Analysis / Ecommerce and retail

Find patterns behind ecommerce order cancellations

Review cancellation frequency, timing and recorded reasons across order groups, keeping unknown reasons separate and avoiding fault or fraud inference.

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Your starting prompt.

Analyze [uploaded order status history] to calculate cancellation frequency and elapsed time by channel, product category and payment state. Separate customer requests, merchant initiated cancellations and unknown reasons, and show the proportion canceled before versus after fulfillment. Produce an evidence based investigation list and missing reason audit; do not infer buyer fraud or operational fault from a cancellation record alone.

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Method and review

Keep the assumptions visible.

Reconcile orders, refunds, costs and fulfillment at a consistent grain. Use supplied exports when a native Connection is unavailable, and distinguish revenue from contribution.

For this task, check

Status history and reason codes can be incomplete or reflect different operational definitions.

This starting prompt has no published worked example yet. Begin with a small sample and check the calculations before relying on the result.

Before you begin

Bring exports you are allowed to upload, or data your Workspace can already query.
Choose the reporting period and agree what each record represents.

Work with permitted files or queryable data. Verify the result against the original records.

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Make it your investigation.

Copy the prompt above, create or open your Workspace, and paste it into Chat. Add the inputs you have permission to use and adapt the assumptions with your agent.

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