license:mit size_categories:n<1K format:csv modality:tabular modality:text library:datasets library:pandas library:mlcroissant library:polars region:us infinite-dataset-hub synthetic
---
license: mit
tags:
- infinite-dataset-hub
- synthetic
---

# TransactionMatrix

tags: classification, customer_segmentation, price_elasticity

_Note: This is an AI-generated dataset so its content may be inaccurate or false_

**Dataset Description:**

The dataset 'TransactionMatrix' encapsulates customer purchase behavior and product details. It includes transaction data, product information, and pricing metrics, from which it computes valuable features like average purchase price, quantity sold, purchase frequency, customer segmentation, and price elasticity. The dataset is designed for analysis of customer transaction patterns and strategizing product pricing.

**CSV Content Preview:**

```
TransactionID,CustomerID,ProductID,Quantity,Price,TransactionDate,PurchaseFrequency,CustomerSegment,PriceElasticity
TX001,C001,P001,2,49.99,2023-01-15,3.5,Premium,0.75
TX002,C002,P002,1,19.99,2023-01-16,1.2,Standard,1.20
TX003,C003,P003,5,39.99,2023-01-17,5.0,Budget,0.60
TX004,C004,P001,3,49.99,2023-01-18,2.0,Premium,0.80
TX005,C005,P002,2,19.99,2023-01-19,1.5,Standard,1.10
```

In this preview, the columns represent the following:
- `TransactionID`: A unique identifier for each transaction.
- `CustomerID`: The unique identifier of the customer making the purchase.
- `ProductID`: The unique identifier for the product purchased.
- `Quantity`: The number of units purchased in the transaction.
- `Price`: The price per unit of the product.
- `TransactionDate`: The date on which the transaction occurred.
- `PurchaseFrequency`: The average number of transactions per customer.
- `CustomerSegment`: The categorized group of the customer based on their purchasing behavior (e.g., Premium, Standard, Budget).
- `PriceElasticity`: A calculated metric indicating the sensitivity of the quantity demanded to a change in price.

**Source of the data:**

The dataset was generated using the [Infinite Dataset Hub](https://huggingface.co/spaces/infinite-dataset-hub/infinite-dataset-hub) and microsoft/Phi-3-mini-4k-instruct using the query 'customer transactions, product information, and pricing, average purchase price, quantity sold and other relevant columns. Develop relevant features such as purchase frequency, customer segmentation, and price elasticity':

- **Dataset Generation Page**: https://huggingface.co/spaces/infinite-dataset-hub/infinite-dataset-hub?q=customer+transactions,+product+information,+and+pricing,+average+purchase+price,+quantity+sold+and+other+relevant+columns.+Develop+relevant+features+such+as+purchase+frequency,+customer+segmentation,+and+price+elasticity&dataset=TransactionMatrix&tags=classification,+customer_segmentation,+price_elasticity
- **Model**: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct
- **More Datasets**: https://huggingface.co/datasets?other=infinite-dataset-hub
