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Retail Sales Analytics Dataset
Retail & Consumer Behavior
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About
This dataset features detailed sales transactions, providing insights into order specifics, revenue, profit, and customer information. It is ideal for sales analysis, trend forecasting, and generating business intelligence insights. The data spans various product categories and is structured to facilitate straightforward analysis of sales performance across different locations and time periods.
Columns
- Order ID: A unique identifier for each order. There are 1,194 valid entries with 547 unique IDs. The most common ID is B-26032, representing 1% of entries.
- Amount: The total sale amount for the order. All 1,194 entries are valid. The mean amount is 5,180, with a standard deviation of 2,800. Amounts range from a minimum of 508 to a maximum of 9,992.
- Profit: The profit earned from the order. All 1,194 entries are valid. The mean profit is 1,350, with a standard deviation of 1,120. Profits range from a minimum of 50 to a maximum of 4,930.
- Quantity: The number of items sold in the order. All 1,194 entries are valid. The mean quantity is 10.7, with a standard deviation of 5.77. Quantities range from a minimum of 1 to a maximum of 20.
- Category: A broad classification of the product, such as Electronics. All 1,194 entries are valid, with 3 unique categories. Furniture is the most common (34%), followed closely by Office Supplies (33%).
- Sub-Category: The specific type of product within its category, for example, Printers or Electronic Games. All 1,194 entries are valid, with 12 unique sub-categories. Tables and Pens are the most common, each representing 10%.
- PaymentMode: The payment method used, such as UPI or Credit Card. All 1,194 entries are valid, with 5 unique payment modes. Debit Card and Credit Card are the most common, each at 22%.
- Order Date: The date when the order was placed. All 1,194 entries are valid, with dates ranging from 22 March 2020 to 15 March 2025.
- CustomerName: The name of the customer who placed the order. All 1,194 entries are valid, with 802 unique customer names.
- State: The state where the order was delivered. All 1,194 entries are valid, with 6 unique states. New York (19%) and California (18%) are the most common.
- City: The city where the order was delivered. All 1,194 entries are valid, with 18 unique cities. Buffalo (8%) and San Francisco (7%) are the most common.
- Year-Month: A date-time representation of the order month and year. All 1,194 entries are valid, with dates ranging from 1 March 2020 to 1 March 2025.
Distribution
This dataset is provided as a CSV file named
Sales Dataset.csv, with a file size of 118.08 kB. It contains 12 columns and features 1,194 records, as indicated by the consistent number of valid entries across all fields.Usage
This dataset is ideally suited for:
- Sales performance analysis
- Revenue and profit trend forecasting
- Business intelligence reporting
- Identifying top-performing products or categories
- Understanding customer purchasing patterns
- Analysing sales performance by location and time period
Coverage
The dataset covers sales transactions primarily across six unique states, with New York and California being the most frequently represented. It includes data from 18 unique cities, notably Buffalo and San Francisco. The temporal scope spans approximately five years, with order dates ranging from March 2020 to March 2025. The data includes transactions across 3 main product categories and 12 sub-categories, serving 802 unique customers.
License
CC0: Public Domain
Who Can Use It
This dataset is highly beneficial for:
- Data Analysts: For uncovering sales trends and insights.
- Business Strategists: For informing decisions based on sales performance.
- Marketing Professionals: For understanding customer behaviour and product popularity.
- Researchers: For studying e-commerce patterns and market dynamics.
- Students: For learning data analysis, especially in the business domain.
Dataset Name Suggestions
- Sales Transaction Data
- E-commerce Sales Records
- Retail Sales Analytics Dataset
- Order and Profit Data
- Product Sales Insights
Attributes
Original Data Source: Retail Sales Analytics Dataset
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