Name: Customer Segmentation Classification
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Customer Segmentation Classification

Context

An automobile company has plans to enter new markets with their existing products (P1, P2, P3, P4, and P5). After intensive market research, they’ve deduced that the behavior of the new market is similar to their existing market.

In their existing market, the sales team has classified all customers into 4 segments (A, B, C, D ). Then, they performed segmented outreach and communication for a different segment of customers. This strategy has work e exceptionally well for them. They plan to use the same strategy for the new markets and have identified 2627 new potential customers.

You are required to help the manager to predict the right group of the new customers.

Content

Variable	Definition
ID	Unique ID
Gender	Gender of the customer
Ever_Married	Marital status of the customer
Age	Age of the customer
Graduated	Is the customer a graduate?
Profession	Profession of the customer
Work_Experience	Work Experience in years
Spending_Score	Spending score of the customer
Family_Size	Number of family members for the customer (including the customer)
Var_1	Anonymised Category for the customer
Segmentation	(target) Customer Segment of the customer

Acknowledgements

This dataset was acquired from the Analytics Vidhya hackathon.

Tables

Test

@kaggle.kaushiksuresh147_customer_segmentation.test

33.49 kB
2,627 rows
11 columns

CREATE TABLE test (
  "id" BIGINT,
  "gender" VARCHAR,
  "ever_married" VARCHAR,
  "age" BIGINT,
  "graduated" VARCHAR,
  "profession" VARCHAR,
  "work_experience" DOUBLE,
  "spending_score" VARCHAR,
  "family_size" DOUBLE,
  "var_1" VARCHAR,
  "segmentation" VARCHAR
);

Train

@kaggle.kaushiksuresh147_customer_segmentation.train

86.7 kB
8,068 rows
11 columns

CREATE TABLE train (
  "id" BIGINT,
  "gender" VARCHAR,
  "ever_married" VARCHAR,
  "age" BIGINT,
  "graduated" VARCHAR,
  "profession" VARCHAR,
  "work_experience" DOUBLE,
  "spending_score" VARCHAR,
  "family_size" DOUBLE,
  "var_1" VARCHAR,
  "segmentation" VARCHAR
);