CAR SALES OVERVIEW
PROJECT BACKGROUND
This prototype was built following a request from a business consultant seeking to support a car sales client with little to no data utilization. The client had access to raw sales data but lacked reporting structure, performance tracking, or clear commercial insight. The goal was to demonstrate what could be achieved with their existing data using Power BI. The project was delivered to a high professional standard as a proof of concept - showing the power of data visualization even when resources are constrained.
PROJECT AIM
The primary goal of this project was to deliver an interactive sales performance overview dashboard for a small car dealership business. The dashboard needed to highlight key commercial metrics - total units sold, sales revenue, and gross profit margin - in a clear, concise format that enabled non-technical stakeholders to quickly assess business health and identify actionable insights.
The solution was designed to demonstrate the untapped value of data to business decision-makers with minimal data infrastructure.
THE DATA
The dataset provided consisted of mock transactional summaries reflecting monthly car sales over the financial year. It included: Total units sold, Sales revenue, Vehicle cost, Selling expenses, VAT-based margins, Retail vs. trade unit distinction
This allowed meaningful analysis of month-on-month performance trends and sales-to-cost ratios. All data was anonymised and fictional, intended purely for demonstration purposes.
METHODOLOGY & RESULTS
The dashboard was developed using Power BI, following an end-to-end process from data preparation to insight delivery. After cleaning and structuring the mock sales data, dynamic calculations were built using DAX to measure total revenue, unit growth, and profit margin trends. The visual design centered around a single-page interactive layout, enhanced with bookmarks to toggle between key metric groups: Units Sold, Total Sales Revenue, and Gross Profit Margin. Clear visual elements such as KPI cards, combo line/bar charts, donut charts, and colour-coded matrix tables were used to drive quick interpretation. Each view was supported by contextual annotations and actionable insight overlays to bridge the gap between data and decision-making. A custom brand palette and personal watermark were applied to distinguish the prototype while preserving professionalism.
Results:
Despite the limited dataset, the dashboard effectively highlighted performance dips, seasonal trends, and cost-to-revenue relationships — demonstrating the commercial value of even basic data when presented with clarity and context.