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E-commerce User Behaviour Data

Kaggle
•

@kaggle.okiasstephanie_e_commerce_user_behaviour_data

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E-Commerce Behavioral Analytics: Demographics to Transactions

Dataset Description

This dataset contains user behaviour data from an e-commerce platform. It is designed for analytics, machine learning, and customer behaviour research, making it ideal for projects involving purchase prediction, customer segmentation, market analysis, and recommendation systems.

The dataset combines demographic information, browsing activity, engagement metrics, and purchase outcomes to provide a realistic representation of online shopping behaviour

Dataset Features

Column Description
user_id Unique identifier for each user
age Age of the user
gender User gender
device_type Device used during browsing (Mobile/Desktop/Tablet)
time_on_site Total time spent on site
pages_viewed Number of pages visited
previous_purchases Number of previous purchases made by the user
cart_item Number of items added to the cart
discount_seen Whether the user saw a discount or promotion
ad_clicked Indicates if the user clicked an advertisement
returning_user Whether the user is a returning customer
avg_session_time Average session duration
bounce_rate Probability of leaving the site quickly
purchase Indicating whether a purchase was completed

Possible Use Cases

  • Purchase prediction models
  • Customer behaviour analysis
  • Marketing campaign analysis
  • User segmentation
  • Recommendation system
  • Exploratory data analysis (EDA)
  • Classification and prediction modeling projects
  • Data visualisation and dashboards

Dataset Characteristics

  • 6019 user interaction records
  • Clean and ready to use dataset
  • No missing values
  • Mixed of categorical and numerical features
  • Suitable for beginners and advanced science projects

Recommended ML Tasks

  • Binary classification
  • Customers segmentation
  • Behavioural Analytics
  • Feature Importance Analysis
  • Predictive modeling

License

This dataset is intended for educational, research, and porfolio projects


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