Superstore Sales Report

Table of Contents

• Project brief
• Objective
• Questions to Answer
• Data source
• Tools
• Dashboard design charts
• Development
• Data Cleaning
• Data processing
• Findings
• Recommendations

Project brief

Analyzed Superstore Sales Report with over £2.3M in sales data using an interactive dashboard.

Objective

To identify top-performing product lines, customer segments, and shipping methods in order to maximize profit growth and streamline sales strategy.

Questions to answer

• What factors contributed to the YoY profit growth?

• How does this quarter’s sales compare to the same period last year?

• Which products or categories are dragging overall profitability down?

• Why is Technology performing better than Office Supplies and Furniture?

• What marketing efforts were done specifically for the Technology category?

• Can we increase profit margins in Office Supplies or Furniture?

• What made Phones the best-performing sub-category?

• Are low-performing sub-categories worth keeping, or should they be removed or improved?

• How do profit margins compare across the different sub-categories?

• What strategies helped the Consumer segment outperform others?

• How can we improve engagement with Corporate and Home Office segments?

• Why do most customers choose Standard Class shipping over faster options?

• Is there a cost-benefit to promoting Same Day or First Class shipping?

• Do certain shipping methods result in higher customer satisfaction or repeat purchases?

• Based on current trends, what will next quarter’s top-selling sub-category likely be?

Tools

Tools	Purpose
Excel	Cleaning, Transformation, Processing and Visualization

Data

Here are the Data columns used in achieving project goal

• KPIs
• Product segment
• Product category
• Product sub-category
• Shipping method
• Region
• City
• Delivery duration
• Monthly
• Year

Dashboard design

Here is a list of appropriate chart visuals used in answering key questions.

• Score cards
• Column chart
• Donut chart
• Area chart
• Progress Bar chart
• Column chart
• Line chart
• Filter panel

Development

Here’s a step by step guide on how the data was approached

• Get data from source
• Load to Excel
• Clean and transform with Excel
• Visualizations using Excel customized charts
• Generate Insights
• Give recommendations

Data Cleaning

The goal is to clean the dataset to ensure data integrity, accuracies and standardization.

• Only relevant columns will be retained.
• All data types should be appropriate for the contents of each column.
• No column contains null values, indicating complete data for all records.

Processing

Findings

• Total Quantity Sold 67.9k units.

• Total Sales of £2.30M

• Total Profit of £286.4k

• Year-over-Year (YoY) profit increased by 14.2% – a positive trend.

• Technology had the highest sales of £836.1k

• Office Supplies and Furniture followed with £710k and £742k respectively.

• Phones led with £330k in sales.

• Followed by Chairs £328.4k, Copiers £203.4k, and Accessories (£167.4k).

• Consumers brought in the highest sales £1.16M, more than Corporate and Home Office.

• Standard Class accounts for 60% of orders.

• Same Day and First Class make up smaller shares 15.4% and 19.5%

Recommendations

• Focus more on Technology and Phone products – promote them in marketing and sales strategies.

• Increase inventory for high-selling sub-categories like Phones and Chairs.

• Since Consumers drive most sales, create exclusive offers or loyalty programs for them.

• Since most orders are Standard Class, explore faster, low-cost shipping options to attract more Same Day or First Class users.

• Investigate why categories like Home Office are low in sales – is it pricing, demand, or product mix?

• Suggest accessories or furniture items when customers buy technology items like phones.