This n8n workflow automates the process of retrieving recent Stripe checkout sessions, splitting and filtering the data based on custom fields, and preparing it for visualization or analysis. It is ideal for businesses that want to analyze customer checkout behavior, segment transactions, or monitor specific customer details.

The workflow begins with a sticky note explaining the overall goal: to fetch all checkout sessions from the last 20 days, with pagination enabled to ensure all data is captured. It then performs an HTTP request to Stripe’s API, requesting checkout sessions created within the specified time frame. To handle large datasets, pagination parameters are utilized, fetching subsequent pages until all sessions are retrieved.

Next, the data is split into manageable chunks for easier visualization using a ‘splitOut’ node. Additional sticky notes provide context about the data splitting process. The workflow also includes a filtering step based on custom fields, where only sessions with specific custom attributes like ‘nickname’ and ‘job_title’ are selected. This allows users to focus on particular customer segments or transactions.

Finally, the data is split again to prepare for further processing or reporting. This workflow is practical for automated reporting, customer segmentation, or monitoring specific checkout behaviors over a defined period, reducing manual effort and ensuring data accuracy.