Customer reference generator

Abstract

A system generates a customer reference recommendation based on similarity to other customers. The system includes a customer data file including demographic data and purchasing pattern data for a plurality of customers, a first cluster model trained on the demographic data, and a second cluster model trained on the purchasing pattern data. A customer reference generator produces a customer reference recommendation based on cluster membership in the first and second cluster models in response to a query from a user interface.

1 . A computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to generate a customer reference recommendation by:
 uploading customer data including past purchasing pattern data and demographic data for a plurality of customers;   requesting a customer reference recommendation; and   receiving at least one customer reference recommendation from a prediction model trained by the purchasing pattern data and the demographic data.   
     
     
         2 . The computer-readable medium of  claim 1 , wherein demographic data includes at least one of: a customer location, industry, headquarter country, public corporation status, importer status, exporter status, number of locations, number of employees, and annual revenue. 
     
     
         3 . The computer-readable medium of  claim 1 , wherein the at least one customer reference recommendation includes a similarity score to another customer. 
     
     
         4 . The computer-readable medium of  claim 1 , wherein the prediction model comprises a first cluster model and a second cluster model. 
     
     
         5 . The computer-readable medium of  claim 4 , wherein the first cluster model is built on the demographic data. 
     
     
         6 . The computer-readable medium of  claim 4 , wherein the second cluster model is built on the past purchasing pattern data. 
     
     
         7 . The computer-readable medium of  claim 4 , wherein the first and second cluster models are used to calculate a similarity score based on cluster membership. 
     
     
         8 . The computer-readable medium of  claim 7 , wherein a first customer and a second customer both sharing membership in a first cluster in the first cluster model and a second cluster in the second cluster model generates a maximum similarity score. 
     
     
         9 . A computer-implemented method for generating a customer reference recommendation, comprising:
 receiving customer data including purchasing pattern data and demographic data for a plurality of customers;   generating a prediction model trained by the purchasing pattern data and the demographic data;   receiving a query for a customer reference recommendation; and   responding to the query with at least one customer reference recommended by the prediction model.   
     
     
         10 . The method of  claim 9 , wherein demographic data includes at least one of: a customer location, industry, headquarter country, public corporation status, importer status, exporter status, number of locations, number of employees, and annual revenue. 
     
     
         11 . The method of  claim 9 , wherein the at least one customer reference includes a similarity score to another customer. 
     
     
         12 . The method of  claim 9 , wherein the prediction model comprises a first cluster model and a second cluster model. 
     
     
         13 . The method of  claim 12  wherein the first cluster model is built on the demographic data. 
     
     
         14 . The method of  claim 12 , wherein the second cluster model is built on the purchasing pattern data. 
     
     
         15 . The method of  claim 12 , wherein the first and second cluster models are used to calculate a similarity score based on cluster membership. 
     
     
         16 . A system for generating a customer reference recommendation, comprising:
 a customer data file including demographic data and purchasing pattern data for a plurality of customers;   a first cluster model trained on the demographic data;   a second cluster model trained on the purchasing pattern data;   a customer reference generator that produces a customer reference recommendation based on cluster membership in the first and second cluster models; and   a user interface for querying the customer reference generator.   
     
     
         17 . The system of  claim 16 , wherein the customer reference recommendation is based on a similarity score generated from cluster memberships in the first cluster model and the second cluster model. 
     
     
         18 . The computer-readable medium of  claim 1 , further comprising generating a buying pattern prediction for a new customer. 
     
     
         19 . The computer-readable medium of  claim 1 , wherein the customer reference recommendation comprises a list of customer references in a ranked order. 
     
     
         20 . The computer-readable medium of  claim 1 , further comprising receiving feedback for at least one of the customer reference recommendation.