Systems and Methods for Recommending Third Party Products and Services

Abstract

Systems and methods for recommending third party products and services. The method includes the steps of ranking the third party products and services based on one or more factors, and generating a user profile based on one or more user-related factors. Next, the method determined appropriate third party products and services based on the user's geographical location and filters the third party products and services based on the user profile and the user's geographical location. These filtered results are dynamically ranked based on the user profile, and personalization of the third party products and services. Finally, the method provides the ranked results pertinent to the end user's preferences, and the geographical location.

What is claimed is: 
     
         1 . A computer-implemented method for recommending one or more third party products and services to a user, comprising the steps of:
 receiving information relating to third party products and services, wherein the information for each third party product and service includes one or more factors indicative of product and service specifics;   ranking the third party products and services based on the one or more factors;   generating a user profile based on one or more user-related parameters;   determining appropriate third party products and services for the user from the ranked third party products and services based on a geographical location associated with the user;   filtering the ranked third party products and services based on the user profile, and based on the appropriate third party products and services determined from the geographical location of the user; and   providing the user with one or more optimal third party products and services extracted from the filtered third party products and services.   
     
     
         2 . The computer-implemented method of  claim 1 , wherein the one or more factors are selected from the group comprising: consumer experience information, on-going promotions or sales information, information regarding plan metrics, product or service rating information, product or service popularity, product or service reviews, product or service profitability, product or service type, price, product or service details, or number of sales. 
     
     
         3 . The computer-implemented method of  claim 1 , wherein the step of ranking comprises:
 retrieving the one or more factors related to each third party product and service;   assigning weights to the retrieved factors;   calculating a score for each third party product and service based on the weighted factors; and   ranking the third party products and services based on the scores.   
     
     
         4 . The computer-implemented method of  claim 3 , wherein the step of assigning weights to the retrieved factors comprises using a look-up table to determine predetermined weights corresponding to the factors. 
     
     
         5 . The computer-implemented method of  claim 1 , wherein the step of generating comprises:
 identifying the user;   retrieving user information and preference history information pertinent to the user;   receiving user preferences; and   classifying the user into one or more categories based on the user preferences, user information, and preference history information.   
     
     
         6 . The computer-implemented method of  claim 5 , wherein the step of identifying the user comprises:
 receiving one or more user details selected from user name, email address, telephone number, social security number, date of birth, verification password, account number, account name, or user ID; and   comparing the received user details with user information stored in a database.   
     
     
         7 . The computer-implemented method of  claim 5 , wherein the step of retrieving user information includes retrieving one or more of census demographics, age of the user, user's family size, marital status of the user, census income data pertaining to the user, or the user's credit score. 
     
     
         8 . The computer-implemented method of  claim 5 , wherein the step of classifying the user into one or more categories includes classifying the user as at least one of:
 high profile customer, low profile customer, medium profile customer, high value customer, low value customer, medium value customer, a particular age group, or a particular preference group.   
     
     
         9 . The computer-implemented method of  claim 1 , wherein the step of determining comprises:
 obtaining the geographical location of the user;   retrieving location information pertaining to the geographical location of the user;   analyzing the location information to determine availability of third party products and services to the geographical location of the user; and   determining appropriate third party products and services based on the geographical location of the user, and the location information.   
     
     
         10 . The computer implemented method of  claim 9 , wherein the step of retrieving location information includes fetching at least one of address information, address history, residence plan, residence specifications, residence type, census data, or ownership information. 
     
     
         11 . A system for providing recommendations to a user for a plurality of third party products and services, the system comprising:
 a product engine for ranking the third party products and services based on one or more factors;   a profile engine for generating a user profile based on one or more user-related factors;   a location engine for determining appropriate third party products and services from the ranked third party products and services based on a geographical location associated with the user;   a filtering engine for filtering the ranked third party products and services based on the user profile, and based on the appropriate third party products and services determined from the geographical location of the user; and   an output engine for providing the user with one or more optimal third party products and services extracted from the filtered third party products and services.   
     
     
         12 . The system of  claim 11 , wherein the one or more factors are selected from the group comprising: consumer experience information, on-going promotions or sales information, information regarding plan metrics, product or service rating information, product or service popularity, product or service reviews, product or service profitability, product or service type, price, product or service details, or number of sales. 
     
     
         13 . The system of  claim 11 , wherein the ranking engine includes:
 a fetching module for retrieving the one or more factors related to each third party product and service;   a weighting module for assigning weights to the retrieved factors;   a calculation module for calculating a score for each third party product and service based on the weighted factors; and   a ranking module for ranking the third party products and services based on the scores.   
     
     
         14 . The system of  claim 12 , wherein the weighting module assigns weights to the retrieved factors using a look-up table to determine predetermined weights corresponding to the factors. 
     
     
         15 . The system of  claim 1  wherein the profile engine includes:
 an identification module for identifying the user; 
 an input module for receiving one or more third party product and service preferences from the user; 
 a fetching module for retrieving user information and preference history information pertinent to the user; and 
 a classification module for classifying the user into one or more categories based on the third party product and service preferences, user information, and preference history information. 
 
     
     
         16 . The system of  claim 15 , wherein the identification module is configured to identify the user by:
 receiving one or more user details selected from user name, email address, telephone number, social security number, date of birth, password, account number, account name, or user ID; and   comparing the received user derails with user information stored in a database.   
     
     
         17 . The system of  claim 15 , wherein the fetching module retrieves user including one or more of census demographics, age of the user, user's family size, marital status of the user, census income data pertaining to the user, or user's credit score. 
     
     
         18 . The system of  claim 15 , wherein the classification module classifies the user into one or more categories including high profile customer, low profile customer, medium profile customer, high value customer, low value customer, medium value customer, a particular age group, or a particular preference group. 
     
     
         19 . The system of  claim 11 , wherein the location engine includes:
 an input module for obtaining the geographical location of the user;   a fetching module for retrieving location information pertaining to the geographical location of the user;   an analyzer for analyzing the location information to determine availability of third party products and services to the geographical location of the user; and   a calculator for determining appropriate third party products and services based on the geographical location of the user, and the location information.   
     
     
         20 . The system of  claim 19 , wherein the fetching module retrieves location information including at least one of address information, address history, residence plan, residence specifications, residence type, census data, or ownership information. 
     
     
         21 . In a system for facilitating purchase by users of third party products and services offered by one or more third party product and service providers, wherein the third party products and services correspond to geographical locations associated with the users, a method for identifying optimal third party products and services for a user, comprising the steps of:
 receiving product/service information corresponding to a plurality of product/services offered by the one or more third party product and service providers, wherein the product/service information includes a plurality of parameters, each product/service including one or more parameters;   standardizing the plurality of parameters based on one or more predefined rules;   assigning a predefined weight to each of the plurality of standardized parameters;   calculating a composite score for each product/service offered by the one or more third party product and service providers based on the standardised parameters and predefined weights associated with each product/service; and   generating one or more optimal product/service recommendations for the user based on the composite score for each product/service according to a predefined ranking scheme,   whereby the one or more optimal product/service recommendations are used to suggest one or more products or services to the user that best fit the user's needs.