Customer Segmentation Analysis & Predict Consumer Behaviour
Learn how to conduct customer segmentation analysis and predict consumer behaviour using machine learning
4.21 (7 reviews)
1,726
students
3.5 hours
content
Jan 2025
last update
$44.99
regular price
What you will learn
Learn how to conduct customer segmentation analysis using k means clustering
Learn how to build customer spending prediction model using decision tree regressor
Learn how to build customer churn prediction model using support vector machine
Learn the basic fundamentals of customer segmentation analytics, technical challenges and limitations in customer analytics, and its use cases in marketing
Learn about predictive customer analytics workflow. This section covers data collection, feature selection, model selection, model training, and prediction
Learn how to segment customer by age and gender
Learn how to segment customer by education level
Learn how to calculate average customer spending by country
Learn how to find correlation between purchase frequency and customer spending
Learn how to find correlation between customer income and customer spending
Learn how to conduct feature importance analysis using random forest
Learn how to evaluate model accuracy and performance using k fold cross validation method
Learn how to deploy machine learning model and create user interface using Gradio
Learn how to handle class imbalance with synthetic minority oversampling technique
Learn about factors that influence consumer behaviour, such as psychological, economic, social, technology, personal, and culture
Learn how to clean dataset by removing missing values and duplicates
Learn how to find and download customer spending data from Kaggle
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udemy ID
1/31/2025
course created date
2/4/2025
course indexed date
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