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01_​Basic_​Customer_​Segmentation_​Use_​Case

Basic Customer Segmentation

This workflow implements a basic customer segmentation through a clustering procedure. No input is required from the business analyst.

Customer Segmentation Data Reading1. Contract Data2. Operational Data Clustering1. k-Means2. Denormalization for data& cluster centers Pre-Processing1. If needed: Conversion To String Discretization (binning) Aggregation2. Normalization 10 clusterson allnumerical inputsNormalizenumerical input datato [0,1]Back to originaldata rangeBack to originaldata rangeCalls DataContract DataJoin calls dataand contract dataArea codeand churn ->Stringk-Means Normalizer (PMML) Denormalizer (PMML) Denormalizer (PMML) Excel Reader CSV Reader Joiner Number To String Customer Segmentation Data Reading1. Contract Data2. Operational Data Clustering1. k-Means2. Denormalization for data& cluster centers Pre-Processing1. If needed: Conversion To String Discretization (binning) Aggregation2. Normalization 10 clusterson allnumerical inputsNormalizenumerical input datato [0,1]Back to originaldata rangeBack to originaldata rangeCalls DataContract DataJoin calls dataand contract dataArea codeand churn ->Stringk-Means Normalizer (PMML) Denormalizer (PMML) Denormalizer (PMML) Excel Reader CSV Reader Joiner Number To String

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: albrecht
Created at: 2016-03-09
On NodePit since: 2024-10-14
Last update: 2024-11-21
Created with KNIME version: v4.5.0
Tags: clusteringk-Meanscustomer segmentationCustomer IntelligenceCIPracticing Data Science

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