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US 2018/0322537 A1Published application
System for determination of potential customer status
AssigneeMariana
InventorsJustin Driemeyer, Soumyadeb Mitra, Abishek Kashyap, Arunim Samat, Venkat Nagaswamy, Solomon Fung
Life of this patent
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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
Claims5
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.
6 more elements
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.
11 more elements
Dependencies are inferred from the claim text.