Client: A leading retail company
Developed a sales and marketing dashboard with real-time sales tracking, customer insights, and profit forecasting.
Technologies Used: Power BI, SQL Server, Power BI Service
The Retail Sales Dashboard provides a comprehensive view of sales performance, helping businesses analyze revenue, order patterns, and customer preferences. It includes key performance indicators (KPIs), visualizations, and data tables to offer insights into sales trends and customer behavior.
1. Key Objectives
- Track total revenue and sales performance.
- Understand order distribution across different time periods.
- Identify the most and least popular items varieties.
- Analyze customer preferences based on size, category, and order patterns.
- Provide actionable insights for business growth.
2. Dashboard Components
2.1 Key Performance Indicators (KPIs)
These KPIs provide a quick snapshot of the overall business performance:
- Total Revenue – The total sales revenue generated from product orders.
- Total No. of Products Sold – The total quantity of products sold.
- Total No. of Orders – The total number of customer orders placed.
- Total No. of Categories – The number of different product categories available (e.g., Audio, Computer, Wearable, Electronics).
- Total No. of Product Types – The number of unique product types offered on the menu.
- Total No. of Variety of Products – The count of different varieties (unique product names).
2.2 Order Distribution by Time of Day (Bar Chart)
This bar chart divides orders into four key time slots:
- Morning (10 AM – 12 PM)
- Afternoon (12 PM – 5 PM)
- Evening (5 PM – 9 PM)
- Night (9 PM – 1 AM)
📌 Insight: Helps understand when sales are highest and lowest, guiding business decisions such as promotional offers or staffing.
2.3 Orders by Hour (Column Chart)
A column chart shows the total number of orders placed each hour from 10:00 AM to 1:00 AM.
📌 Insight: Helps identify peak order hours, allowing for better inventory and staff management.
2.4 Weekly Sales Heatmap (Matrix Visualization)
The matrix chart displays orders based on day of the week (rows) and time of the day (columns from 10 AM to 1 AM).
📌 Insight:
- Identifies the busiest days and peak time slots.
- Helps optimize pricing strategies (e.g., discounts on slow days).
2.5 Top 3 Items Sold | Revenue Basis (Table Visualization)
This table lists the top 3 best-selling products, ranked by the number of units sold.
📌 Insight:
- Identifies customer favorites, which can be further promoted.
- Helps decide which products to keep or expand in the menu.
2.6 Bottom 3 Products Sold (Table Visualization)
This table lists the 3 least-selling products, ranked by the number of units sold.
📌 Insight:
- Helps identify under-performing products.
- Assists in making decisions about menu optimization or promotions to boost sales.
2.7 Sales by Product Category (Bar Chart)
A pie chart shows sales distribution across four main item categories:
- Audio
- Computers
- Wearable
- Electronics
📌 Insight:
- Identifies the most popular product category.
- Helps in planning marketing and inventory for different customer segments.
2.8 Sales by Sales Channel (Pie Chart)
A bar chart breaks down sales by different Sales Channels:
In-Store
Online
📌 Insight:
- Identifies which size is most popular among customers.
Helps in pricing strategy (e.g., offering combos on certain sizes).
3. Business Insights & Decision Making
🔹 Peak Selling Times – The dashboard helps pinpoint the busiest time slots for orders.
🔹 Best-Selling & Least-Selling Products – Helps decide which products to promote and which to reconsider.
🔹 Customer Preferences by Size & Category – Allows better planning of inventory and marketing.
🔹 Sales Trends Over Time – Assists in forecasting future sales and adjusting business strategies accordingly.
4. Conclusion
This Power BI Pizza Sales Dashboard provides a data-driven approach to sales analysis, helping restaurant owners make informed decisions about menu optimization, pricing, promotions, and operational efficiency. By leveraging the insights from this dashboard, businesses can improve customer satisfaction and maximize revenue.
