01
Step 1
Start with order IDs, creation and status timestamps, values, refunds and reporting rules.
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Spark playbook scenarios · Spark: AI Store Assistant
Analyze order volume and composition
An operator needs to understand order volume and composition without counting records inconsistently. In this case, the immediate task is to analyze order volume and composition. The workflow should produce an order report with clear inclusion rules, using the merchant's actual records and constraints.
Topic
Order Analytics and Reporting
Target keyword
shopify order analytics
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 analyze order volume and composition.
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 IDs, creation and status timestamps, values, refunds and reporting rules]. Deduplicate orders, define included statuses and summarize the requested dimensions with reconciled counts.
Return an order report with clear inclusion rules 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.Scenario & problem
When does this scenario usually come up?
Start with the business context, the trigger, and the expected output before moving into the execution steps.
An operator needs to understand order volume and composition without counting records inconsistently. In this case, the immediate task is to analyze order volume and composition. The workflow should produce an order report with clear inclusion rules, using the merchant's actual records and constraints.
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.
02
Step 2
Deduplicate orders, define included statuses and summarize the requested dimensions with reconciled counts.
03
Step 3
Deliver an order report with clear inclusion rules; 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.
Should canceled or test orders be included?
That depends on the report's purpose. State the inclusion rule so operational and commercial reports are not confused.
Why preserve order IDs in a detailed report?
They allow aggregated figures to be traced back to the underlying records and help investigate discrepancies.
What information is needed to investigate this use case?
Start with order IDs, creation and status timestamps, values, refunds and reporting rules. 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
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Next step
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