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Consumer Transaction Records
E-commerce & Online Transactions
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About
This dataset captures customer purchase records across various product categories throughout the year 2023. It includes essential customer details such as age and gender, alongside transaction specifics like product category, quantity, and total amount spent. This data is ideal for analysing consumer behaviour, identifying sales trends, and developing recommendation or forecasting models.
Columns
- Date: The date on which the transaction occurred.
- Gender: The gender of the customer (e.g., Male or Female).
- Age: The age of the customer at the point of purchase.
- Product Category: The specific category of the item purchased (e.g., Beauty, Clothing, Electronics).
- Quantity: The number of units purchased within the transaction.
- Price per Unit: The cost of a single item in the selected category.
- Total Amount: The overall amount spent for that transaction, calculated as Quantity × Price per Unit.
- An auto-generated index column may be present from a previous export; this can typically be ignored or removed.
Distribution
This dataset is provided in CSV format and has a file size of approximately 43.64 kB. It contains 8 distinct columns and consists of 1000 records or rows of customer purchase data.
Usage
This dataset is well-suited for a variety of analytical applications and use cases, including:
- Consumer segmentation
- Market basket analysis
- Sales forecasting
- Product trend analysis
- Customer profiling model development
- Dynamic pricing strategy formulation
- Analysing spending patterns broken down by gender or age group.
- Tracking the most popular product categories over time.
- Predicting total amounts spent based on customer features.
- Identifying seasonal or monthly spikes in specific product categories.
Coverage
The dataset primarily covers customer purchase activities during the calendar year 2023, with transaction dates ranging from 1st January 2023 to 1st January 2024. It includes demographic information such as customer age, ranging from 18 to 64 years, and gender, with a split of 51% female and 49% male. Product categories include Clothing (35%), Electronics (34%), and other items (31%). The geographic scope for this data is not specified within the provided information.
License
CC0: Public Domain
Who Can Use It
This dataset is particularly useful for:
- Data Analysts: To explore consumer behaviour, spending patterns, and product trends.
- Marketing Professionals: To perform customer segmentation and develop targeted marketing strategies.
- Retail Strategists: To identify popular product categories, inform inventory management, and develop pricing strategies.
- Data Scientists: For building and training models for sales forecasting, recommendation systems, and customer profiling.
Dataset Name Suggestions
- Retail Sales 2023
- Customer Purchase Data 2023
- Consumer Transaction Records
- Annual Retail Sales Analytics
Attributes
Original Data Source:Consumer Transaction Records
QUALITY