Project Title: Car Sales Performance Analysis
Link notion page: (English version) (versi Bahasa Indonesia)
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Description: This case study presents an end-to-end Car Sales Performance Analysis built on the USA Car Sales Dataset (2018–2024). The objective of this project is to transform raw transactional sales data into a structured analytics solution that enables clear, actionable business insights. The project covers the full analytics lifecycle, starting from data cleaning and validation, dimensional data modeling using a star schema in PostgreSQL, and ending with an interactive Power BI dashboard. The dashboard is designed to support strategic decision-making by providing visibility into sales trends, customer behavior, product performance, and salesperson effectiveness.
- Data Cleaning & Validation: Identification and handling of missing values, data inconsistencies, outliers, and recalculation of derived metrics (e.g., profit).
- Dimensional Modeling: Design and implementation of a star schema to support analytical queries and BI reporting.
- Aggregation & KPI Development: Creation of business metrics such as total sales, profit margin, quantity sold, commission, and growth trends.
- Exploratory & Descriptive Analysis: Trend analysis, segmentation analysis, and performance comparison across dimensions.
- Summary Overview – High-level KPIs, sales and profit trends, payment distribution, and seasonal patterns.
- Customers & Market Analysis – Customer demographics, age and gender segmentation, regional performance, and purchasing behavior.
- Salesperson Performance – Sales ranking, commission analysis, performance gaps, and efficiency comparison.
- PostgreSQL: Data storage, cleaning, transformation (ETL), and data warehouse implementation.
- Power BI: Data modeling, DAX measures, interactive dashboards, and visual analytics.
- Total sales and profit show a stable and slightly increasing trend over the observed period, indicating overall business stability.
- Customer purchases are relatively gender-neutral, with balanced contributions from male and female customers.
- The company maintains a healthy average profit margin of approximately 16%.
- The primary revenue-driving customer segment falls within the 35–64 age range.
- Sales are evenly distributed across payment methods, reducing dependency on a single payment channel.
- Older customers tend to purchase higher-priced vehicles, indicating stronger purchasing power.
- Luxury brands such as Mercedes, BMW, and Audi contribute the highest profit.
- There is a significant performance gap between top-performing and bottom-performing salespersons.
- The market shows stable demand with no significant sales decline across years.
- Several salespersons generate negative profit, likely due to excessive discounting practices.
- Focus on High-Margin Brands: Strengthen marketing and inventory strategies for luxury brands that drive higher profitability.
- Target Core Customer Segments: Prioritize marketing campaigns toward customers aged 35–64, who contribute the largest share of revenue.
- Sales Training Programs: Implement targeted coaching and performance improvement plans for low-performing salespersons.
- Discount Control Policy: Introduce approval mechanisms or discount thresholds to prevent profit erosion.
- Commission Optimization: Align commission structures more closely with profitability rather than revenue alone.
- Regional Strategy Enhancement: Allocate resources and sales efforts more aggressively in high-performing regions.
PBIX file: The PBIX file is too large to upload directly to GitHub. Please download it from the following link: https://drive.google.com/drive/folders/1_q9_pMhwO92h1Tqc5UVCqEXZsAy9BuZ2?usp=sharing