eoroot1974/demos_d_retail_cust_purchases

Purchase Recommendation Dataset

Overview

This dataset contains synthetic purchase records of 5,000 customers from a tech retail shop over the course of one year (2024). It is designed to support tasks like sequential product recommendation, customer behavior analysis, and predictive modeling for marketing strategies.

Key Features:

• Customers: 5,000 unique customers with randomly generated identifiers.
• Products: 100 unique products purchased by customers.
• Timeframe: Purchase records span from January 1, 2024, to December 31, 2024.
• Interactions: 50,000 purchase records with details on the amount spent per transaction.

Dataset Details

Columns:

1. CustomerName: The name of the customer (synthetically generated).
2. ProductName: The name of the product purchased (e.g., Product_1, Product_2).
3. PurchaseDate: The date of the transaction (YYYY-MM-DD format).
4. AmountSpent: The monetary value spent on the transaction (in USD).
5. CustomerID: A unique numerical identifier for each customer.
6. ProductID: A unique numerical identifier for each product.

Example Rows:

CustomerName	ProductName	PurchaseDate	AmountSpent	CustomerID	ProductID
Client_1	Product_10	2024-01-15	125.50	1	10
Client_2	Product_20	2024-02-10	89.99	2	20

Usage

Applications

This dataset is suitable for:

• Sequential Recommendations: Predicting the next product a customer might purchase.
• Customer Segmentation: Analyzing purchasing behaviors to group customers based on spending patterns or product preferences.
• Predictive Analytics: Building machine learning models for sales forecasting or personalized marketing.

How to Use

1. Load the Dataset:

   import pandas as pd
   
   # Load dataset
   df = pd.read_csv("path/to/demos_retail_cust_purchases.csv")
   

2. Exploration:

   print(df.head())
   print(df.info())
   

3. Sequential Modeling: Create input-output pairs for predicting the next purchase based on historical transactions.

Dataset Statistics

• Number of Records: 50,000
• Number of Customers: 5,000
• Number of Products: 100
• Date Range: January 1, 2024 - December 31, 2024

Licensing

This dataset is provided under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Users are free to share and adapt the dataset, provided proper attribution is given.

Citation

If you use this dataset in your research or projects, please cite as:

@dataset{purchase_recommendation_2024,
  title={Purchase Recommendation Dataset},
  author={Synthetic Data Generator},
  year={2024},
  url={https://huggingface.co/datasets/your-dataset-name}
}

Acknowledgements

This dataset was synthetically generated using Python libraries like faker and pandas. Special thanks to the open-source community for providing the tools to generate and share data.

Contact

For questions or issues, please reach out to [Your Name/Organization] at [Your Email or Contact Info].