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Online Retail Purchase Patterns Dashboard

A Power BI dashboard that reveals retail KPIs, top products, seasonality, and country performance.

Tools: Power BI • DAX • Power Query • Excel Role: Solo builder Users: Peers exploring e‑commerce patterns

Problem

Retail teams needed a concise view of what drives revenue by product, month, and market. Raw tables made it hard to compare patterns across time and countries.

Solution

I built a Power BI model with DAX for % of total, ranks, and AOV. The report highlights KPIs, top products, monthly sales trends, and a countries view for quick geographic comparisons.

Impact

The dashboard surfaced peak months (Nov/Dec), product concentration, and country contribution mix. Stakeholders could prioritize catalog and markets based on clear trends.

Role & Context

Solo project done in ~1 week using Excel + Power Query + DAX. Built for practice with retail data and reviewed with peers for clarity.

DATA MODELING

  • Model Type: Flat, single-table model for performance and simplicity
  • Relationships: Single fact table (Year 2010–2011)
  • Calculated Columns: YearOnly (extracted from InvoiceDate)
  • Hierarchies: Year > Quarter > Month > Day for time-based filtering

DAX CALCULATIONS

The dashboard includes several advanced DAX calculations for comprehensive analysis:

  • % of Total Sales: Calculates each product's share of total revenue
  • Product Sales Rank: Ranks products by revenue
  • Average Order Value: Average revenue per order
  • Avg Quantity per Order: Average items per order
  • YearOnly: Extracted year for filtering capabilities

DASHBOARD DESIGN

The dashboard follows best practices for visualization and user experience:

  • KPI Summary Row: Total Sales, Customers, Invoices at the top
  • Main Charts: Bar charts for top products, area charts for monthly sales, map visuals for geographic sales, line charts for customer trends
  • Slicer Panel: Year and month filters for dynamic filtering
  • Interactivity: Tooltips, cross-filtering, dynamic slicers
  • Design: Dark theme for high contrast, minimal clutter, consistent color scheme

RESULTS AND INSIGHTS

  • Top-selling product: DOTCOM POSTAGE (0.02% of total revenue)
  • Peak sales months: November and December showing significant seasonal increases
  • Largest market: Canada identified as the primary geographic market
  • Seasonal trends: Q4 showing significant sales increases
  • Customer behavior: Clear patterns in purchase frequency and order values

SKILLS DEMONSTRATED

Data Cleaning Data Preparation Data Modeling DAX Calculations Visual Design Conditional Formatting Interactive Dashboards Power Query Excel

TECHNOLOGIES USED

Power BI DAX Power Query Microsoft Excel Data Visualization

Gallery

Power BI online retail dashboard overview showing total sales, customer count, invoice metrics, and key retail KPIs
Total revenue visualization displaying aggregate sales revenue across all products and time periods
Monthly sales trend chart showing seasonal patterns with peak sales in November and December
Geographic sales analysis map showing revenue distribution by country with Canada as top market
Customer revenue analysis chart ranking top customers by total purchase value
Product sales ranking chart showing top-selling products by revenue, led by DOTCOM POSTAGE
Average order value metric calculating mean revenue per transaction across all customers
Average quantity per order visualization showing typical number of items purchased per transaction
Customer count metric displaying total unique customers in the retail dataset
Invoice count visualization showing total number of transactions and orders processed
Time-based analysis chart categorizing sales by year and month for trend identification

CHALLENGES & SOLUTIONS

Challenge: Handling large datasets efficiently in Power BI with performance constraints
Solution: Optimized data model using a flat table structure and efficient DAX calculations, ensuring fast query performance even with substantial data volumes.
Challenge: Creating meaningful DAX calculations for complex business metrics
Solution: Developed calculated measures using DAX functions like CALCULATE, FILTER, and RANKX to accurately compute percentages, rankings, and averages.
Challenge: Presenting multiple insights in a single dashboard without clutter
Solution: Used a clean dark theme with consistent color schemes, organized KPIs at the top, and implemented interactive filtering to allow users to explore data without overwhelming visuals.

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