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Spark playbook scenarios · Spark: AI Store Assistant

Design a return-request handling workflow

A support team needs consistent handling of return or refund requests without skipping eligibility checks. In this case, the immediate task is to design a return-request handling workflow. The workflow should produce a return or refund decision draft and processing steps, using the merchant's actual records and constraints.

Topic
Returns and Refund Automation
Target keyword
shopify returns automation
Copyable AI prompt

A prompt you can drop directly into Spark

First replace every [bracketed] placeholder with real store scope and constraints, then add any actual records or data you have, and paste it into your preferred AI assistant or Spark agent. Spark will follow this page's workflow to produce structured output and verification steps.

ai-prompt.txt
Act as a Shopify operations specialist.
Help me design a return-request handling workflow.
My store context is [describe the business, products and target audience].

My scope is [specify the affected products, pages, customers or reporting period]. Use these inputs: [provide order details, purchased items, policy, request reason and prior refunds].

Check the supplied eligibility rules, calculate the proposed outcome and handle exceptions before any authorized system action.
Return a return or refund decision draft and processing steps for the specified task.
Show the relevant evidence or before-and-after examples and explain how I can verify the result.
If essential data is missing, ask for it and mark unsupported conclusions as unknown.
Do not invent metrics, product claims or customer facts.
For any publication, message, account or store change, use only connected tools within my explicitly authorized scope and report success only after verification; otherwise provide the draft or proposed steps.
Use in Spark
How to solve

A recommended resolution workflow

Split the work into input, judgment, and deliverable phases. Verify each step's output before moving to the next.

01

Step 1

Start with order details, purchased items, policy, request reason and prior refunds.

02

Step 2

Check the supplied eligibility rules, calculate the proposed outcome and handle exceptions before any authorized system action.

03

Step 3

Deliver a return or refund decision draft and processing steps; verify the result against the supplied records and identify unresolved inputs.

FAQ

Common questions when running this scenario

Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.

Does a return request always require a refund?

No. The applicable policy and circumstances may lead to a return, exchange, refund or further review.

Why check prior refunds?

Without that check, repeated requests can lead to duplicate or excessive refunds.

What information is needed to investigate this use case?

Start with order details, purchased items, policy, request reason and prior refunds. These inputs establish the relevant scope and help separate an actual issue from missing information or an unsuitable comparison. Without them, the result should remain a proposed approach rather than a confirmed diagnosis.

Related scenarios

Continue with adjacent or same-topic scenarios

Start with scenarios under the same topic, then expand into cross-topic matches suggested by similarity.

Next step

Want these AI scenarios embedded directly into daily operations?

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