Azi Almasi

Data Scientist

Data Analyst

Azi Almasi

Data Scientist

Data Analyst

Retail Intelligence Dashboard for Data-Driven Decision Making

Project Overview

This dashboard provides a unified view of retail performance, combining customer metrics, sales trends, product insights, regional performance, and purchasing behaviour. The goal is to enable business stakeholders to quickly understand what is happening in the business and why, and to support strategic decisions with real data.

To achieve this, I designed the dashboard to be:

  • Interactive: allowing users to drill down by category, brand, year, and month

  • Business-focused: aligned with how retail teams make day-to-day decisions

  • Visually clean and intuitive: enabling fast interpretation even for non-technical users


Key Features & Insights

1. Executive KPI Summary

At the top of the report, I included high-level KPIs such as:

  • Total Customers

  • Total Customer Lifetime Value (CLV)

These metrics allow leadership teams to assess customer scale and long-term revenue potential at a glance.


2. Advanced Filtering for Multi-Dimensional Analysis

Users can dynamically adjust filters to analyse performance by:

  • Product Category

  • Brand

  • Year

  • Month

This level of interactivity supports deeper questions such as:
Which brand performed best in Q2?
How did Makeup sales trend over the last 12 months?


3. Monthly Revenue Trend Analysis

A time-series line chart highlights revenue fluctuations throughout the year.
This helps identify:

  • Seasonal trends

  • Growth periods

  • Revenue dips requiring operational or marketing intervention


4. Sales Distribution & Customer Behaviour

To better understand what drives revenue, I incorporated:

  • Sales by Brand

  • Sales by Store Type (Online vs In-Store)

  • Sales by Category

  • Sales by Gender

These visuals support key business questions like customer preferences, profitable categories, and channel effectiveness.


5. Geographic Sales Mapping

A treemap visual displays sales performance across major cities.
This helps businesses identify:

  • Top-performing regions

  • Locations requiring attention

  • Opportunities for targeted marketing or stock optimisation


6. Operational Insights

Two visuals provide additional operational intelligence:

  • Quantity by Payment Method – supporting financial planning

  • Quantity by Supplier – useful for supply chain optimisation

These insights allow retail teams to understand both customer choices and supplier reliability.