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Created customer segmentation for an e-commerce website to reach out to millions customers with effective marketing strategy

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Customer-Segmentation

Clustering is one of the most common exploratory data analysis technique used to get an intuition about the structure of the data. It can be defined as the task of identifying subgroups in the data such that data points in the same subgroup (cluster) are very similar while data points in different clusters are very different. Since reaching out to indiviual customer will be challenging hence creting a group of customers having similar behaviour is helpful for implementing marketing strategies.

Problem statement

Create a groups of customers for an e-commerce website and help them to reach out to millions of customer with effective marketing strategy.

Download dataset from here: https://archive.ics.uci.edu/ml/datasets/Online+Retail

Steps:

1] Data Cleaning.

2] Data pre-processing

3] K-means algorithm from scratch

4] Tune the performance of model by finding appropriate value of k by using Elbow and silhouette method

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Created customer segmentation for an e-commerce website to reach out to millions customers with effective marketing strategy

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