Analysis for Customer Segmentation

By means of this project I am trying to create a value-based customer segmentation model using RFM(Recency, Frequency, Monetary) analysis in python using pandas, numpy and matplotlib

A Streamlit App for Customer Segmentation Project using Kmeans Clustering (Best Choice)

Develop a customer segmentation to define marketing strategy. Used PCA to reduce dimensions of the dataset and KMeans++ clustering technique is used for clustering and profiling of clusters.

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This project demonstrates how to perform customer segmentation for a shopping mall using machine learning algorithms. This is an unsupervised clustering problem.

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CLV PULSE - A DYNAMIC CUSTOMER LIFETIME VALUE PREDICTOR MODEL USING MACHINE LEARNING

Customer Segmentation and Targeting for Retail Industry

It is a machine learning project in which the model tries to identify the features and segments the customers based on their buying patterns

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FLO, an online shoe store, wants to segment itscustomers and determine marketing strategies according to these segments. For this purpose, customers' behaviors will be defined and groups will be formed according to the clusters in these behaviors.

Presentation of Customer Segmentation Basics done during the Kschool Meetup on April 2018

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Customer Segementation is used in marketing to better understand customers of a business and target them accordingly. Segmentation of customer can take many forms, based on demographic, geographic, interest, behavior or a combination of these characteristics. Segmentation for this analysis was conducted based on their purchase behavior, the features to be analyzed were Recency, Frequency and Monetary Value, (RFM) for short.

In this Python notebook, we explore how K-Means can be used for customer segmentation to gain a competitive advantage and improve a business's bottom line.

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University project about using SAS Enterprise Miner to segment a customer database

This project implements customer segmentation using machine learning techniques, including K-Means clustering, to group customers based on their purchasing behavior and demographic characteristics. The analysis helps businesses understand different customer segments for targeted marketing strategies.

This is our incredible CustomerSegmentation Project for Data Mining

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Predictive model that divides the customers into groups based on common characteristics so companies can market to each group effectively and appropriately

Customer Personality Segmentation analysis with LLM

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Categorical clustering techniques, KModes and KPrototype, to predict customer segmentation.

Build Customer Segments and predict customer responses to marketing campaign for Arvato Financial Services

Cohort Analysis of customer data for Saas company