SALES PERFORMANCE DASHBOARD
Introduction:
The Sales Performance Dashboard project aimed to provide a comprehensive overview of a company’s sales data in a visually appealing and easy-to-understand format.
This dashboard was created to help decision-makers gain valuable insights into key performance metrics, such as customer count, product sales, profit, and more. The process involved gathering data from ChatGPT, cleaning and processing it in Excel Power Query, and then using Excel to create a pivot table and build an interactive dashboard.
In the process of obtaining data from ChatGPT for the Sales Performance Dashboard project, I followed a structured approach:
- Requesting Data from ChatGPT: I initiated data retrieval by posing specific questions or prompts related to the sales data needs.
2. Receiving Responses: ChatGPT provided text-based responses containing the requested data.
3. Extracting Data: I carefully extracted the relevant information from ChatGPT’s responses.
4. Formatting Data: Extracted data was structured into tables for better organization.
5. Cleaning Data: Data was reviewed for errors, duplicates, and inconsistencies, and necessary cleaning was performed.
6. Handling Null Values: Null values were identified and addressed, by filling them and excluding incomplete records.
7. Transforming Data: Data transformations were executed, including date format conversions and aggregation for analysis readiness.
8. Exporting Data: The cleaned and formatted data was saved as Excel files for use in creating this Sales Performance Dashboard in Excel.
Below are the insights I generated for the sales performance data:
1. Total Number of Customers:
The first step was to create a card visualization displaying the total customer count. Data was sourced from ChatGPT, cleaned by removing duplicates and inconsistencies and loaded into Excel. The result was a clear and concise representation of the total customer count, making it easy for decision-makers to grasp this essential metric at a glance.
2. Total Number of Products:
Similar to the customer count, the total number of products was visualized using a card. Data was gathered, cleaned, and loaded into Excel. This card provided a quick and easily understandable snapshot of the company’s product inventory, aiding in inventory management and decision-making.
3. Total Profit:
The total profit card was created to showcase the overall profitability of the business. The process involved extracting profit data from ChatGPT, ensuring data consistency, and loading it into Excel. The resulting card visualization offered a clear picture of the company’s financial health, helping stakeholders assess the business’s overall profitability.
4. Total Sales:
The total sales card provided an instant view of the company’s revenue. Data on sales was extracted, cleaned, and loaded into Excel. This card visualization allowed decision-makers to monitor the company’s sales performance and set performance benchmarks.
5. Quantity Sold by Month:
A clustered column chart was used to visualize the quantity of products sold each month.
Data was sourced, cleaned, and transformed in Excel Power Query, making it suitable for charting. The clustered column chart allowed for easy identification of trends and seasonality in sales.
6. Quantity Sold by Product:
Using a Pie Chart, the quantity of each product sold was visualized. Data was obtained, cleaned, and structured to create the chart.
This visualization made it effortless for stakeholders to identify the best-selling products and allocate resources accordingly.
7. Quantity Sold by Location:
To understand sales performance by location, a clustered bar chart was used. Data was extracted, cleaned, and loaded into Excel, making it suitable for charting.
The clustered bar chart allowed decision-makers to compare sales across different locations and make informed decisions about resource allocation.
8. Payment Method by Customers:
A Pie Doughnut chart was employed to visualize payment methods preferred by customers. Data on payment methods was extracted, cleaned, and structured for charting. This visualization helped in assessing the popularity of various payment methods among customers.
9. Quantity Sold by Salesperson:
A clustered column chart was used to visualize the quantity of products sold by each salesperson.
was obtained, cleaned, and transformed in Excel Power Query to create this chart. The chart allowed management to evaluate the performance of individual salespeople.
10. Quantity Sold by Day of the Week:
Another clustered bar chart was used to display the quantity of products sold on different days of the week. Data was extracted, cleaned, and loaded into Excel for chart creation. This visualization provided insights into sales patterns throughout the week.
11. Profit Margin per Product:
Lastly, a Line Chart was used to visualize profit margins per product over time.
Data on profit margins was extracted, cleaned, and structured for charting. This chart helped decision-makers track the profitability of individual products.
The success of the Project:
The Sales Performance Dashboard project was a resounding success. It provided a comprehensive, user-friendly, and visually appealing representation of key sales metrics. Decision-makers found the dashboard invaluable for monitoring and improving the company’s sales performance. The project demonstrated the power of data visualization in making complex information easily understandable and actionable. It enabled the company to make informed decisions, optimize resources, and ultimately improve its bottom line.
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About the Author
I am Thaddeus Ndubuisi Amadi, a committed Graphic Designer, adept Social Media Manager, and an enthusiastic data aficionado with a talent for transforming numbers into enlightening insights. My unwavering commitment lies in harnessing the potential of data to steer well-informed decision-making. Join me in embarking on data-driven journeys, and together, we’ll explore the boundless possibilities of information. Connect with me, and let’s embark on data-driven adventures hand in hand!
