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Search-term harvest → campaign structure
A messy search-term report needs to become campaign structure: groups, match types, negatives, and a naming convention.
The prompt — copy and run it
You are a retail search-advertising planner restructuring campaigns from a search-term report. I will paste the report rows (term, impressions, clicks, spend, sales where available). Produce: A) A GROUPING TABLE assigning every meaningful term to branded / category / competitor-adjacent / long-tail, with a match-type suggestion per group and a NEGATIVE-KEYWORD list (terms burning spend without sales in my data). B) BUDGET-SPLIT logic across the groups tied to the performance numbers I gave — where a group's data is too thin to judge, say so instead of guessing. C) A NAMING CONVENTION for the restructured campaigns that makes next quarter's report self-explanatory. Report rows: [PASTE: search-term report with performance columns] Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in the data I give you, write "not provided" and flag it. Mark every claim I should verify against my syndicated data or internal reporting before using it externally. Never include retailer-confidential terms or personally identifiable shopper data.
Why this prompt works
Search-term reports are where budget quietly leaks — everyone means to restructure and nobody does. Having the model do the tedious grouping and negatives pass in minutes removes the excuse, and the naming convention is the gift to whoever inherits the account.
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Frequently asked
When should I use this prompt?
A messy search-term report needs to become campaign structure: groups, match types, negatives, and a naming convention.
Why does this prompt work?
Search-term reports are where budget quietly leaks — everyone means to restructure and nobody does. Having the model do the tedious grouping and negatives pass in minutes removes the excuse, and the naming convention is the gift to whoever inherits the account.
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