You have been hired as a marketing analyst by a rapidly growing mid-sized retail company that has accumulated a significant amount of sales data. Despite their growth, the company is struggling to extract actionable insights due to fragmented and disorganized reporting processes. The leadership team is eager to identify the main drivers of profit, recognize top-performing products and customers, and optimize sales strategies across different states and market segments. However, their ability to make informed, data-driven decisions is currently hindered by the absence of a comprehensive, user-friendly dashboard.Your assignment is to develop a comprehensive sales dashboard that consolidates all of the companysales data into a single, interactive platform. This dashboard should empower the companyleadership and sales teams to quickly assess key performance metrics, identify trends, and make informed decisions that will drive more effective and strategic business actions.Objective: The dashboard should visually represent the sales data provided, modeled after the example dashboard shown in the provided video. The key metrics and visualizations should include:
Total Sales
Total Profit
Profit Percentage
Units Sold
Top Selling Product
Sales and Profit by Month
Sales Generated by Customer
Sales by States
Sales Breakup by Segment
You must use Excel to create the dashboard.Ensure that your submitted files include a sheet demonstrating the thoroughness of your analysis.Any dashboard generated using AI will be marked zero.Data provided contains the following columns:
Segment: The market segment where the product was sold (e.g., Franchise, Retail, Wholesale, Online).
Customer_ID: Unique identifier for customers.
Product_ID: Unique identifier for products.
Discount Band: The discount level applied (e.g., Low, Medium).
Units Sold: The number of units sold.
Manufacturing Price: The cost to manufacture the product.
Sale Price: The selling price of the product.
Discounts: Total discounts given.
Date: The date of the sale.
Customer_Name: The name of the customer.
Product_Name: The name of the product.
State: The state where the sale occurred.
Gross Sales: Total sales before deductions.
Sales: Total sales after deductions.
COGS: Cost of Goods Sold.
Profit: Profit generated from the sales.
Profit (‘000): Profit in thousands.
Month: The month of the sale.
Quarter: The quarter of the sale.
Year: The year of the sale.
Steps:
Data Cleaning and Preparation:
Ensure data consistency and accuracy.
Handle missing values and correct any data inconsistencies.
Derive additional columns if needed (e.g., Monthly Sales, Yearly Profit, etc.).
Visualizations:
Total Sales & Profit: Display total sales and total profit.
Profit Percentage: Calculate and display the profit percentage.
Units Sold: Display total units sold.
Top Selling Product: Identify and display the top-selling product.
Sales & Profit by Month: Create a bar chart showing sales and profit for each month.
Sales Generated by Customers: List customers and their corresponding sales.
Sales by States: Visualize sales distribution across different states.
Sales Breakup by Segment: Pie chart showing the percentage of sales by different market segments.
Dashboard Design:
Design a dashboard that is clear, visually appealing, and easy to interpret.
Use appropriate chart types, colors, and labels to enhance readability.
Analysis and Insights:
Analyze the data and provide insights based on the visualizations.
Identify trends, patterns, and any notable observations from the data.
Presentation:
Prepare a brief report or presentation summarizing the findings.
Highlight key metrics and insights from the dashboard.
Include a 20 – 25 minute presentation video where you walk through the workings of the dashboard and a brief summary of the analysis. The presentation should cover:
Overview of the Dashboard: Introduce the key metrics and visualizations included.
Data Sources and Preparation: Explain the data cleaning and preparation steps and highlight key aspects of your analysis.
Detailed Walkthrough: Go through each visualization, explaining what it shows and why it is important.
Key Insights and Observations: Summarize the main findings and insights from the data.
Technical Aspects: Briefly discuss any technical challenges or interesting techniques used in creating the dashboard.
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