Found 11 repositories(showing 11)
Customer analytics and in particular A/B Testing are crucial parts of leveraging quantitative know-how to help make business decisions that generate value.
Hamdaan-P
A comprehensive portfolio of real-world statistical analysis projects, demonstrating expertise in Python, hypothesis testing, and data visualization. Projects include credit risk modeling, business A/B testing, customer survey analytics, and advanced sales performance analysis.
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TAHSIN78425
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Abhinay-MA
Marketing & Data Analytics professional skilled in SQL, Python, Tableau, Adobe Analytics, and A/B testing. I analyze digital performance, build dashboards, and translate customer journey data into actionable insights to drive smarter marketing decisions.
KatlinRaev
Showcasing projects in data analytics, including Power BI dashboards, retention and churn analyses, funnel analyses, customer segmentation (RFM), CLV, A/B testing, and Python-based data analysis and visualization.
Austink-mari
End-to-end retail analytics pipeline: exploratory analysis in Python, business queries in SQL, A/B testing and time-series forecasting in R, and an interactive Tableau dashboard. Analyzes 15,000+ multi-channel transactions across product categories, customer segments, and promotional strategies.
DmitryPankov33
Data Analytics Portfolio showcasing various projects in data analysis, visualization, and business intelligence. This repository contains work involving advanced Excel, SQL, Python, A/B testing, and customer segmentation, demonstrating my ability to solve real-world business problems using data.
shubh-ag-git
Data-driven analytics project for ABC Bank's new credit card launch. Conducts customer segmentation, rigorous A/B testing (p=0.003), and revenue impact quantification projecting ₹1.9 crore annual opportunity. Includes data cleaning, visualization, and statistical validation using Python. Explore in phase1_self.ipynb
Mlesh21
In this mini-project, I performed a full analytics cycle independently to demonstrate my data analysis skills. The project includes data cleaning, exploratory data analysis, RFM customer segmentation, A/B testing, and data visualization using Python and Power BI. The goal was to show my abilities to handle real-world datasets.
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