Topic: "customer-segmentation-analysis"
AbhishekGit-hash/Data-Analytics-Customer-Segmentation
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.
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Pegah-Ardehkhani/Customer-Segmentation
Customer Personality Analysis Using Clustering
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pouyaardehkhani/FinancialAnalysis
This notebook provides some skills to perform financial analysis on economical data.
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jjone36/Cohort
Customer Segmentation Anaylsis
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Jen-uis/Customer-Segmentation-Analysis
This repository contains materials for the Spring 2024 STAT 208 class, specifically for Team 8. All materials are the property of Team 8, University of California, Riverside, A. Gary Anderson School of Management. Thank you for viewing our repository.
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Arkantos-13/RFM_Customer_Segmentation_Analysis
RFM (Recency, Frequency, Monetary) analysis is a proven marketing model for behaviour based customer segmentation. It groups customers based on their transaction history in other terms– how recently (R), how often (F) and how much (M) did they buy.
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nano-bot01/Customer-Segmentation-using-Clustering-
Customer Segmentation using Clustering (Machine Learning)
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kshitizrohilla/mall-customer-segmentation-using-k-means-clustering-algorithm
This project aims to perform customer segmentation on a Mall customer dataset using the K-Means clustering algorithm. The goal of this project is to cluster the customers based on their purchasing behavior and demographic characteristics.
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bellamartirosyan/Customer-Segmentation-for-Mall
The goal of the project is to group consumers into clusters using the elbow approach. The project also includes scatter plots to show the relationships between the variables and dataset's columns.
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Ashutosh-Singh15/RFM-analysis
Customer Segmentaton using RFM analysis
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jeffrey125/Mall-Customer-Segmentation
A dataset of Customer Profile going into a Mall Reference: https://www.kaggle.com/vjchoudhary7/customer-segmentation-tutorial-in-python
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rconfa/machine-learning-customer-segmentation
This is a project for the course "Machine Learning" - Master's degree in Data Science, University Milano-Bicocca
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coletangsy/Customer-Analysis-Online-Retails
This project focus on customer analysis and segmentation. Which help to generate specific marketing strategies targeting different groups. RFM Analysis, Cohort Analysis, and K-means Clusters were conducted on a UK-based online retail transaction dataset with 1,067,371 rows of records hosted on the UCI Machine Learning Repository.
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shsarv/Customer-segmentation
Prediction and finding the clusters of potential customers of the mall using k-means Clustering.
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geekquad/Customer-Segments
Analyzing a dataset containing data on various customers' annual spending amounts of diverse product categories for internal structure. Doing so would equip the distributor with insight into how to best structure their delivery service to meet the needs of each customer.
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ferserna95/analysis-of-different-databases-
project: (Customer Personality Analysis for Marketing Optimization); database: (Customer Segmentation: Clustering)
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harmanveer-2546/Supply-Chain
Supply chain analytics is a valuable part of data-driven decision-making in various industries such as manufacturing, retail, healthcare, and logistics. It is the process of collecting, analyzing and interpreting data related to the movement of products and services from suppliers to customers.
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aifenaike/Market-Basket-Analysis-InstaCart-Orders
Can we use association mining and machine learning to understand groceries purchase? Can we predict products that a user will buy again, try for the first time or add to cart next during a session? Can we segment our customer base into several cohorts based on their preferred products and purchase behaviour?
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Senan25/RFM_Analysis_Customer_Segmentation
It is highly related to the Customer Segmentation problem, so with RFM Analysis itself as well
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teyang-lau/Chips_Customer_Segmentation
Conducted customer sales segmentation and affinity analysis on chip sales to identify groups to target for advertisements and promotions.
Language: Python - Size: 4.26 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 2
husskhosravi/AdventureWorks-sales-dashboard
A complete Power BI dashboard
Size: 1.27 MB - Last synced at: 21 days ago - Pushed at: 21 days ago - Stars: 0 - Forks: 0
ShivaNeuralNet/-Airline-Passenger-Satisfaction-Unsupervised-Learning-Project
Unsupervised learning project to cluster airline passengers based on satisfaction using KMeans and PCA. Includes feature engineering, visualization, and cluster evaluation.
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Tolumie/RFM-Marketing-Analysis
This project focuses on RFM (Recency, Frequency, and Monetary) Analysis, a powerful customer segmentation technique used in marketing and business analytics. The analysis helps businesses identify their most valuable customers, potential loyalists, at-risk customers, and churned users.
