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Global Electronics Retail Sales Data
Retail & Consumer Behavior
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About
Sales data for a fictitious global electronics retailer provides insight into transactions, products, customers, stores, and currency exchange rates. This collection of data is designed to help understand customer locations, product types, seasonal sales trends, and patterns in order volume or revenue. It can also be used to analyse differences between online and in-store sales, as well as track average delivery times.
Columns
- CustomerKey: A unique identifier for each customer.
- Gender: The gender of the customer, listed as Male or Female.
- Name: The full name of the customer.
- City: The city where the customer resides.
- State Code: The abbreviated code for the customer's state or province.
- State: The full name of the customer's state or province.
- Zip Code: The postal code for the customer's location.
- Country: The country where the customer resides.
- Continent: The continent where the customer resides.
- Birthday: The customer's date of birth.
Distribution
The data is provided in CSV format. The
Customers.csv file contains 1.43 MB of data with 10 columns and 15,300 rows.Usage
Ideal applications for this data include:
- Analysing seasonal patterns and trends in order volume and revenue.
- Identifying the types of products sold and the geographic locations of customers.
- Calculating the average delivery time and observing how it changes over time.
- Comparing the average order value (AOV) between online and in-store sales channels.
- Conducting time series and geospatial analyses to uncover deeper retail insights.
Coverage
The data covers customers from 8 different countries across 3 continents, with North America being the most represented. The United States accounts for 45% of the customers. Customer birth dates in the file range from 3 February 1935 to 18 February 2002.
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
- Retail Analysts: To investigate sales trends, customer behaviour, and regional performance.
- Data Scientists: For building predictive models for sales forecasting or customer segmentation.
- Marketing Professionals: To understand customer demographics and geographic distribution for targeted campaigns.
- Business Strategists: To evaluate the performance of online versus in-store sales channels and inform operational decisions.
Dataset Name Suggestions
- Global Electronics Retail Sales Data
- Fictional Electronics Retailer Customer & Sales Info
- Electronics Marketplace Transactional Data
- Retail Customer Demographics and Sales Analysis
Attributes
Original Data Source: Global Electronics Retail Sales Data
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