Online Retail Transaction Dataset

Columns

• Orders Table
  • order_id: A unique identifier for each order, serving as the primary key.
  • customer_id: A unique identifier for the customer associated with the order. This column may not be unique at this table level.
  • order_status: Indicates the current status of an order, such as delivered, cancelled, or processing.
  • order_purchase_timestamp: The precise time and date when the customer placed the order.
  • order_approved_at: The timestamp when the order received approval from the seller.
  • order_delivered_timestamp: The timestamp when the order was delivered to the customer's location.
  • order_estimated_delivery_date: The anticipated delivery date communicated to the customer at the time of order placement.
• Order Items Table
  • order_id: The unique identifier for the order to which the item belongs.
  • order_item_id: The specific item number within an order, forming part of the primary key in conjunction with order_id.
  • product_id: A unique identifier for the product.
  • seller_id: A unique identifier for the seller of the product.
  • price: The selling price of the product.
  • shipping_charges: Any costs associated with the shipping of the product.
• Customers Table
  • customer_id: A unique identifier for a customer, acting as the primary key for this table.
  • customer_zip_code_prefix: The initial part of the customer's postcode.
  • customer_city: The city where the customer is located.
  • customer_state: The state where the customer is located.
• Payments Table
  • order_id: The unique identifier for the order associated with the payment.
  • payment_sequential: Provides information on the sequence of payments made for a given order.
  • payment_type: The method of payment used, such as credit card or debit card.
  • payment_installments: The number of payment instalments, particularly for credit card transactions.
  • payment_value: The monetary value of the transaction.
• Products Table
  • product_id: A unique identifier for each product, serving as the primary key for this table.
  • product_category_name: The name of the category to which the product belongs.
  • product_weight_g: The weight of the product in grams.
  • product_length_cm: The length of the product in centimetres.
  • product_height_cm: The height of the product in centimetres.
  • product_width_cm: The width of the product in centimetres.

Distribution

Usage

• Analysing e-commerce order patterns and customer behaviour.
• Optimising supply chain and logistics operations.
• Identifying trends in product sales and payment methods.
• Developing and evaluating marketing strategies for e-commerce services.
• Supporting business intelligence and operational decision-making.

Coverage

License

Who Can Use It

• E-commerce businesses: For internal analytics, operational improvements, and strategic planning.
• Data analysts and scientists: To conduct sales performance analysis, customer segmentation, and predictive modelling.
• Logistics and supply chain professionals: To enhance delivery routes, inventory management, and overall supply chain efficiency.
• Marketing teams: For developing targeted campaigns and understanding market trends.
• Researchers: Studying e-commerce ecosystems, consumer behaviour, and market dynamics.
• Developers: Building analytical tools or features for e-commerce platforms.

Dataset Name Suggestions

• E-commerce Order and Supply Chain Analytics Data
• Online Retail Transaction Dataset
• Customer Order and Product Insights Data
• E-commerce Logistics and Sales Records
• Digital Store Operational Data

Attributes