Segment Search Terms and Negative Keywords by Targeting Type
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Quick answer
Search term and negative keyword segmentation by targeting type is a structured way to separate Amazon Ads performance data into category-targeted and ASIN-targeted buckets. Instead of treating all search terms as one list, advertisers group clicks, spend, and conversions by the targeting context that produced them. This makes it easier to see where wasted spend is concentrated, decide which terms should become negative keywords, and identify bid-reduction opportunities without mixing signals from structurally different campaigns.
When category and ASIN targeting are compared side by side, a single search term report can bury important performance differences. Segmenting the data first gives you a cleaner base for negative keyword and bid decisions.
Why blended search term data misleads
Category targeting tends to match broader shopper behavior, while ASIN targeting often captures terms around specific products and competitor pages. When both are combined in a single view, a term that looks unprofitable overall may actually perform well in one targeting context and poorly in another.
Separating search terms by targeting type lets you evaluate spend and conversion signals in the right context. The goal is not to add more complexity, but to make negative keyword choices and bid adjustments match the actual targeting source.
- Category targeting can reveal broader discovery terms that need different thresholds.
- ASIN targeting may produce more competitor-related terms that require tighter negation.
- Performance thresholds often differ by targeting type.
A practical segmentation workflow
Start by exporting your Amazon Ads search term report and tagging each row by its associated campaign or ad group targeting type. Then group key metrics like clicks, spend, sales, and ACoS by that tag. A tool like Amazon Negative Keyword Tool by Todoza can classify terms as negative keyword candidates or bid-reduction opportunities using campaign-specific signals.
- Export search term reports with campaign and ad group context.
- Add a targeting type label: category or ASIN.
- Review zero-conversion and high-spend terms within each bucket.
- Separate terms into negative keyword candidates, bid reductions, or more data needed.
When this matters
Segmentation becomes especially useful when you are scaling campaigns or reviewing accounts across multiple marketplaces. It helps prevent a global negative keyword from blocking a valuable search term that only performs well under one targeting type. Since these Amazon Ads analytics tools are read-only, keeping segmentation as an analysis step lets you approve changes manually before they go live.
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Once search terms and negatives are segmented by targeting type, category vs ASIN performance comparisons become easier to trust. This approach fits directly into the broader Amazon Category Targeting vs ASIN Targeting comparison by keeping the data behind each decision clean and source-aware.