The binary build of LEO CDP Free Edition for training purposes
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Updated
Jul 15, 2024 - HTML
The binary build of LEO CDP Free Edition for training purposes
This a simple Customer Lifetime Value analysis using Buy Till You Die Modelling With PyMC Marketing library
This a simple RFM Analysis Using K Means Clustering On A Publicly Available Brazilian e Commerce Dataset on Kaggle
This repo is a code demo that implements a custom Customer Retention Analysis class with a number of helpful methods/functions to generate customer churn insights frequently used for marketing analytics to understand the growth and change of your customer base (new vs retained vs lost) .
Telco Customer Churn Analysis using Python
Tools for Customer Segmentation using RFM Analysis
Repositori ini berisi proyek data mining yang menganalisis perilaku pelanggan di sektor perbankan, dengan fokus pada prediksi churn. Dilengkapi dengan visualisasi data dan implementasi algoritma Naive Bayes untuk analisis lebih lanjut.
In a fictional situation I helped 2Market, a leading international supermarket chain, leverage data analytics to gain deeper customer understanding to boost sales. By analysing consumer datasets, I uncovered valuable insights into customer behaviour, sales trends, and advertising effectiveness.
This repository contains configuration files for analysing data obtained from Oodles of Noodles
Analyzing US crime statistics using hierarchical clustering to uncover patterns in state-level arrest data and Advanced analytics to delineate market segments in retail, optimizing targeted marketing strategies through customer behavior and demographic profiling.
Advanced analytics in R to delineate market segments in retail, optimizing targeted marketing strategies through customer behavior and demographic profiling
SQL-driven analysis and reporting for strategic insights into Excelsior Mobile's customer usage and billing data to inform business decisions
What are some of the best ways to prepare a large dataset for modeling? In this project, I optimized the memory usage of the dataset to ensure that it is stored as efficiently as possible to allow models to run faster.
Customer Segmentation Project
This is task 2 of 3 from the Power BI PwC Switzerland Virtual Internship organized in partnership with Forage
🛍️A retail company “XYZ Private Limited” wants to understand the customer purchase behaviour (specifically, purchase amount) against various products of different categories. They have shared purchase summary of various customers for selected high volume products from last month.
This repository contains results of the completed tasks for the Quantium Data Analytics Virtual Experience Program by Forage, designed to replicate life in the Retail Analytics and Strategy team at Quantium, using Python.
Customer Segmentation - Using k-means, About: Customer Segmentation is a popular application of unsupervised learning. Using clustering, identify segments of customers to target the potential user base. They divide customers into groups according to common characteristics like gender, age, interests, and spending habits.
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