Google Search Term Mining: Expand, Clean, and Segment Intent
The search terms report is not a trash bin. First sort queries into expand, clean, split, or observe, then use n-grams, page fit, margin, and evidence paths to choose the next action.
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Ranfeng WeiPublished
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Review scope Reviewed against Shopify, Google Search, ads, analytics, and ecommerce operating workflows.
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Understand what this lesson solves
The search terms report is not a trash bin. First sort queries into expand, clean, split, or observe, then use n-grams, page fit, margin, and evidence paths to choose the next action.
Diagnose the layer holding performance back, then improve search terms, bidding, budgets, landing pages, PMax, feeds, and value signals without giving up profit control.
Lesson outline
- 1Choose the search-term review window
- 2Export the Search terms report
- 3Classify intent with the 10-term classifier
- 4Run n-gram checks on high-spend roots
- 5Write intent, economic value, and fit gaps
- 6Use priority scoring to choose the top five
- 7Choose one action per query
- 8Copy the search-term review notes
Public core framework
- Use the last 28-30 days or 60-90 days, and mark promotions, stockouts, page edits, tracking fixes, budget changes, and bid strategy changes. First decide whether the window is usable.
- Export search term, campaign, ad group, keyword, match type, cost, clicks, conversions, conversion value, device, location, landing page, and date range. Do not work from the summary only.
- Sort queries into waste, potential, brand, competitor, compatibility, bulk/custom, free/DIY, and related groups. Classify intent before choosing the action.
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