GoldenMetrics

Intelligent Sales Forecasting for Luxury Retail

Project Description:
Is a data-driven sales analysis and forecasting project designed for the luxury retail sector, with a special focus on consumer behavior related to Golden Goose products. The main goal is to build a solution powered by data that anticipates future demand, optimizes stock management decisions, and detects commercial opportunities through the use of artificial intelligence and advanced analytics.

The project simulates a realistic dataset with 4,000 records representing daily sales over one year across multiple physical stores and online channels. The dataset includes information on products, profit margins, promotional campaigns, VIP customers, stock levels, and seasonality.

🧠 Objectives:

- Forecast future sales by product, store, and campaign.

- Analyze the impact of promotions, seasons, and
customer behavior.

- Identify top-selling and low-rotation products.

- Recommend smart restocking actions to avoid
stockouts.

🔍 Key Features:

- Exploratory data analysis of sales by category, store,
channel, and customer type.

- Predictive modeling using regression techniques
(Random Forest, XGBoost).

- Dynamic KPI dashboards built with Streamlit or Power
BI.

- Identification of high-performing campaigns.

- Inventory recommendations based on projected
demand and stock levels.

🧱 Technologies Used:

- Python (pandas, numpy, scikit-learn, matplotlib,
seaborn)

- Streamlit / Power BI for interactive visualizations

- Realistic data simulation

- Machine Learning for sales forecasting

- Advanced EDA and business-focused KPIs

📁 Simulated Dataset:
The dataset includes 17 relevant business variables such as:

- Sale date, store, SKU, product, category

- Price, cost, unit margin, units sold

- Customer type (VIP or retail), sales platform, payment
method

- Campaign, season, initial and final stock levels, restock
suggestion

💼 Impact and Applicability:
This project demonstrates how structured data analysis can support strategic decision-making in the luxury retail sector. The ability to forecast demand and understand customer context and seasonality allows brands like Golden Goose to improve operational efficiency, reduce waste, and maximize profitability.