https://keen.io/ JavaScript SDKs. Track users and visualise the results. Demo http://keen.github.io/keen-dataviz.js/

💳 ETL (Extract, Transform and Load) pipeline for calculating stats for a transactions database & testing the efficacy of a loyalty program. 💻

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

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.

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

Key: descriptive statistics and exploratory data analysis, forecasting (linear regressions, ARMIA, Prophet), and a Tableau dashboard that delivers customer insights such as RFM analysis.

This program helps to create sales reports based on warehouse sales data

Trained a model that estimates if a lead is likely to be converted based on lead behavior in historical customer data using ML.

Workshop for integrating Dynamics 365 Customer Insights and Azure Data Services

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

Классификация клиентов банка для прогнозирования вероятности открытия депозита.

A Rust crate for calculating Net Promoter Score (NPS) from survey responses.

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.

Customer Intelligent from scratch

Mediumroast for GitHub CLI and API/SDK

Mediumroast for GitHub API/SDK

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 ba…

This repository is all about creating the framework for the digital banking

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.