01
Step 1
Record, for each period, the spend and the attributed revenue together with the period boundaries, currency, attribution window and value definition that produced them.
Back to topic
Spark playbook scenarios · Spark: AI Store Assistant
Track attributed revenue relative to ad spend
Period-to-period return figures move, but the tracking itself keeps changing window and value definitions. In this case, the immediate task is to track attributed revenue relative to ad spend. The workflow should produce a per-period tracking report with reconciliation notes, so the recorded changes reflect real movement in the merchant's data.
Topic
Marketing Attribution and ROAS
Target keyword
shopify roas tracking
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 track attributed revenue relative to ad spend.
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: [per-period spend and attributed revenue with the period boundaries, currency, attribution window and value definition that produced them]. Hold the window and the value definition identical across every period so a movement reflects a change in the data, and mark as not comparable any period whose settings differ, reporting it separately rather than in the trend.
Return the tracking report with reconciliation notes 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.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
Hold the window and the value definition identical across every period so a movement reflects a change in the data, and mark as not comparable any period whose settings differ, reporting it separately rather than in the trend.
03
Step 3
Deliver a per-period tracking report with reconciliation notes, check each period's revenue against the order export before publishing, and re-run the earliest period under the current settings wherever a definition change has made the history inconsistent.
FAQ
Common questions when running this scenario
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
How often should the figure be reviewed?
Use the reporting cadence the merchant already follows, and keep the period length, window and value definition identical each time. Changing any of them between reviews makes the movement you are tracking indistinguishable from the change in method.
Why did the figure move with no campaign change?
Check the attribution window and the data freshness first, since a settings change or late-arriving conversions can move the figure on their own. Reconcile against the order export before treating the movement as a performance signal.
Can a single day drive a decision?
Prefer a period long enough to contain a full buying cycle, and note any delay in conversion reporting. A day's figure is often incomplete at the moment it is read, which makes it a weak basis for pausing spend.
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.
Calculate advertising return using stated cost and value definitions
Compare channel ROAS using compatible definitions
Connect store sales with available attribution evidence
Compare marketing channel outcomes and tradeoffs
Analyze orders attributed to marketing campaigns
Reconcile marketing attribution with store outcomes
Next step
Want these AI scenarios embedded directly into daily operations?
Ciwi Spark builds Shopify-native AI tools and agents around the workflows merchants actually run: research, ads, translation, and customer support. Stop rewriting the same prompts by hand.