SplitOut Automate

This workflow is ideal for:

• E-commerce Managers: Who need to analyze customer checkout sessions to improve sales strategies.
• Marketing Teams: Looking to filter and segment customer data based on specific custom fields for targeted campaigns.
• Data Analysts: Who require a streamlined process to retrieve and visualize data from Stripe for reporting purposes.
• Business Owners: Interested in understanding customer behavior and preferences through detailed checkout session analysis.

This workflow addresses the challenge of retrieving and analyzing checkout sessions from Stripe over a specific time frame (last 20 days) while allowing users to filter results based on custom fields such as nickname and job title. It automates the data retrieval process and provides a structured way to visualize relevant customer data, enhancing decision-making capabilities.

1. Trigger: The workflow is manually triggered by the user.
2. Retrieve Checkout Sessions: It calls the Stripe API to get the latest checkout sessions created in the last 20 days.
3. Split Data: The retrieved data is split into separate nodes for easier handling and visualization.
4. Filter Custom Fields: The workflow filters the data to include only those sessions that have specific custom fields filled out (like nickname and job title).
5. Final Output: The filtered data can then be used for further analysis or reporting.