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BANA482 | Retail Performance Analytics

We built this case study for STAT 482: Capstone in Analytics for Business. Our work uses the Sample Superstore dataset to study sales, profitability, discounting, product performance, and regional patterns through Tableau dashboards and written analysis.

Project Focus

We focused on one main question: are stronger sales translating into sustainable profit?

To answer that, we analyzed:

  • Sales and profit trends from 2014 to 2017.
  • Profitability by product category and customer segment.
  • The relationship between discounting and profit.
  • Regional sales and profit patterns.
  • Top and bottom product performance.

Dataset

We used the Sample Superstore dataset, which contains 9,994 order-line records and 21 variables. The data includes order dates, ship dates, regions, states, customer segments, product categories, sub-categories, sales, quantities, discounts, and profit.

The original public dataset source is Kaggle:

https://www.kaggle.com/datasets/vivek468/superstore-dataset-final

Tools

We used:

  • Tableau for dashboards, visual analytics, calculated fields, filters, and product ranking.
  • Microsoft Word for the written report.
  • Microsoft PowerPoint for the presentation.
  • CSV data for the Tableau source file.

What We Built

We created three main Tableau dashboards:

  • Executive Overview: total sales, total profit, profit ratio, average discount, and time trends.
  • Profitability Drivers: category profit, segment profit, discount impact, and profitability heatmap.
  • Regional and Product Insights: state-level sales, top products, bottom products, and interactive filters.

Key Findings

  • Total sales reached about $2.30M and total profit reached about $286K.
  • Overall profit margin was about 12.47 percent.
  • Sales increased over time, but profit moved with more volatility.
  • Technology was the strongest product category by profit.
  • Furniture was the weakest product category by profit.
  • The Consumer segment contributed the largest share of profit.
  • Higher discounts were often linked with lower or negative profit.
  • The West region had the highest sales and profit, while the Central region had the lowest profit.

Recommendations

Based on our analysis, we recommended that management:

  • Reduce aggressive discounting and use clear discount thresholds.
  • Prioritize Technology because it has stronger profit performance.
  • Review Furniture pricing, costs, and product positioning.
  • Strengthen Consumer segment retention while improving segment diversification.
  • Customize product and pricing strategies by region.
  • Reevaluate products that consistently produce weak sales or weak profit.

Repository Structure

Path Purpose
assignment/ Original case assignment brief
data/ Source dataset used for the analysis
reports/ Final PDF reports
reports/editable/ Editable Word report files
presentations/ Final presentation deck
tableau/ Tableau workbook
tableau/exports/ Exported Tableau sheets and dashboard slides

Main Files

File Purpose
data/Sample - Superstore.csv Source dataset used for the analysis
tableau/interactive-analytics.twb Tableau workbook
tableau/exports/interactive-analytics-all-sheets.pdf Exported Tableau sheets
tableau/exports/interactive-analytics-all-sheets.pptx Tableau sheet export in presentation format
tableau/exports/interactive-analytics-dashboard.pptx Tableau dashboard export
presentations/case-4-retail-performance-presentation.pptx Final presentation deck
reports/case-4-retail-performance-report.pdf Final written report
reports/editable/case-4-retail-performance-report.docx Editable final written report
reports/case-4-individual-report-mohammed.pdf Individual report version
reports/editable/case-4-individual-report-mohammed.docx Editable individual report version
assignment/case-4-assignment-brief.pdf Original case instructions

How To Review

Start with reports/case-4-retail-performance-report.pdf for the full written analysis. Then open presentations/case-4-retail-performance-presentation.pptx for the presentation flow. To inspect the dashboards directly, open tableau/interactive-analytics.twb in Tableau. We keep the data in data/Sample - Superstore.csv, and the workbook is set up to look for that file from the project structure.

License

We licensed our original coursework in this repository under the MIT License. The Sample Superstore dataset remains subject to its original source terms from Kaggle and its data owner.

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