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farzeenshahid/Exploratory-Data-Analysis-on-Customer-segmentation-Dataset
This project performs Exploratory Data Analysis (EDA) on a customer segmentation dataset to uncover insights into customer demographics, spending behaviors, and transaction patterns. The goal is to guide targeted marketing strategies by identifying key customer segments.
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mahikshith/User-retention-Segementation-Analysis-for-a-product-based-company
Cohort Analysis + Revenue growth Analysis + Customer segmentation for Target Marketing + User retention
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chaitanyasai-2021/Optimizing-Customer-Segmentation-in-Online-Retail
This project analyzes customer behavior in online retail using cohort analysis, **Recency, Frequency, Monetary (RFM)** metrics, and K-means clustering to segment customers. It identifies key groups like Best, At-Risk, and Average Customers, offering strategies to enhance engagement and drive loyalty.
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Rubina-Bansal/KPMG-Marketing-Analysis
Helped their client optimize their marketing strategy by recommending high-value customers.
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vaishali071017/Buy-Now-Pay-Later-Research-case-study
The growth of BNPL services and assess their impact on consumer spending habits and credit risk in the fintech sector
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Honey28Git/Customer-Segmentation-EDA
The Following is a practice on Data Visualization Project using Python. This Dataset is taken from Kaggle.com.
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deepakb41/KPMG-Job-Simulation-Forage
Data Analytics virtual internship programme by KPMG AU on Forage.
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VishalKrish70/Data-Analytics-Customer-Segmentation
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.
Language: Jupyter Notebook - Size: 4.47 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
Hannahnv/Customer-Transaction-Analysis
Analyzing retail sales data to craft targeted marketing, elevate customer experiences, and forecast future sales.
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tieugem1997/CustomerSegmentation_Streamlit
A Streamlit App for Customer Segmentation Project using Kmeans Clustering (Best Choice)
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AImmanuel/Customer-Segmentation-using-PowerBI
Customer segmentation using Python and PowerBI
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TalhaFarook/SegmentWise
SegmentWise: Unveiling Customer Insights for Exploratory Data Analysis (EDA) and Customer Segmentation
Language: Python - Size: 47.9 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0
dikshashub/Customer-Segmentation-analysis
In this project, a RFM model is implemented to relate to customers in each segment. Assessed the Data Quality, performed EDA using Python .
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Zitzewiz/Customer-Segmentation-Challenge
The idea of this challenge was to cluster customers based on a given dataset to align the marketing efforts. Four customer groups were characterized based on income, buying power, credit score, and other criteria
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Sofxley/customer-segmentation
Identification and characterization of the main groups of mall customers in order to gain a deeper understanding of their needs, preferences, and behaviors.
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Sanchariii/Customer_Profiling
This project helps any company or market to target their desired customers or clients by clustering people according to their needs, behaviour and preferences so that they could improve their overall business performance.
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melisnv/churn-ml-capstone-project
Data Scientist Bootcamp capstone project
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tknishh/Customer-Segmentation-Bank-dataset
EDA and comparisons of various on Bank customer data using pycaret
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CasperJaa/Analysing-e-commerce-book-sales
E-commerce site data preparation and sales analysis to answer customer profile and sales questions
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solapade/customersegmentation
The purpose of this project was to perform customer segmentation on mall customers using sklearn Kmeans algorithm. Exploratory data analysis was first performed on the dataset to understand the data. Silhouette analysis was then used to determine the best number of clusters using age, annual income and spending score assigned to customers based on spending habit.
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ManinderpreetPuri/Customer-Segmentation-and-Profiling
Customer segmentation is a pivotal task for business analytics. Customer segmentation is the process of splitting customers into different groups with similar characteristics for potential business value proposition. Many companies find that segmenting their customers enable them to communicate, engage with their customers more effectively. Future Bank is conducting an analysis on the existing customer profiles and the marketing campaign data to identify the target customers who are mostly likely to subscribe long-term deposits. As a member of the data analytics team, I am tasked to analyse historical data and develop predictive models for marketing purposes. I have used SAS Enterprise Miner and Rstudio to perform the analysis.
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gabrielhpr/InstacartClustering
Customer segmentation in Instacart. K-means, RFM Analysis.
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baoh13/ml-capstone
Customer Segmentation Report for Arvato Financial Services. Analyzing demographics data for customers of a mail-order sales company in Germany and identifying most suitable parts of general population whom are most likely to be converted to customers through marketing campaigns.
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karolrives/Arvato-Project
Identifies the parts of the Germany population that best describe the core customer base of the Arvato company. Uses a supervised model to predict which individuals are most likely to convert into becoming customers for the company.
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