Method and Apparatus for Building a User Profile, for Personalization Using Interaction Data, and for Generating, Identifying, and Capturing User Data Across Interactions Using Unique User Identification

1 . A computer-implemented method for delivering personalized content to a user, the method comprising:

providing a processor for obtaining data sets related to a user including user data, interaction data, transaction data, and aggregate data;

said processor analyzing one or more of the data sets related to said user to identify behavioral characteristics of said user;

said processor parameterizing the data related to the user to generate behavioral scores based on identified behavioral characteristics and aggregate data;

said processor generating a user profile for the user based on the behavioral scores;

said processor generating a personalization engine based on the user profile;

said processor targeting relevant content using the personalization engine; and

said processor delivering personalized content to the user based on the targeting.

2 . A computer-implemented method for building a user profile and for user personalization, comprising:

providing a processor for compiling and analyzing user related data;

said processor continuously generating a user profile to provide personalized services by evaluating a plurality of different sets of said data collected across a plurality of channels, multiple data sources, and unique identifiers comprising each of unique data which corresponds to unique identification parameters of the user, aggregate data, transaction data, and interaction data, said user profile including information that uniquely identifies a user as well as the user's previous interaction experience and personal information which is used to refine results in response to queries submitted by the user;

said processor parameterizing said user related data to generate a behavioral score; and

said processor using said parameterized user related data and said behavioral score to build tools which decide how and when to engage with a particular user.

3 . The method of claim 2 further comprising:

said processor generating a personalization engine based on the user profile;

said processor using a personalization engine for any of:

identifying at least one user and targeting relevant content to be delivered to said user;

extracting and analyzing key concepts and items of information that said user makes known to customize content delivery;

tracking trends in user behavior, user interests, and technology configurations to identify user involvement levels and trends; and

providing any of recommendations, alerts, or notifications to said user.

4 . The method of claim 2 further comprising:

said processor generating a score for user behavior characteristics by at least one of a ranking procedure or a statistical technique.

5 . The method of claim 2 further comprising:

said processor generating a value index or a behavioral score of said user based on an amount of personal information the user has explicitly or implicitly disclosed.

6 . The method of claim 2 , wherein said unique data comprises any of a username, an email ID, a social networking website ID, a vehicle number, or a credit card number.

7 . The method of claim 2 , wherein said aggregate data comprises any of products purchased, service intents, client loyalty metric, devices owned, channel propensity, geography, age group, ethnicity, or lifestyle attributes of said user.

8 . The method of claim 2 , wherein said transaction data comprises any of a location, a browsing pattern, a travelling trigger, income details, marital status, a laptop usage pattern, or social media interests of said user.

9 . The method of claim 2 , wherein said interaction data comprises any of a chat pattern data, data indicative of calls of said user, or any interaction that occurs between said user and a chat agent.

10 . The method of claim 2 , wherein said personalized services comprise any of a product recommendation, a proactive notification, or a personalized offer.

11 . The method of claim 2 further comprising:

modeling user behavior to identify any of said user's preferences, contextual information, and a change in said user's location.

12 . The method of claim 11 further comprising:

determining at least one of a user channel propensity based on past interactions or a price preference for a particular brand based on a particular interaction.

13 . The method of claim 2 further comprising:

said processor evaluating feedback of other similar users to determine how a similar user responds to similar needs.

14 . The method of claim 2 further comprising:

compiling granular data comprising any of user confidential information, interaction data from chats, web logs, voice data, identity data, location logs, travel data, financial data, customer relationship management (CRM) data, demographic data, product usage, or social networking interactions;

compiling user profile data related to behavioral data, identity data, and selected sets of granular data that are parameterized;

performing user modeling by application of an algorithm, extracted feature sets, and responses based on user interactions;

classifying results based on user modeling to obtain scores and action sets; and

creating a personalization application or sets of personalization applications based on said classified results.

15 . The method of claim 14 further comprising:

said processor obtaining said extracted feature sets for user modeling by any of probabilistic latent semantic analysis (PLSA) or term frequency inverse document frequency (Tf-idf) techniques.

16 . The method of claim 1 further comprising:

receiving a request from said user through at least one of a plurality of channels;

obtaining or assigning a unique identifier to the user;

obtaining user data based on the unique identifier from two of the plurality of channels;

storing said user data based on the unique identifier;

said processor using said stored user data in connection with generating said user profile.

17 . A computer device comprising:

a processor; and

a memory storing instructions that, when executed by the processor, causes the computer device to:

compile and analyze user related data;

continuously generate a user profile to provide personalized services by evaluating a plurality of different sets of said user related data collected across a plurality of channels, multiple data sources, and unique identifiers comprising all of unique data which corresponds to unique identification parameters of the user, aggregate data, transaction data, and interaction data, said user profile including information that uniquely identifies a user as well as the user's previous interaction experience and personal information which is used to refine results in response to queries submitted by the user;

parameterize said user related data to generate a behavioral score; and

use said parameterized data and said behavioral score to build tools which decide how and when to engage with a particular user.

18 . The computer device of claim 17 further caused to:

generate a score for user behavior characteristics by at least one of a ranking procedure or a statistical technique.

19 . The computer device of claim 17 further caused to:

generate a value index or behavioral score of said user based on an amount of personal information the user has explicitly or implicitly disclosed.

20 . The computer device of claim 17 , wherein said unique data comprises any of a username, an email ID, a social networking website ID, a vehicle number, or a credit card number.