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Apply logistic-regression churn models and k-means airline-customer segmentation to retention and targeted marketing within a broader R/Excel analytics course
Exam Turf · Udemy
Apply logistic-regression churn models and k-means airline-customer segmentation to retention and targeted marketing within a broader R/Excel analytics course
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Related tasks, tools and formats. Check the differences before choosing.
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Preprocess customer data and use Excel/XLSTAT regression, clustering and automated logistic models for behavior, churn/retention and sales forecasts
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Analyze campaign and retention metrics, use unsupervised customer segmentation, build CatBoost churn and MLP lifetime-value models, and run A/B tests within a broader Excel/Python/Power BI course
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Use KNIME churn-training workflows and a clothing-customer dataset for k-means segmentation, cluster optimization and marketing personas within a broader platform course