customer-insights
There are 2 repositories under customer-insights topic.
zuzannna / Loyalty-Program-ETL
💳 ETL (Extract, Transform and Load) pipeline for calculating stats for a transactions database & testing the efficacy of a loyalty program. 💻
Language:Jupyter Notebook 9seby-sbirna / Customer-Insights-and-Business-Intelligence-upon-the-Japanese-restaurant-industry-in-Toronto-Canada
This repository contains the Business Intelligence insights generated as part of the final project challenge for the DTU Data Science course 42578: Advanced Business Analytics
Language:Jupyter Notebook 8sawadogosalif / Trade_area_analysis
In the retail industry a trade area, also known as a catchment area, is the geographic area from where you draw your customers. Here I derive trade area from scratch
Language:Python 5kristiewirth / customer-analysis
Have you ever wondered who your most valuable customers are? This project, created for a software company, sought to identify those who stand out above the rest.
Language:Python 4abhijitpai000 / predictive_lead_scoring
Trained a model that estimates if a lead is likely to be converted based on lead behavior in historical customer data using ML.
Language:Python 3AndrMoura / llm-user-analytics-platforms
This repository contains a list of open source and comercial platforms that take insights from user and chatbot models conversations
ArtisConsulting / customer-insights-azure-data-workshop
Workshop for integrating Dynamics 365 Customer Insights and Azure Data Services
tylerbro93 / COBOL-SALES-BY-WAREHOUSE
This program helps to create sales reports based on warehouse sales data
Language:COBOL 2zhangkelly014 / Online-Superstore-Insight-Analysis-Challenge
Key: descriptive statistics and exploratory data analysis, forecasting (linear regressions, ARMIA, Prophet), and a Tableau dashboard that delivers customer insights such as RFM analysis.
Language:Jupyter Notebook 2mediumroast / mediumroast_js
Mediumroast for GitHub CLI and API/SDK
Language:JavaScript 1onlinepractice / digitalbanking
This repository is all about creating the framework for the digital banking
VIKRAM2563 / CustomerSegmentation-KMeans-MachineLearning
This project demonstrates customer segmentation using K-Means clustering, a popular machine learning technique. By analyzing customer data, we group customers into distinct segments to better understand their behaviors and preferences. This segmentation can help businesses tailor their marketing strategies and improve customer satisfaction.
Language:Jupyter Notebook 1yajasarora / Superstore-Sales-Analysis-with-Tableau
This project provides an interactive analysis of Superstore sales data using Tableau, offering insights into sales performance, customer behavior, and market trends to help optimize business strategies.
EdoStra / Talking-to-Customers
A short hand-picked collection of resources to help SaaS founders get started with customer interviews.
0esana1 / retail-customer-segmentation
Leveraging K-Means clustering, our project categorizes retail customers based on purchasing behaviors and demographics. This provides businesses with actionable insights to tailor marketing efforts, enhancing customer experience and boosting sales.
Language:Jupyter Notebook 0exelero565 / Project_4_ML
Классификация клиентов банка для прогнозирования вероятности открытия депозита.
Language:Jupyter Notebook 0- Language:R 0
hsuwanying / traveller-insights-analysis
The project aims at developing a traveller insight dashboard that can help Swiss Online Travel Agencies(OTAs) to improve conversion cross traveller’s digital decision making process
Language:Jupyter Notebook 0irfanalidv / UFL_London
Customer Intelligent from scratch
0jakeepia / Sales-Performance-X-Customer-Insights
Developed a Power BI Sales Performance and Customer Insights Dashboard to visualize key sales metrics, analyze customer behavior, and identify growth opportunities. The dashboard provided insights into sales trends, product performance, customer retention, and geographic distribution.
0M3GHAN / RFM-Analysis
This notebook focuses on RFM (Recency, Frequency, Monetary) segmentation, a popular method used in customer analysis to group customers based on their purchasing behavior. The key goal of RFM segmentation is to identify different customer segments by analyzing their transaction history and assigning them to categories based on their recency of purc
Language:Jupyter Notebook 0Mediumroast for GitHub API/SDK
Language:Python 0samisaud / retail-customer-segmentation
Leveraging K-Means clustering, our project categorizes retail customers based on purchasing behaviors and demographics. This provides businesses with actionable insights to tailor marketing efforts, enhancing customer experience and boosting sales.
Language:Jupyter Notebook 0Tapas-Gope / Adidas-Sales
This interactive dashboard provides a comprehensive overview of Adidas sales data. It offers valuable insights into sales trends, regional performance, product popularity, and retailer contributions.The dashboard is designed to empower stakeholders with data-driven insights, facilitating informed decision-making and strategic planning for Adidas.
0vyvy-2001 / Sales-Performance-Customer-Analytics
This project offers an interactive dashboard to track sales performance and customer behavior. It helps businesses analyze trends, identify growth opportunities, and make data-driven decisions to optimize strategies, enhance customer satisfaction, and boost profitability.
0hamzaziizzz / UK-Bank-Customer-Insights
This repository is about data visualization of a bank's customer insights. This bank has four branches in Scotland, Northern Ireland, Wales and England. The bank manager wants to analyze how its customers are distributed in the four countries. Now this can be done in various ways, what percentage of males or females are account holders in the bank, how much balance does they hold, what are their job classifications, etc. In this project, I have distributed data in four ways - Age Distribution, Balance Distribution, Job Classification and Gender Distribution.
MohammedAkmal / Customer-Subscription-
Analyzing a subscription-based digital product offering for financial advisory that includes newsletters, webinars, and investment recommendations. The offering has a couple of varieties, annual subscription, and digital subscription.
rrrodzilla / net_promoter_score
A Rust crate for calculating Net Promoter Score (NPS) from survey responses.
Language:Rust
