Account results arrive at campaign level in one currency, while store reporting compares periods across currencies and product lines. In this case, the immediate task is to consolidate Google Ads results for store reporting. The workflow should produce a unified reporting model and discrepancy log with subtotals checked against the original exports.
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 consolidate Google Ads results for store reporting.
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: [campaign and ad group exports with the account structure above them, spend and conversion columns, account currency and conversion settings, and store-side order and product line figures for the same periods]. Roll account data up to the store's product line and period dimensions without overwriting platform metrics that have no store-side equivalent, keeping those as labelled platform figures, and state the conversion method and rate date wherever the account currency differs from the reporting currency.
Return a unified reporting model and discrepancy log with subtotals checked against the original exports 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 the campaign and ad group exports, the account structure above them, the spend and conversion columns each export carries, the currency and conversion settings applied to the account, and the store-side order and product line figures for the same periods.
Roll account data up to the store's product line and period dimensions without overwriting platform metrics that have no store-side equivalent, keeping those as labelled platform figures, and state the conversion method and rate date wherever the account currency differs from the reporting currency.
Deliver the unified reporting model and discrepancy log with subtotals checked against the original exports, then verify that rolled-up totals equal the account export subtotals at every level, that currency-converted amounts name the rate used and that no store dimension receives a value the export cannot support.
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
Exports shift columns between refreshes and flatten the account hierarchy, so a pasted table silently reorders comparisons. A defined model fixes the levels and fields, which keeps a period-over-period chart stable even after the export layout changes.
State the conversion method and the rate date applied, and use one rule for every period in the same chart. Mixing converted and unconverted amounts makes a spend change indistinguishable from a rate movement, so any period converted at another rate is marked in the log.
No. Account-only measures stay labelled as platform data at the level the account reports them. Forcing them into product line or period dimensions invents a precision the export never carried and hides the mismatch from anyone reading the result.
Start with scenarios under the same topic, then expand into cross-topic matches suggested by similarity.
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