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RetailPulse Analytics Dashboard

Project Overview

This dashboard analyzes revenue, customer demographics, product performance, inventory levels, and return rates to identify key business trends and support data-driven decision making.

Tools Used:

Power BI, DAX, Power Query, CSV Dataset

Dashboard Preview

Dashboard

Dashboard

Dataset Link:

https://www.kaggle.com/datasets/malaiarasugraj/e-commerce-dataset

📊 Business Insights

Revenue Analysis

  • Books generated the highest revenue at 50,476M, closely followed by Electronics (50,467M).
  • Revenue distribution across categories is highly balanced, with minimal variation between the top-performing categories.

Inventory & Popularity Analysis

  • Several products exhibit high popularity despite relatively lower stock levels, indicating potential inventory risks.
  • Footwear achieved a popularity score of 100 with a stock level of 48K units.
  • Gaming Console and Monitor also recorded maximum popularity scores while maintaining comparatively lower inventory levels.

Customer Demographics

  • The 25–34 age group contributed the highest revenue, generating approximately 202M and accounting for 20.06% of total sales.
  • Customer revenue contribution is fairly balanced across all age segments.

Geographic Performance

  • Dubai, UAE emerged as the highest revenue-generating location with 16,951M in revenue.
  • Chicago, USA (16,939M) and Singapore (16,904M) closely followed, indicating strong global revenue distribution without a single dominant market.

Product Return Analysis

  • Toaster recorded the highest average return rate at 10.75%.
  • Non-Fiction (10.52%) and Fiction (10.51%) products also experienced elevated return rates.
  • These products may require further investigation to identify potential quality, expectation, or customer satisfaction issues.

Shipping Cost Analysis

  • Shipping costs are distributed almost equally across all shipping methods.
  • Express Shipping accounts for the highest share at 33.35%, though the difference from Overnight and Standard shipping remains marginal.

Seasonality Analysis

  • Seasonal impact on product popularity appears minimal.
  • Both seasonal and non-seasonal products maintain nearly identical average popularity scores of approximately 49.97, suggesting limited influence of seasonality on customer demand.

💡 Business Recommendations

  • Monitor high-popularity products with lower stock levels to reduce stockout risks.
  • Investigate products with elevated return rates to improve customer satisfaction and profitability.
  • Continue investing across multiple product categories, as revenue generation is evenly distributed.
  • Maintain a geographically diversified sales strategy since revenue is balanced across key markets.
  • Reassess seasonal marketing efforts, as seasonality currently shows limited impact on product popularity.

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Interactive Power BI dashboard providing insights into sales performance, customer behavior, top-performing locations, and product return trends using e-commerce data.

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