System and a method for multisession analysis

A method to build a database of related user data collected from a clickstream and exploit the database of related user data, the method comprising:

• receiving clickstream data transmitted over a network between one or more client devices and one or more content servers;
• analyzing the clickstream data to identify a plurality of data content within the clickstream data that is related to a particular user, wherein one or more of the plurality of data content are received from different client devices and/or different content servers;
• creating a data content grouping comprising the plurality of data content for that particular user;
• and
• analyzing the grouping of data content to identify a first anchor subject;
• and
• further analyzing the clickstream data to search for other content items associated with the first anchor subject;
• creating a semantic network comprising the grouping of data content and one or more additional groupings of data content;
• and
• assigning a weight to the first anchor subject based at least on how many times the first anchor subject appears in the grouping of data content and the one or more additional groupings of data content.

A method for tracking a user web journey, the method comprising:

• receiving, by a computerized server, from a plurality of computerized client devices communicatively coupled via a communication network to at least one content server of a plurality of content servers, a plurality of data content transmitted between anyone of the plurality of computerized client devices client devices and the at least one content server, wherein at least some of the computerized client devices are operated by a same user;
• dividing the plurality of data content into data content groupings, wherein at least two data content groupings are associated with the same user and derived from clickstream data collected from at least two respective computerized client devices associated with the same user;
• identifying a plurality of characteristics of each data content grouping;
• selecting a first characteristic as an anchor characteristic for each data content grouping;
• selecting a second characteristic for each data content grouping;
• creating a semantic network for each data content grouping;
• and
• assigning a weight to each of the characteristics for each data content grouping, the weight based at least on how many times the characteristic appears in the data content groupings.