How Amazon Ads Search Terms Are Classified for Weekly Reviews

Signals that drive classification

The most useful classification decisions come from combining several data points instead of relying on a single metric. For example, a term with many clicks and zero orders after sufficient maturity is usually a stronger negative keyword candidate than a term that has just started receiving traffic. The same logic applies to bid adjustments: if a term generates sales but its ACoS is above the campaign target, it may need a lower bid rather than immediate exclusion.

• Spend and clicks: highlight terms that are consuming budget.
• Orders and sales: confirm whether those clicks produce revenue.
• ROAS, ACoS, CPA: add profitability context.
• Conversion rate: identifies terms that attract clicks but don't convert.
• Campaign maturity: prevents premature decisions on low-data terms.

Tools like Amazon Negative Keyword Tool by Todoza apply these signals in a read-only workflow, but the same structure can be built manually in an Excel workbook.

Three common classification groups

A practical way to sort search terms in a weekly review is to assign every underperforming or unknown term to one of three groups. This prevents knee-jerk reactions and keeps decisions consistent across campaigns.

• Negative keyword candidates: spend has accumulated without sales or the conversion rate is very low.
• Bid reduction opportunities: sales exist but the term is too expensive relative to its return.
• Needs more data: clicks are too low to judge; leave the term visible while monitoring it.

The thresholds for each group should be set per campaign because a term that is unprofitable in a low-margin product campaign may still be acceptable in a brand-building or high-margin campaign.

When this matters for weekly reviews

If search terms are classified before any cleanup decisions are made, the rest of the review meeting becomes much easier to run. You can go down the list, document the reason for each action, and avoid re-litigating data you already interpreted. This is especially helpful for teams or agencies handling multiple accounts or marketplaces, where consistent decision rules reduce miscommunication.

Because many Amazon Ads tools are read-only by design, final campaign changes still require manual approval. Classification is about preparing a reliable decision queue, not automating live changes.