Date&Time Operations: Customer Purchase Analysis
Working with date & time values can be tricky. KNIME offers a variety of nodes for date-& time-related operations. To make use of these nodes, it is crucial to transform the relevant columns into Date&Time cells.
Based on a customer purchase analysis use case, this example workflow demonstrates how to how to convert a date & time value from String into Date&Time and illustrates how different date & time operations can be performed. After processing the transaction data, the workflow identifies each customer's potential churn risk based on a their inactivity.
The sample data has 5 columns:
Customer ID: Each customer's identification number
Purchase Date: The date and timestamp when each purchase was made
Purchase Amount: The purchase amount
Store Location: The location of the store where the purchase was made
Product Category: The product category