Retail Sales Performance Analysis Project (SQL)

Project Overview

This project simulates a real world commercial sales analytics engagement where a Data Analyst is tasked with using SQL to analyse retail sales performance and deliver actionable business insights.

The analysis focuses on evaluating revenue, profitability, returns, customer value, promotion effectiveness, and store performance across multiple regions and sales channels over a three year period.

Using SQL Server, the raw transactional data is transformed into meaningful business metrics through structured queries, aggregations, and analytical logic. The goal is to replicate how analysts work in real organisations to support leadership with reliable, data driven insights.

The final deliverable is a comprehensive SQL analytical solution that answers key business questions and provides a foundation for executive reporting and decision making.

Business Objective

The objective of this project is to support commercial and strategic decision making by analysing sales performance and answering critical business questions such as:

• What is the company’s total revenue and profit over time?

• Which regions, stores, and sales channels generate the most revenue and profit?

• Which products and categories are driving or reducing profitability?

• What impact do product returns have on overall business performance?

• How effective are promotions in generating revenue?

• Who are the most valuable customers based on lifetime value and profitability?

• Which areas of the business require improvement or strategic attention?

Stakeholders

This analysis is designed to support key stakeholders including:

• Executives and Senior Leadership

• Commercial and Sales Managers

• Finance and Accounting Teams

• Operations Managers

• Business Intelligence and Data Teams

Key Business Decisions Enabled

The insights generated from this analysis can support decisions such as:

• Identifying high performing and underperforming regions or stores

• Improving product portfolio and pricing strategies

• Evaluating promotion effectiveness and profitability impact

• Managing return related losses

• Optimising sales channel performance

• Identifying and retaining high value customers

• Improving overall business profitability

Dataset Description

The dataset simulates a real world retail transactional database and includes the following tables:

• customers – customer demographic and registration information

• stores – store locations and regional information

• products – product details including category, cost, and status

• sales – order level transactional data

• sales_items – detailed product level sales data

• returns – returned items and refund information

• promotions – promotional campaigns and discount periods

The dataset contains over 150,000 sales transactions spanning multiple years, enabling realistic commercial analysis.

Refer to the exercise files to access the dataset used in this project.

SQL Skills Demonstrated

This project demonstrates practical, job ready SQL skills used by professional Data Analysts, including:

• Multi table joins

• Aggregate functions such as SUM, COUNT, and AVG

• Business KPI calculations including revenue, profit, and margin

• Window functions such as RANK, NTILE, and LAG

• Customer lifetime value analysis

• Return rate and refund impact analysis

• Promotion effectiveness analysis

• Performance ranking and segmentation

• Complex business logic implementation using SQL Server

Analytical Outcome

The project delivers a complete SQL driven analytical solution that enables the business to:

• Measure revenue and profit performance

• Identify key revenue drivers

• Understand customer value and behaviour

• Evaluate operational efficiency

• Support strategic planning and commercial decision making

This project reflects the type of SQL analysis performed by Data Analysts in retail, ecommerce, and enterprise environments.