Matching customer and product behavioral traits

Abstract

At least one detail for at least one product in a group of products is received. At least one input for at least one customer in a group of customers is received. At least one detail for at least one product and at least one input for at least one customer is stored to a database repository. Product traits for at least one product are generated and stored to a database repository. Customer traits for at least one customer are generated and stored to a database repository. The generation of customer traits is independent from the generation of product traits. At least one recommendation for matching at least one product to at least one customer is generated. The at least one recommendation is based on the generated traits of the at least one product and the generated traits of the at least one customer.

What is claimed is: 
     
         1 . A method for matching customers to products, the method comprising:
 receiving, by one or more computer processors, at least one detail for at least one product in a group of products;   receiving, by one or more computer processors, at least one input for at least one customer in a group of customers;   storing, by one or more computer processors, the at least one detail for the at least one product and the at least one input for the at least one customer to a database repository;   generating, by one or more computer processors, product traits relating to the at least one product in the group of products;   generating, by one or more computer processors, customer traits relating to the at least one customer in the group of customers, wherein generating the customer traits occurs independently from generating the product traits; and   determining, by one or more computer processors, at least one recommendation for matching the at least one product to the at least one customer based on the generated traits of the at least one product and the generated traits of the at least one customer.   
     
     
         2 . The method of  claim 1 , wherein the at least one detail for the at least one product in a group of products includes at least one of the following: a name; a description; an attribute; a hierarchy of the product in a catalog of products; and a description of a product category. 
     
     
         3 . The method of  claim 1 , wherein the at least one input for the at least one customer in the group of customers includes at least one of the following: a gender; an age; a location; a marital status; an education level; an employment status; a place of employment; a purchase history; and a listing of social media activity. 
     
     
         4 . The method of  claim 1 , wherein the product traits and the customer traits are generated using Natural Language Processing, wherein the Natural Language Processing performs a linguistic analysis of a written text and infers traits from the written text. 
     
     
         5 . The method of  claim 1 , further comprising:
 mapping, by one or more computer processors, at least one product to at least one customer, wherein the mapping comprises an automated process based on the generated product traits and the generated customer traits.   
     
     
         6 . The method of  claim 1 , wherein the step of determining, by one or more computer processors, a recommendation for matching the at least one product to the at least one customer, comprises:
 determining a weighted average for each product trait and a weighted average for each customer trait, wherein the weighted average comprises at least one product trait or at least one customer trait weighted by a number of occurrences of the at least one product trait or the at least one customer trait normalized as a percentage of all of the product traits or all of the customer traits; and   matching a list of highest weighted product traits to a list of highest weighted customer traits based on a best-fit basis of the weighted averages, wherein the weighted average has met a threshold to be considered for matching.   
     
     
         7 . The method of  claim 3 , wherein the listing of social media activity includes at least one of the following: posting a written text to a social media website and posting an image or video to a social media website, wherein Natural Language Processing generates customer traits from the written text, and wherein the Natural Language Processing uses a result from an object recognition of the image or video to generate customer traits. 
     
     
         8 . A computer program product for matching customers to products, the computer program product comprising:
 one or more computer readable storage media; and   program instructions stored on the one or more computer readable storage media, the program instructions comprising:
 program instructions to receive at least one detail for at least one product in a group of products; 
 program instructions to receive at least one input for at least one customer in a group of customers; 
 program instructions to store the at least one detail for the at least one product and the at least one input for the at least one customer to a database repository; 
 program instructions to generate product traits relating to the at least one product in the group of products; 
 program instructions to generate customer traits relating to the at least one customer in the group of customers, wherein generating the customer traits occurs independently from generating the product traits; and 
 program instructions to determine at least one recommendation for matching the at least one product to the at least one customer based on the generated traits of the at least one product and the generated traits of the at least one customer. 
   
     
     
         9 . The computer program product of  claim 8 , wherein the at least one detail for the at least one product in a group of products includes at least one of the following: a name; a description; an attribute; a hierarchy of the product in a catalog of products; and a description of a product category. 
     
