting in a set of at least one interested users;
• generating, for each user in the set of at least one interested users, a user intent score, the user intent score indicating a user interest level of the each user in the items in the list of items;
• and
• modifying a previously planned interaction with the each user based on the user intent score.

A method comprising:

• receiving, at a computer system, a list of items, where each item in the list of items has a similar purpose and can be substituted with other items in the list of items;
• identifying, via at least one processor of the computer system, a set of item content elements associated with items in the list of items;
• generating, via the at least one processor, a content embedding based on at least one element of content within the set of item content elements, the content embedding encoding a relevancy of the at least one element of content to the list of items;
• identifying, via the at least one processor, a plurality of websites with website content that is relevant to the list of items, the relevancy of the website content determined by comparing item content embeddings with content embeddings for the website content;
• identifying, via the at least one processor using network traffic data, at least one user that accessed at least one of the plurality of websites, resulting in a set of at least one interested users;
• generating, via the at least one processor for each user in the set of at least one interested users, a user intent score, the user intent score based on the relevancy of the website content, the user intent score indicating a user interest level of the each user in the items in the list of items;
• and
• modifying, via the at least one processor, a previously planned interaction with the each user based on the user intent score.

A system comprising:

• at least one processor;
• and
• a non-transitory computer-readable storage medium having instructions stored which, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
• receiving a list of items, where each item in the list of items has a similar purpose and can be substituted with other items in the list of items;
• identifying a set of item content elements associated with items in the list of items;
• generating a content embedding based on at least one element of content within the set of item content elements, the content embedding encoding a relevancy of the at least one element of content to the list of items;
• identifying a plurality of websites with website content that is relevant to the list of items, the relevancy of the website content determined by comparing item content embeddings with content embeddings for the website content;
• identifying, using network traffic data, at least one user that accessed at least one of the plurality of websites, resulting in a set of at least one interested users;
• generating, for each user in the set of at least one interested users, a user intent score, the user intent score based on the relevancy of the website content, the user intent score indicating a user interest level of the each user in the items in the list of items;
• and
• modifying a previously planned interaction with the each user based on the user intent score.

A non-transitory computer-readable storage medium having instructions stored which, when executed by at least one processor, cause the at least one processor to perform operations comprising:

• receiving a list of items, where each item in the list of items has a similar purpose and can be substituted with other items in the list of items;
• identifying a set of item content elements associated with items in the list of items;
• generating a content embedding based on at least one element of content within the set of item content elements, the content embedding encoding a relevancy of the at least one element of content to the list of items;
• identifying a plurality of websites with website content that is relevant to the list of items, the relevancy of the website content determined by comparing item content embeddings with content embeddings for the website content;
• identifying, using network traffic data, at least one user that accessed at least one of the plurality of websites, resulting in a set of at least one interested users;
• generating, for each user in the set of at least one interested users, a user intent score, the user intent score based on the relevancy of the website content, the user intent score indicating a user interest level of the each user in the items in the list of items;
• and
• modifying a previously planned interaction with the each user based on the user intent score.