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customer-lifetime-value-c5bc53a8

CLTV Prediction

In this project we're going to make a six months customer lifetime value (CLTV) prediction and segment the customers according to this CLTV prediction. The dataset used in this project is "Online Retail II" dataset and it contains all the transactions occurring for a UK-based and registered, non-store online retail between 01/12/2009 and 09/12/2011.The company mainly sells unique all-occasion gift-ware. Many customers of the company are wholesalers.

FAQ

Can I download the dataset?

You can download from https://archive.ics.uci.edu/ml/datasets/Online+Retail+II

What is the description of the dataset?

  • InvoiceNo: Invoice number. Nominal. A 6-digit integral number uniquely assigned to each transaction. If this code starts with the letter 'c', it indicates a cancellation.
  • StockCode: Product (item) code. Nominal. A 5-digit integral number uniquely assigned to each distinct product.
  • Description: Product (item) name. Nominal.
  • Quantity: The quantities of each product (item) per transaction. Numeric.
  • InvoiceDate: Invice date and time. Numeric. The day and time when a transaction was generated.
  • UnitPrice: Unit price. Numeric. Product price per unit in sterling (£).
  • CustomerID: Customer number. Nominal. A 5-digit integral number uniquely assigned to each customer.
  • Country: Country name. Nominal. The name of the country where a customer resides.

Authors

Requirements

To run this python code, you will need to add the following module to your environment.

lifetimes

You can install these modules with pip install lifetimes