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, wherein the at least one detail for the at least one product in the group of products includes 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;   receiving, by one or more computer processors, at least one input for at least one customer in a group of customers, wherein the at least one input for the at least one customer in the group of customers includes the following: a gender; an age; a location; a marital status; an education level; an employment status; a place of employment; and a purchase history;   monitoring, by one or more computer processors, one or more social media websites used by the at least one customer;   receiving, by one or more computer processors, at least one social media activity related to the at least one customer from the one or more monitored social media websites, wherein the received at least one social media activity includes a written comment, an image, and a video;   storing, by one or more computer processors, the received at least one social media activity;   determining, by one or more computer processors, comments made by the at least one customer, wherein the comments are about a company or about activities of the customer related to a product or a company;   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;   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;   determining, by one or more computer processors, 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;   matching, by one or more computer processors, 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;   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, wherein the product traits and the customer traits are generated using Natural Language Processing, and wherein the Natural Language Processing performs a linguistic analysis of a written text and infers traits from the written text; and   providing, by one or more computer processors, the at least one recommendation to the at least one customer.