Data Science

Identify customer segments for online retail with the use of K-means clustering

E-commerce industry needs data scientists for pretty much everything growth-related. Build some extraordinary proof of work in Data Science for e-commerce

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Role

Data Scientist

Industry

Technology

Menterns at work

Level

Intermediate

Time Commitment

60 Hours

Duration

45 days

Tools you’ll learn

Here’s What You Work On

About the Company

Snapdeal's mission is to become India’s value lifestyle omni-channel leader. This means they want to be the one-stop shop for all offline and online shoppers who are looking for a budget purchase.
The company is building a complete ecosystem around value commerce, where they can serve 'Bharat' consumers wherever they are on their offline to online shopping journey. Snapdeal services 96% of the country's pin codes and aims to expand its network to reach the remotest areas of India.

Explore

the following work techniques

K-means clustering

Data Science Application in E-Commerce

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Bridging the gap

E-commerce businesses like any other business depend on Customer Relationship Management software to manage customer relationships and drive customer loyalty and retention. Understanding the behavior of their customers and dividing them into segments as per their spending habits, and frequency of platform’s use - helps an e-commerce platform sharpen its customer success policy and increase revenue coming from repeat customers.

Everyone in the e-commerce business understands that in a crowded marketplace, it is cheaper to retain customers than to acquire new ones for whose attention many competitors are already trying. A simple algorithm called K-means clustering can help Data Scientists better understand customer segments and predict their purchasing behavior and needs. In this menternship, you will get to implement this algorithm using Python.

Apply

the following skills

Data Analysis

Data preparation

Hypothesis testing

Model formulation

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Expected output

In this menternship, you will use K-means clustering to identify customer segments in online retail

Create

the following deliverables

Dataset preparation for analysis

A model to group customer segments in online retail using Python

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What you’ll need before starting

Python Libraries
Segmentation Algorithms

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Identify customer segments for online retail with the use of K-means clustering

E-commerce industry needs data scientists for pretty much everything growth-related. Build some extraordinary proof of work in Data Science for e-commerce

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