     
         10 . The computer program product of  claim 8 , wherein the at least one input for the at least one customer in the group of customers includes at least one of the following: a gender; an age; a location; a marital status; an education level; an employment status; a place of employment; a purchase history; and a listing of social media activity. 
     
     
         11 . The computer program product of  claim 8 , wherein the product traits and the customer traits are generated using Natural Language Processing, wherein the Natural Language Processing performs a linguistic analysis of a written text and infers traits from the written text. 
     
     
         12 . The computer program product of  claim 8 , further comprising program instructions stored on the one or more computer readable storage media, to:
 map at least one product to at least one customer, wherein the mapping comprises an automated process based on the generated product traits and the generated customer traits.   
     
     
         13 . The computer program product of  claim 8 , wherein the program instructions to determine a recommendation for matching the at least one product to the at least one customer, comprise:
 program instructions to determine a weighted average for each product trait and a weighted average for each customer trait, wherein the weighted average comprises at least one product trait or at least one customer trait weighted by a number of occurrences of the at least one product trait or the at least one customer trait normalized as a percentage of all of the product traits or all of the customer traits; and   program instruction to match a list of highest weighted product traits to a list of highest weighted customer traits based on a best-fit basis of the weighted averages, wherein the weighted average has met a threshold to be considered for matching.   
     
     
         14 . The computer program product of  claim 10 , wherein the listing of social media activity includes at least one of the following: posting a written text to a social media website and posting an image or video to a social media website, wherein Natural Language Processing generates customer traits from the written text, and wherein the Natural Language Processing uses a result from an object recognition of the image or video to generate customer traits. 
     
     
         15 . A computer system for matching customers to products, the computer system comprising:
 one or more computer processors;   one or more computer readable storage media; and   program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more computer processors, the program instructions comprising:
 program instructions to receive at least one detail for at least one product in a group of products; 
 program instructions to receive at least one input for at least one customer in a group of customers; 
 program instructions to store the at least one detail for the at least one product and the at least one input for the at least one customer to a database repository; 
 program instructions to generate product traits relating to the at least one product in the group of products; 
 program instructions to generate customer traits relating to the at least one customer in the group of customers, wherein generating the customer traits occurs independently from generating the product traits; and 
 program instructions to determine at least one recommendation for matching the at least one product to the at least one customer based on the generated traits of the at least one product and the generated traits of the at least one customer. 
   
     
     
         16 . The computer system of  claim 15 , wherein the at least one detail for the at least one product in a group of products includes at least one of the following: a name; a description; an attribute; a hierarchy of the product in a catalog of products; and a description of a product category. 
     
     
         17 . The computer system of  claim 15 , wherein the at least one input for the at least one customer in the group of customers includes at least one of the following: a gender; an age; a location; a marital status; an education level; an employment status; a place of employment; a purchase history; and a listing of social media activity. 
     
     
         18 . The computer system of  claim 15 , wherein the product traits and the customer traits are generated using Natural Language Processing, wherein the Natural Language Processing performs a linguistic analysis of a written text and infers traits from the written text. 
     
     
         19 . The computer system of  claim 15 , further comprising program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more computer processors, to:
 map at least one product to at least one customer, wherein the mapping comprises an automated process based on the generated product traits and the generated customer traits.   
     
     
         20 . The computer system of  claim 15 , wherein the program instructions to determine a recommendation for matching the at least one product to the at least one customer, comprise:
 program instructions to determine a weighted average for each product trait and a weighted average for each customer trait, wherein the weighted average comprises at least one product trait or at least one customer trait weighted by a number of occurrences of the at least one product trait or the at least one customer trait normalized as a percentage of all of the product traits or all of the customer traits; and   program instruction to match a list of highest weighted product traits to a list of highest weighted customer traits based on a best-fit basis of the weighted averages, wherein the weighted average has met a threshold to be considered for matching.