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UK Retail Purchase Data
Retail & Consumer Behavior
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About
This dataset captures the essence of transactions within a retail environment, offering insights into consumer behaviour and retail dynamics. Its primary purpose is to unlock valuable information for retail analytics, facilitating the exploration of purchasing patterns, popular products, pricing strategies, and regional preferences. By delving into this wealth of information, analysts and businesses can uncover insights to drive strategic decision-making, refine marketing efforts, and ultimately, enhance customer experiences to thrive in today's competitive landscape.
Columns
- CustomerID: A unique identifier for each individual customer. This column contains 100,000 valid records.
- ProductID: A unique identifier for each product. This column has 100,000 valid records and includes 4 unique product IDs, with 'C' and 'D' being among the most common.
- Quantity: Represents the number of units purchased for a particular product in a transaction. This column has 100,000 valid records, with values ranging from 1 to 9, and a mean quantity of 5.01.
- Price: The unit price of the product. This column has 100,000 valid records, with prices ranging from 10 to 100, and an average price of 55.1.
- TransactionDate: The specific date and time when the transaction occurred. This column contains 100,000 valid records, covering transactions from 30th April 2023 to 29th April 2024.
- PaymentMethod: The method used by the customer to complete the payment. This column has 100,000 valid records and includes 4 unique payment methods, such as 'PayPal' and 'Credit Card'.
- StoreLocation: The physical location where the transaction took place. This column contains 100,000 valid records, each representing a unique store location.
- ProductCategory: The category to which the product belongs. This column has 100,000 valid records and includes 4 unique product categories, such as 'Clothing' and 'Books'.
- DiscountApplied(%): The percentage of discount applied to the product during the transaction. This column has 100,000 valid records, with discounts ranging from 0% to 20%, and an average of 10%.
- TotalAmount: The total amount paid for the entire transaction. This column contains 100,000 valid records, with amounts ranging from 8.27 to 896, and a mean total amount of 248.
Distribution
The dataset is typically provided as a CSV file, named
Retail_Transaction_Dataset.csv. It has a file size of 12.8 MB and contains ten essential columns. Each column has 100,000 valid records, indicating a substantial volume of transactional data.Usage
This dataset is ideal for:
- Identifying seasonal trends and peak purchasing periods.
- Analysing the impact of various marketing campaigns over time.
- Understanding evolving consumer payment preferences and the effectiveness of different payment strategies.
- Gaining insights into consumer responsiveness to promotions and discounts.
- Optimising pricing strategies for maximum impact.
- Refining marketing efforts and enhancing customer experiences.
Coverage
The dataset's temporal scope extends from 30th April 2023 to 29th April 2024. Geographically, it covers 100,000 unique store locations, indicating a diverse spatial distribution of transactions. While specific demographic data is not directly listed, the unique customer identifiers, product categories, and payment method details offer indirect insights into customer behaviour.
License
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Who Can Use It
- Data Analysts: To uncover valuable insights into consumer behaviour and retail trends.
- Businesses and Retailers: For strategic decision-making, refining marketing efforts, and optimising pricing.
- Marketing Teams: To assess campaign effectiveness and understand consumer responsiveness to promotions.
- Financial Strategists: To analyse payment preferences and optimise payment strategies.
Dataset Name Suggestions
- Retail Sales Transactions 2023-2024
- E-commerce Transaction Log
- UK Retail Purchase Data
- Consumer Spending Patterns Dataset
Attributes
Original Data Source: UK Retail Purchase Data
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