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

Exploratory Data Analysis (EDA) on Bengaluru restaurant data to uncover insights into ratings, cuisines, cost, location, and dining trends. Built using Python, Pandas, Seaborn, and Matplotlib to understand customer behavior and food business patterns.

A short hand-picked collection of resources to help SaaS founders get started with customer interviews.

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

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.

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

A Data Analysis project performing Exploratory Data Analysis (EDA) on Global Electronics' data to uncover insights that enhance customer satisfaction, optimize operations, and drive business growth.

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

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

Workshop for integrating Dynamics 365 Customer Insights and Azure Data Services

This repository contains a list of open source and comercial platforms that take insights from user and chatbot models conversations

📊 Sales Data Analysis – Coffee Shop | Analyzing sales trends, payment methods, and top-selling drinks using Python (Pandas, Matplotlib, Seaborn).

Scalable multimodal AI system combining FSDP, RLHF, and Inferentia optimization for customer insights generation.

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.

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.

Behavior-based consumer segmentation and predictive modeling using R for AXANTEUS client analysis.

A Node.js-powered tool that scrapes high-quality SaaS product reviews from platforms like G2, Capterra, and Trustpilot (Bonus). Scrapeflow — structures Reviews into clean, standardized JSON—empowering product teams to extract insights, monitor sentiment, and prioritize what matters most.

Unlocking key business insights from food delivery order data using SQL. This project dives deep into customer behavior, order patterns, and city-level performance to support data-driven decision-making in the food delivery industry. 🛠 Tools Used: SQL Server 📂 Dataset: Simulated Food Delivery Orders Data