System for determination of potential customer status

Abstract

A system is described which accepts corporate and employee data from an interested company and a prospective company, and calculates a probability that the prospective company will form a successful relationship with the interested company and generate campaign data for companies for those prospective companies

What is claimed is: 
     
         1 ) A system for generating a marketing campaign based on relationship data between an interested company and a prospective company, the system comprising:
 a computer,   a UI module, coupled to the computer, configured to accept and request data from one or more external data sources,   a Raw Data Store module, coupled to the computer and the UI module, configured to accept structured or unstructured data in various standard data formats such as Comma Separated Variable and JSON and save the data,   a Customer Data Store module, coupled to the computer, configured to accept data from interested companies including data about prospective companies,   a Transfer API module, coupled to the computer and the UI module, configured to accept data from the UI module and store the information in the Raw Data Store module,   a training module, coupled to the computer, configured to describe a neural network, configured to accept corporate data and relationship data, calculate a set of coefficients for the neural network from the company and relationship data, and store the coefficients into the storage module,   a Semantic indexing module, coupled to the computer, configured to accept company information from the training module, configured to accept requests to compare two prospective companies,   a Prediction module, coupled to the computer, configured to accept prediction parameters from the storage module and generate an output for each prospective company in the storage module, and   a Campaign API module, coupled to the computer, configured to accept output for each prospective company and outputs to marketing tools such as Twitter, Google Ads and Facebook Ads.   
     
     
         2 ) The system in  claim 1 , further comprising a Data Crawl Module, the Data Crawl Module coupled to the computer, the Data Crawl Module configured to accept html data from one or more web sites, to extract information from those web sites and store the information in the Customer Data Store. 
     
     
         3 ) The system in  claim 1 , further comprising a Data API Module, the Data API Module coupled to the computer, the Data API module configured to accept data from one or more sources via an internet API such as the ZoomInfo API. 
     
     
         4 ) The system in  claim 1 , further comprising a Partner Dump Module, the Partner Dump Module coupled to the computer, the Partner Dump module configured to accept data from various partners and store said data in the Raw Data Store. 
     
     
         5 ) A method for generating a marketing campaign between an interested company and a prospective company, the method using:
 a computer,   a UI module, coupled to the computer, configured to accept and request data from one or more external data sources,   a Raw Data Store module, coupled to the computer and the UI module, configured to accept structured or unstructured data in various standard data formats such as Comma Separated Variable and JSON and save the data,   a Customer Data Store module, coupled to the computer, configured to accept data from interested companies including data about prospective companies,   a Transfer API module, coupled to the computer and the UI module, configured to accept data from the UI module and store the information in the Raw Data Store module,   a training module, coupled to the computer, configured to describe a neural network, configured to accept corporate data and relationship data, calculate a set of coefficients for the neural network from the company and relationship data, and store the coefficients into the storage module,   a Semantic indexing module, coupled to the computer, configured to accept company information from the training module, configured to accept requests to compare two prospective companies,   a Prediction module, coupled to the computer, configured to accept prediction parameters from the storage module and generate an output for each prospective company in the storage module, and   a Campaign API module, coupled to the computer, configured to accept output for each prospective company and outputs to marketing tools such as Twitter, Google Ads and Facebook Ads,   the method comprising:   accepting structured and unstructured data from external data sources about interested and prospective companies,   training a neural network based on structured and unstructured data using companies with known relationships with the interested company and generating sets of coefficients,   comparing prospective companies with the interested companies based on the neural network coefficients, and   generating campaign data for those prospective companies.