This algorithm enriches the customer profile with information about their purchase behavior.
Description
You must provide data about the customer’s transactions as input. For example, the amount of money spent, the discount received, the purchase date and other similar input data for each transaction.
The output can include information such as the total number of orders made by a customer so far, the total and average amount spent, the average number of items in each order and similar.
Customer purchase statistics input data and output
| Input data | Output |
| Transactional data
Customer_id. Date. Order_id. Order_line_id. Product_id. Amount. Discount. |
Total amount.
Total orders. Average spend. Number of returns. Total amount of discount. Average number of items per order. |
Output examples
The output is provided as new fields that are associated with each customer profile.
Example of the output
| Customer ID | 11223344 |
| Total amount | €150.00 |
| Total orders | 3 |
| Returns | 1 |
| Total discount | €75.00 |
| Total quantity | |
| Average quantity per ticket | 2.1 |
Tags:
- Transactional.
- Clustering.
- Single customer.
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