Step 1
Collect spend and attributed revenue per channel with the attribution window, currency and value definition each one was produced under, plus the matching store orders.
Each channel is measured under its own attribution window, so the ROAS numbers are not comparable as they stand. In this case, the immediate task is to compare channel ROAS using compatible definitions. The workflow should produce the figures restated under one shared definition, with each restated value traced back to the merchant's records.
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.
Act as a Shopify operations specialist.
Help me compare channel ROAS using compatible definitions.
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-channel spend and attributed revenue with each channel's attribution window, currency and value definition, plus the matching store orders]. Restate every channel under one shared window, currency and value definition before any comparison, keeping both the original and the restated figures in the table so the effect of the restatement stays visible.
Return the channel return comparison 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.Split the work into input, judgment, and deliverable phases. Verify each step's output before moving to the next.
Collect spend and attributed revenue per channel with the attribution window, currency and value definition each one was produced under, plus the matching store orders.
Restate every channel under one shared window, currency and value definition before any comparison, keeping both the original and the restated figures in the table so the effect of the restatement stays visible.
Deliver the channel comparison built only on restated figures, trace each restated value back to the supplied records, and list any channel that could not be restated with the reason it was left out.
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
Only when spend, value and window definitions match, which they rarely do. Restate each channel under one rule first and keep the original beside it, so you can see how much of the gap came from definitions rather than performance.
Follow the merchant's stated value definition and keep it identical across channels in the same report. Including them for some channels and not others shifts the ranking without any change in what the advertising produced.
Not necessarily, because a channel may be assigned an earlier stage. Judge it against the role the merchant gave it, and say which tradeoff the comparison reflects before drawing a conclusion.
Start with scenarios under the same topic, then expand into cross-topic matches suggested by similarity.
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.