This algorithm enriches the customer profile with data about their purchases over time.
Description
You must provide data about the customer’s transactions, including any time-based details, such as the purchase date, which is mandatory when saving an ‘event’ in Contacthub. For example, the amount of money spent, the discount received and the purchase date.
The output can include information such as the total number of orders, the total and average amount spent within a predefined time frame, such as six months, as well as the inter-purchase time and the loyal time.
Customer time-based behavior statistics input data and output
| Input data | Output |
| Transactional data
Customer_id. Date. Order_id. Order_line_id. Product_id. Amount. Discount. |
Total amount last #months.
Total orders last #months. First transaction date. Last transaction date. Inter-purchase time. Loyal time. |
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 last 6 months | €65.00 |
| Total orders last 6 months | 1 |
| First transaction date | 2016-03-11 |
| Last transaction date | 2018-01-18 |
| Inter-purchase time | 340 days |
| Loyal time | 678 days |
Tags:
- Clustering.
- Transactional.