We have taken the Online_Retail dataset from UCI Machine Learning (Link: https://archive.ics.uci.edu/ml/datasets/online+retail) to perform RFM analysis and Kmeans Clustering.

It is a transnational data set which contains transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.The company sells unique all-occasion gifts. Many customers of the company are wholesalers.

The following is the attribute information:

1. InvoiceNo: Invoice number. Nominal, a 6-digit integral number uniquely assigned to each transaction. If this code starts with letter 'c', it indicates a cancellation.

2. StockCode: Product (item) code. Nominal, a 5-digit integral number uniquely assigned to each distinct product.

3. Description: Product (item) name. Nominal.

4. Quantity: The quantities of each product (item) per transaction. Numeric.

5. InvoiceDate: Invice Date and time. Numeric, the day and time when each transaction was generated.

6. UnitPrice: Unit price. Numeric, Product price per unit in sterling.

7. CustomerID: Customer number. Nominal, a 5-digit integral number uniquely assigned to each customer.

8. Country: Country name. Nominal, the name of the country where each customer resides.