Independent Portfolio Analysis
Retail Performance Intelligence Across Sales, Customers & Operations
Retail & Business Intelligence
A cross-functional retail analysis bringing together sales, customer, product, supplier, and delivery data to identify revenue drivers, valuable customer groups, product opportunities, and operational priorities.
The Business Question
Businesses often collect large amounts of information across different departments, but those numbers are not always connected in a way that gives management a clear view of performance. This project asked: “What is driving business performance, where are the strongest opportunities, and where should management focus attention next?” The goal was to move beyond isolated reports and create a broader view of sales, customers, products, suppliers, and delivery performance.
What I Analyzed
Seven related retail datasets covered customer orders, products and categories, pricing, quantities and discounts, suppliers, employees, customer information, and delivery and operational performance. The data was cleaned, connected, and structured into a unified business intelligence model.
Business Performance Overview
Key Findings
Revenue increased substantially across the period analyzed, rising from approximately $226K to $658K. This is an observed pattern in the sample data, not an outcome caused by the analysis. A meaningful share of customers purchased frequently, highlighting potential for loyalty and retention activity. Particular products and categories contributed disproportionately to revenue and showed different seasonal patterns. Approximately 96% of deliveries were completed on time, with a smaller group of delayed orders worth investigating. Some customers stopped purchasing during the observed period, creating a starting point for re-engagement analysis.
Revenue by Market
What This Means for the Business
Customer strategy: prioritize frequent and high-value customers for loyalty, CRM, and retention initiatives. Marketing planning: use seasonal product patterns to inform campaign timing, promotional calendars, and merchandising priorities. Product strategy: focus commercial attention on products contributing most strongly to revenue. Operations: concentrate improvement efforts on the smaller subset of delayed orders. Retention: flag declining or inactive customers for deeper investigation and potential win-back activity.
Delivery Performance
Recommended Actions
Develop differentiated retention strategies for valuable and frequent customers. Investigate seasonal demand when planning campaigns and inventory. Monitor customers showing signs of inactivity. Examine delayed deliveries for recurring causes. Create management reporting that connects commercial and operational KPIs. These are recommended areas for testing and further investigation, not implemented actions or guaranteed outcomes.
Methodology & Tools
Excel · Power BI
Data cleaning, exploratory analysis, data transformation, data modelling, KPI development, visualization, and business intelligence reporting.
Project Context & Transparency
The revenue and delivery figures describe the sample data analyzed. Recommendations identify areas to test and investigate; no implementation or resulting commercial uplift is claimed.
Independent portfolio analysis using sample retail data. This project was not paid client work.
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