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This project involves predicting phishing URLs by extracting 17 features across three categories. It entails training and testing machine learning models using a dataset sourced from Phishtank.
FLO, as an online shoe store, aims to segment its customers and define marketing strategies based on these segments. To achieve this, they will analyze customer behavior and create groups according to the segmentation within these behaviors.
This project involves performing customer segmentation and RFM (Recency, Frequency, Monetary) analysis on customer data from a retail company. The primary goal is to categorize customers into segments based on their buying behavior and identify potential target groups for marketing campaigns.
This project aims to perform customer segmentation and revenue prediction for a gaming company based on customer attributes. The company wants to create persona-based customer definitions and segment customers based on these personas to estimate how much potential customers can generate in revenue.
RFM analysis is a marketing technique used to quantitatively rank and group customers based on the recency, frequency and monetary total of their recent transactions to identify the best customers and perform targeted marketing campaigns.