A Streamlit App for Customer Segmentation Project using Kmeans Clustering (Best Choice)
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Updated
Sep 17, 2023 - Jupyter Notebook
A Streamlit App for Customer Segmentation Project using Kmeans Clustering (Best Choice)
Segmenting customers using RFM model
The goal of segmenting customers is to decide how to relate to customers in each segment in order to maximize the value of each customer to the business. The purpose is to understand customer response to different offers in order to come up with better approaches to sending customers specific promotional deals.
Hotel Customer Segmentation and Behavioral Analysis
analyze the shopping behaviors and demographic profiles of customers visiting a mall using various clustering techniques.
📊🎯✨ Harness the power of the RFM (Recency, Frequency, Monetary) method to cluster customers based on their purchase behavior! Gain valuable insights into distinct customer segments, enabling you to optimize marketing strategies and drive business growth. 📈💡🚀
In this project, a RFM model is implemented to relate to customers in each segment. Assessed the Data Quality, performed EDA using Python and created Dashboard using Tableau.
CLV PULSE - A DYNAMIC CUSTOMER LIFETIME VALUE PREDICTOR MODEL USING MACHINE LEARNING
This repository contains the data, code, and documentation for a project to analyze and predict churn in PowerCo's SME customer segment. The project includes data exploration, cleaning, and transformation, as well as the development and evaluation of a machine learning model to predict churn based on price sensitivity and other relevant factors.
This Program is for Clustering Customer Data On the Basis of their Spending, Income,Family and Children.
Data quality assessment and insights generation
Customer Segmentation Python Project
Deploying clustering machine learning algorithms to segment survey respondents
This is a basic workflow with CrewAI agents working with sales transactions to draw business insights and marketing recommendations. The agents will work on everything from the execution plan to the business insights report. It works with local LLM via Ollama (I'm using llama3:8B but you can easily change it).
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