https://github.com/rakibhhridoy/customersegmentation-clustering

Customer segmentation heavily use in business purpose. It is needed skill for business intelligence and applied machine learning engineer. This represent quite basic way the customer segmentation is done. In python the task is quite easy to do.
https://github.com/rakibhhridoy/customersegmentation-clustering

agglomerative-clustering clustering-algorithm customer ecommerce kmeans-clustering machine-learning scikit-learn scikitlearn-machine-learning segmentation unsupervised-learning unsupervised-machine-learning

Last synced: 4 days ago
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Customer segmentation heavily use in business purpose. It is needed skill for business intelligence and applied machine learning engineer. This represent quite basic way the customer segmentation is done. In python the task is quite easy to do.

• Host: GitHub
• URL: https://github.com/rakibhhridoy/customersegmentation-clustering
• Owner: rakibhhridoy
• Created: 2020-08-08T10:30:26.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2020-08-14T09:15:48.000Z (over 4 years ago)
• Last Synced: 2024-12-25T20:25:13.504Z (about 2 months ago)
• Topics: agglomerative-clustering, clustering-algorithm, customer, ecommerce, kmeans-clustering, machine-learning, scikit-learn, scikitlearn-machine-learning, segmentation, unsupervised-learning, unsupervised-machine-learning
• Language: Python
• Homepage: https://rakibhhridoy.github.io
• Size: 76.2 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# *Customer Segmentation Methods*

![customer](https://blog.intercomassets.com/blog/wp-content/uploads/2020/10/Customer-segmentation-performance-matrix.png)

*This step is one of few steps in Data Science Porjects. To get insight of unstructured data, clustering often use in the field. The data consist of a e-commerce site that is serving customers by different products. They want to know if there is any specific behaviour in customers. After analysis we came to 3 types of different behaviour is in all customers. We can detect them, treat them accordingly & give best oppurtunity to buy from site to their tastes.*

Used Algorithms

  - K-means 

  - Agglomerative clustering

### *Result*

*Got 3 types of customers according to their behaviour.*

   

![cluster](Graphs/cluster.png)

![cluster](Graphs/dendogram.png)

### Get touch with me

Connect- [Linkedin](https://linkedin.com/in/rakibhhridoy) 


Website- [RakibHHridoy](https://rakibhhridoy.github.io)