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The idea of this challenge was to cluster customers based on a given dataset to align the marketing efforts. Four customer groups were characterized based on income, buying power, credit score, and other criteria

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Zitzewiz/Customer-Segmentation-Challenge

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Project Name

example image:

alternative text

-- Project Status: [Active, On-Hold, Completed]

Project Intro/Objective

The purpose of this project is ________. (Describe the main goals of the project. Limit to a short paragraph, 3-6 Sentences)

Partner

  • [Name of Partner organization/Government department etc..]
  • Website for partner
  • Partner contact: [Name of Contact]
  • If you do not have a partner leave this section out

Methods Used

  • Inferential Statistics
  • Machine Learning
  • Data Visualization
  • Predictive Modeling
  • etc.

Technologies

  • R
  • Python
  • D3
  • PostGres, MySql
  • Pandas, jupyter
  • HTML
  • JavaScript
  • etc.

Project Description

(Provide more detailed overview of the project. Talk a bit about your data sources and what questions and hypothesis you are exploring. What specific data analysis/visualization and modelling work are you using to solve the problem? What blockers and challenges are you facing? Feel free to number or bullet point things here)

Getting Started

  1. Clone this repo (for help see this tutorial).

  2. Raw Data is being kept [here](Repo folder containing raw data) within this repo.

    If using offline data mention that and how they may obtain the data from the froup)

  3. Data processing/transformation scripts are being kept [here](Repo folder containing data processing scripts/notebooks)

  4. etc...

If your project is well underway and setup is fairly complicated (ie. requires installation of many packages) create another "setup.md" file and link to it here

  1. Follow setup [instructions](Link to file)

Featured Notebooks/Analysis/Deliverables

Contributing Members

Team Leads (Contacts) : [Full Name](https://github.com/[github handle])

Other Members:

About

The idea of this challenge was to cluster customers based on a given dataset to align the marketing efforts. Four customer groups were characterized based on income, buying power, credit score, and other criteria

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