Dark Mode
Multi-Channel US Sales Data
E-commerce & Online Transactions
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset offers insights into US regional sales data across various sales channels, including In-Store, Online, Distributor, and Wholesale. Comprising 7,991 rows and 16 columns, it encompasses details from order and product specifics to sales performance metrics. It provides an overview of sales transactions and customer interactions, facilitating in-depth analysis of sales patterns, trends, and potential opportunities. This resource is valuable for analysing sales trends, identifying popular products, assessing the performance of different sales channels, and optimising pricing strategies for various regions.
Columns
- OrderNumber: A unique identifier for each order.
- Sales Channel: The channel through which the sale was made (e.g., In-Store, Online, Distributor, Wholesale).
- WarehouseCode: Code representing the warehouse involved in the order.
- ProcuredDate: Date when the products were procured.
- OrderDate: Date when the order was placed.
- ShipDate: Date when the order was shipped.
- DeliveryDate: Date when the order was delivered.
- CurrencyCode: Type of currency used, consistently USD.
- SalesTeamID: Identifier for the sales team involved.
- CustomerID: Identifier for the customer.
- StoreID: Identifier for the store.
- ProductID: Identifier for the product.
- Order Quantity: Quantity of products ordered.
- Discount Applied: The applied discount for the order.
- Unit Cost: Cost of a single unit of the product.
- Unit Price: Price at which the product was sold.
Distribution
The dataset is provided in CSV format, specifically as
US_Regional_Sales_Data.csv, with a file size of 876.89 kB. It is structured as tabular data, containing 7,991 individual records and 16 distinct columns, providing a detailed breakdown of sales transactions.Usage
This dataset is ideal for a range of analytical and predictive applications:
- Sales Trend Analysis: Plotting sales trends over time to identify seasonal patterns and changes in demand.
- Sales Channel Performance: Comparing sales performance across different channels using visualisations.
- Product Performance: Visualising the distribution of sales across different products to identify popular items.
- Discount Impact Analysis: Analysing the effect of discounts on sales.
- Regional Performance Mapping: Creating maps to visualise sales performance across different regions.
- Price Prediction: Building machine learning models (e.g., Linear Regression, Random Forest Regression, Neural Networks) to predict unit price based on features like order quantity, discount applied, and unit cost.
- Feature Importance Analysis: Identifying influential features affecting price prediction.
- Time Series Forecasting: Developing models to predict future prices based on historical sales data.
Coverage
The dataset focuses on US regional sales data. Date fields such as
ProcuredDate, OrderDate, ShipDate, and DeliveryDate indicate that the data spans multiple years, with examples suggesting dates from 2018 through 2020. The dataset does not specify a demographic scope beyond customer and store identifiers.License
CC0: Public Domain
Who Can Use It
This dataset is particularly useful for:
- Data Analysts: For exploring sales patterns, trends, and business opportunities.
- Business Intelligence Professionals: To generate reports and dashboards on sales performance by channel, product, and region.
- Data Scientists: For developing predictive models, such as price prediction and sales forecasting.
- Sales Managers: To assess team performance, optimise sales strategies, and identify areas for improvement.
- Marketing Teams: To understand product popularity and the impact of discounts.
- Strategists: For optimising pricing strategies and regional sales approaches.
Dataset Name Suggestions
- US Regional Sales Transactions
- Multi-Channel US Sales Data
- North American Sales Performance
- Retail Sales Data (US)
- Sales Activity Log (USA)
Attributes
Original Data Source: Multi-Channel US Sales Data
QUALITY