Optimize Ad Spend by Detecting Costly or Underperforming Terms

Separate costly terms from acceptable performance

Start by setting a ROAS baseline for each auto targeting group or account. Terms that fall below that baseline while accumulating meaningful spend are strong candidates for review. A single costly click is not always a pattern, but repeated clicks without orders often signals a term that should be paused or negated.

• Spend level: Highlights terms that consume budget without enough return.
• ROAS below target: Surfaces queries that do not meet the account's efficiency goal.
• Conversion pattern: Distinguishes isolated wasted clicks from ongoing underperformance.

A tool like Amazon Negative Keyword Tool by Todoza applies this logic by importing search term reports and classifying terms using campaign signals like spend and ROAS.

Keep every change in a human approval workflow

Costly term detection works best when it stays read-only. Recommendations may include negative keyword candidates or bid reductions, but they should not go live automatically. This gives your team a chance to confirm whether a term still has value for a new product or seasonal campaign. For client-ready summaries, Amazon Ads Report Analyzer provides PDF snapshots that keep reviews organized.

• Review recommendations by campaign or ad group before acting.
• Assign cleanup tasks to team members for accountability.
• Use shareable performance snapshots to communicate findings with clients or partners.

When this matters

This type of term-level review matters most when an auto targeting group has enough data to show a clear pattern. In accounts with many broad or auto campaigns, the number of search terms can grow quickly, making manual checks time-consuming without a structured classification.

It is also useful when one targeting group appears to drag down overall ROAS. By isolating the terms that spend without converting, you can make smaller, evidence-based negative keyword moves instead of pausing an entire group.