DSND Term 2 Portfolio Exercise: Optimize promotion offers for Starbucks

This repository contains files for my Codebasics Challenge #9: Analyse Promotions and Provide Tangible Insights to Sales Director

Promotion planning optimization project for pharmaceutical supply chains

Analyzes promotional campaign performance for an FMCG client across products, stores, and cities using sales and events data. Delivers business insights on revenue uplift, sales impact, campaign effectiveness, and promotion performance through clear visualizations.

End-to-end FMCG sales analytics dashboard built with Power BI, analyzing sales performance, promotion impact, margin risk, and inventory exposure across 3 years of data.

End-to-end Excel VBA data model for evaluating price elasticity, promotion lift, and sales performance. Automates data preparation and integration, calendar mapping, KPI computation, and scenario simulations for FMCG analysis.

Atliq Mart 🛒, a prominent retail giant with over 50 supermarkets in the southern region of India, conducted a large-scale promotion during the festive seasons of Diwali 2023 🪔 and Sankranti 2024 🪁 on their Atliq branded products.

AI-powered semantic search and analysis for FMCG promo copy. Find, classify, and re-use high-performing headlines using LLMs, emotion analysis, and KPI filters. Modular Python project with Streamlit dashboard—showcasing practical data science and modern NLP for marketing.

Analysis simulated data of the Starbucks Rewards mobile app and implementation of machine learning models to predict individual offer portfolios for each customer

SQL analysis of Zara sales data to identify revenue drivers, product performance and promotion impact.

Analyzed multi-country chocolate sales data to identify revenue drivers, optimize price-pack strategies, evaluate promotion effectiveness, and uncover growth opportunities across brands, customer segments, and sales channels.

HR Analytics Project using Python to analyze employee salary distribution, hiring trends, promotion patterns and experience-based promotion rates using EDA and data visualization.

HR Analytics Project using Python to analyze employee salary distribution, hiring trends, promotion patterns and experience-based promotion rates using EDA and data visualization.

This project analyzes product performance, cost efficiency, and promotion impact using Power BI. The goal is to identify profitable products and evaluate the effectiveness of promotional strategies.