CustomerSalesReport

Project Title: CustomerSalesReport

Overview:

This project dives into customer sales data to uncover valuable insights for improving sales performance and understanding customer behavior. It leverages the power of SQL for data extraction, Excel for data cleaning and manipulation, and Power BI for insightful data visualization.

Objectives:

• Identifying top-selling products or services.
• Segmenting the customer base by purchase behavior.
• Analyzing trends in sales performance over time.
• Identifying customer segments with high purchase value.
• Discovering underperforming product categories.
• Analyzing the effectiveness of marketing campaigns (if sales data reflects them).

Data Source:

https://www.kaggle.com/code/fabiendaniel/customer-segmentation/input

Methods:

Technologies Used: SQL, Excel, Google Cloud, Power Bi.

Extract and Clean Customer Sales Data:

• Utilize SQL queries to efficiently extract relevant sales data from a database.
• Clean and manipulate the data in Excel to ensure accuracy and prepare it for analysis.

Analyze Customer Buying Habits and Sales Performance:

Apply data analysis techniques to identify trends and patterns within the customer sales data. This may include techniques like:

• Identifying top-selling products or services.
• Segmenting the customer base by purchase behavior.
• Analyzing trends in sales performance over time.

Visualization:

• Plotting historical data to visualize trends and patterns.
• Using Power Bi for creating insightful and clear visualizations.

Results:

• Analyzed trends in sales performance over time
• Suggested targeted marketing campaigns for high-value customer segments.
• Highlighted the need for sales training on upselling techniques for specific product categories.
• Improve customer engagement by tailoring marketing campaigns to specific customer needs.

Conclusion:

This customer sales report project effectively demonstrated the power of data analysis in uncovering valuable insights for improving sales performance and understanding customer behavior. Utilizing SQL for data extraction, Excel for data manipulation, and Power BI for visualization, the project delivered key results.