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Retail Sales Transaction Data
Retail & Consumer Behavior
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Free
About
This dataset contains wholesale retail sales information from a company's branches and resellers. It provides fundamental sales data, where the 'customer' field distinguishes between resellers and company branches. For privacy considerations, unique identifiers such as Customer ID, Product ID, and Invoice ID have been processed with LabelEncoder, ensuring each customer or product has a distinct ID. The data spans over three years, with the latest version including records up to January 2023, reflecting how product prices may have changed over time.
Columns
- InvoiceID: A unique identifier for each transaction or invoice. A single transaction may include multiple records for the same customer on the same date, involving various products. This ID can be valuable for grouping transactions and identifying items that were sold together.
- Date: The exact date and time when the transaction or sale occurred.
- ProductID: A unique code assigned to each item or product sold.
- TotalSales: Represents the total sales price for a given transaction. To ascertain the unit price, divide the value in this column by the corresponding quantity.
- Discount: The monetary amount of any discount applied to the transaction.
- CustomerID: A distinct identifier for each customer. In this dataset, a customer can be either a reseller or a branch of the company.
- Quantity: The number of items sold within a specific transaction.
Distribution
The dataset is typically provided as a CSV file, with a file size of approximately 1.83 MB. It contains roughly 33,400 records or rows, with no missing or mismatched data observed across its eight columns.
Usage
This dataset is well-suited for a variety of analytical applications and use cases, including:
- Determining the optimum pricing strategy for individual products.
- Forecasting future demand for each item over upcoming months.
- Calculating the Customer Lifetime Value (CLV) for individual customers.
- Performing customer segmentation, ranging from straightforward RFM (Recency, Frequency, Monetary) models to more sophisticated approaches.
- Developing customer-to-product recommendation systems to suggest the most suitable products for specific customers.
Coverage
The data covers a time period of more than three years, specifically from 1st January 2019 up to 9th November 2022, with the most recent updates extending to January 2023. While specific geographic or demographic details are not provided due to data privacy measures, the dataset focuses on sales transactions involving company branches and resellers.
License
Attribution-NonCommercial-ShareAlike 3.0 IGO (CC BY-NC-SA 3.0 IGO)
Who Can Use It
This dataset is ideal for:
- Data Analysts: For exploring sales trends, identifying top-performing products, and understanding customer behaviour.
- Business Strategists: For optimising pricing, planning inventory, and evaluating sales performance across different branches or resellers.
- Marketing Teams: For segmenting customers, tailoring promotional offers, and enhancing customer engagement through product recommendations.
- Data Scientists: For building predictive models for demand forecasting, customer lifetime value, and advanced customer segmentation.
Dataset Name Suggestions
- Retail Sales Transaction Data
- Wholesale & Branch Sales Records
- B2B Sales Performance Dataset
- Customer & Product Sales Analysis
- Sales Channel Transaction Log
Attributes
Original Data Source: Retail Sales Transaction Data
QUALITY