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Marketing Insight Report
Introduction: This report analyzes retail sales transaction data obtained from Kaggle. The tabular dataset consists of both categorical and numerical data types with 13 columns detailing sales transactions in various stores across the United States. The objective is to identify key insights including top-selling products, customer segment trends, and other actionable findings that will allow further analysis. The data was explored using Microsoft Excel.
Observations
High Revenue Generating Products
After the first review of the dataset, it can be observed that Phones generated the highest revenue, followed closely by Chairs and Storage. Other products like Binders and Tables also had a strong performance. This indicates that Technology and Furniture categories drive major revenue for the business.
2. Demand Drivers: Binders and Paper had the highest unit sales volume, indicating strong demand and frequent repeat purchases. However, Binder sales appear to be largely driven by discounts, impacting profitability. This suggests exploring bundling strategies with complementary products such as Paper or Storage to reduce reliance on discounts.
3. Customer Segment Trends: The Consumer segment generated the highest sales, followed by Corporate and Home Office customers and this emphasizes that the direct-to-consumer is the primary revenue driver. The Consumer segment also accounted for the highest profits which further highlights their significance to the business.
Conclusion The initial analysis of the dataset uncovered insights into the sales and profitability of the retail stores. It highlights the top revenue-generating products as Phones and Chairs while individual consumers form the largest customer segment. Future marketing efforts should focus on this category of consumers and further analysis could investigate the impact of discounts on profitability and understanding customer purchase frequency and average order value to identify opportunities for increasing sales.
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