Intent prediction based recommendation system using data combined from multiple channels

An apparatus for making recommendations to a user, comprising:

• a processor receiving a query from a user through a plurality of channels;
• during a data fusion stage, said processor using said customer's Web journey, multi-channel journeys, and activities that generate data from multi-channels to match the query received from the user with a previous query from any of said user and one or more other users;
• said processor combining data from said plurality of channels in real time to predict user intent in connection with said identified resources, wherein unique identifiers are created, captured, and/or passed between said plurality of channels to identify and tag the user and the user's context uniquely;
• during an intent prediction stage, said processor configured for predicting in real time an outcome of a future selection by said user from a sequence of previous selections made by any of said user and from one or more frequent sequences of previous selections made by a plurality of users;
• said processor using activities of a group of similar users to provide a basis for determining a current user's intent where insufficient information is available about said user or said user is a new visitor;
• during a recommendation stage, said processor collecting and analyzing information gathered during previous visits of one or more users, including that of a current user, to determine in descending order a most frequent sequence of selections;
• said processor ranking results of said predicting;
• said processor presenting a ranked order of recommended results to said user;
• said processor displaying products or services having the highest scores through any of a plurality of channels, wherein each channel has a different setting for top products or services;
• said processor proactively identifying a user need and initiating user contact and/or interaction through any of chat sessions and telephonic contact with a call center;
• said processor, during user interaction, determining a specific type of user engagement mode based upon the intent of the user;
• and
• said processor providing a recommendation to said user based on any of information gathered through said contact and/or interaction and past user activities.

A computer implemented method for making recommendations to a user, comprising:

• providing a processor configured for receiving a query from a user through a plurality of channels;
• said processor configured for using said customer's Web journey, multi-channel journeys, and activities that generate data from multi-channels to match the query received from the user with a previous query from any of said user and one or more other users;
• said processor configured for combining data from said plurality of channels in real time to predict user intent in connection with said identified resources, wherein unique identifiers are created, captured, and/or passed between said plurality of channels to identify and tag the user and the user's context uniquely;
• said processor configured for predicting in real time an outcome of a future selection by said user from a sequence of previous selections made by any of said user and from one or more frequent sequences of previous selections made by a plurality of users;
• said processor configured for collecting and analyzing information gathered during previous visits of one or more users, including that of a current user, to determine in descending order a most frequent sequence of selections;
• said processor configured for ranking results of said predicting;
• said processor configured for presenting a ranked order of recommended results to said user;
• said processor configured for displaying products or services having the highest scores through any of a plurality of channels;
• and
• said processor configured for providing a recommendation to said user based on any of information gathered through said contact and/or interaction and past user activities.