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Retail Sales Analysis

Optimizing Inventory, Pricing, and Regional Strategy through Data-Driven Insights

Tools Used: Power BI · Excel · Tableau

Project Overview

  • In today’s competitive retail landscape, understanding what drives sales is more than just tracking numbers — it’s about decoding customer behavior, market dynamics, and operational efficiency.
  • I worked with a mid-sized e-commerce platform to analyze over 12 months of transaction data, covering thousands of SKUs across diverse product categories. The goal was to identify patterns that could improve profitability and reduce waste.

    • Data Preparation & Exploration

    Using Excel, I began by cleaning and structuring the dataset, which included:

  • Daily sales transactions
  • Product metadata (category, brand, price tier)
  • Store location and regional identifiers
  • Promotional calendar and discount history

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    I performed exploratory analysis to uncover:

  • Sales distribution across categories
  • Seasonal spikes and dips
  • Outliers in pricing and returns
  • Inventory turnover rates

    • This foundational work helped define the KPIs we would track throughout the project: gross sales, margin contribution, sell-through rate, and regional performance.

    Dashboard Development & Visualization

    With Power BI, I built a suite of interactive dashboards tailored for different stakeholders:

  • Executive View: High-level trends in revenue, profit, and growth YoY
  • Category Manager View: SKU-level performance, pricing impact, and stock alerts
  • Regional Manager View: Store-wise comparisons, local demand shifts, and promotional effectiveness

    • Each dashboard featured dynamic filters, drill-down capabilities, and trend lines to support decision-making in real time.

    Tableau was used to create visual stories for quarterly reviews — including heatmaps of regional sales, time-series analysis of seasonal demand, and scatter plots showing price vs. volume relationships.

    Key Insights & Strategic Recommendations

    The analysis revealed several high-impact findings:

  • Top-Selling Products: A small group of SKUs contributed disproportionately to revenue. These were prioritized for reordering and featured in marketing campaigns.
  • Seasonal Trends: Winter accessories and festive items peaked sharply in Q4, while summer apparel had a longer tail. Promotions were rescheduled to align with these cycles.
  • Regional Performance: Coastal stores showed higher demand for lightweight fabrics, while northern regions preferred insulated products. Inventory was rebalanced accordingly.
  • Pricing Sensitivity: Mid-tier products responded well to small discounts, while premium items retained value without markdowns. This led to a tiered pricing strategy.

    • Operational Impact

    The insights translated into tangible business improvements:

  • Inventory Optimization: Reduced overstock by 18 percent and improved stock availability for high-demand items
  • Profitability Boost: Adjusted pricing and markdown schedules led to a 12 percent increase in gross margin
  • Marketing ROI: Targeted campaigns based on regional preferences saw a 25 percent uplift in conversion rates
  • Decision Agility: Stakeholders could now make data-backed decisions weekly instead of relying on monthly reports

    • Collaboration & Workflow

    I worked closely with cross-functional teams:

  • Merchandising: To align product assortment with demand forecasts
  • Marketing: To time promotions and tailor messaging by region
  • Operations: To streamline restocking and reduce logistics costs

    • Feedback loops were built into the dashboards, allowing teams to flag anomalies, suggest improvements, and track the impact of changes over time.

    Lessons Learned

  • Context matters: Sales data alone doesn’t tell the full story — combining it with regional, seasonal, and promotional context unlocks deeper insights.
  • Visualization drives adoption: Stakeholders engaged more with insights when they were presented visually and interactively.
  • Iterative refinement: The dashboards evolved over time based on user feedback, making them more intuitive and impactful.