In this project, we are measuring customer retention with descriptive analysis. Tasks performed:
- Quantifying new customer acquisition
- Quantifying new customer activation
- Quantifying engagement and retention 3.1) Implementing retention definition 3.2) Visualizing retention probability with survival curve 3.3) Creating and comparing customer cohorts 3.4) Recency, Frequency, Monetary analysis of existing customers 3.5) Searching for leading indicators of retention
Dataset source : https://archive.ics.uci.edu/ml/datasets/online+retail This is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.The company mainly sells unique all-occasion gifts. Many customers of the company are wholesalers.
Attribute Information:
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. 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 each 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 each customer resides.