This comprehensive retail dashboard created with Power BI encompasses all-important analytics and metrics that are of great value to the retail business and offers enhanced visibility. Categorized in different segments like sales, profit, order, and shipping, the live dashboard depicts drill down details offering better forecasting and timesaving efficacy.

The enriched retail dashboard overview offers a detailed, real-time view into the summary of major parameters like gross sales and profit, total countries served, the best month for receiving orders, and items sold in a particular year. The retail analytics dashboards offer an effective data visualization experience, with all required information in a single go, based on category, sub-category, and product.

The dashboard offers robust Power BI row-level security features that control the access to rows and implements restrictions, based on user privileges and authentication. Specific security roles and role-based filters can be defined within the dashboard, to ensure effective row-level security.

Focus Metrics:
  • Sales: Region-wise/category wise sales, top countries where the sale is highest, top-performing products, and month-wise sales trend
  • Profits: Monthly profits, profitable/unprofitable regions, category/sub-category wise profits, most profitable customers
  • Orders: Details of orders received category and sub-category wise, location and segment-wise, customers who ordered most, the effect of orders received on profits
  • Shipping: Shipping details like the cost for shipping, customer preference, and locations where products were shipped, the average cost of shipping as against total shipment
Suitable For:

This retail dashboard would help the CEO, CIO, COO, directors, sales leaders, and management of the retail segment, in intuitive strategic planning and decision making for further business prospects.

Industry: Retail

Disclaimer: The data, characters and brand names depicted in the visualizations are for demo purposes only. Any resemblance to actual data, or to brand names, is purely coincidental.