How are negative keyword candidates ranked?
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Quick answer
Negative keyword candidates are ranked based on how efficiently each Amazon Ads search term performs, using signals like spend, clicks, sales, cost per acquisition (CPA), and other performance data. By looking at the relationship between costs and results, Todoza prioritizes which terms may be wasting budget and should be considered for negative targeting.
Finding the right keywords to negate is essential for Amazon advertisers who want to stop budget loss from underperforming search terms. But how does a tool decide which candidates deserve your attention first? Let’s look at how ranking works in a real-world Amazon Ads workflow.
The Key Metrics Used for Ranking
At the core, Todoza reviews several important metrics from your search term performance reports. These include:
- Ad Spend: How much money has been allocated to each search term over a period.
- Clicks and Impressions: Gauges engagement and reach.
- Sales and Orders: Tracks whether clicks translate into actual sales.
- CPA (Cost Per Acquisition): Measures the efficiency of spend in driving conversions.
When a search term accumulates high spend or lots of clicks but results in few or no sales, it rises as a negative keyword candidate. CPA and related indicators help determine which terms are inefficient.
How Todoza Ranks Negative Candidates
Todoza’s approach doesn’t rely on rigid thresholds. Instead, it continually analyzes campaign data to surface search terms that underperform relative to your goals. The tool considers trends and context like recent activity, conversion rates, and how aggressively a term spends versus its sales output. These insights allow you to review and approve negative targets—no changes are made automatically, so you have full control over the process. For users managing multiple accounts or marketplaces, products like the Amazon Negative Keyword Tool by Todoza centralize this ranking for efficiency.
When this ranking method matters
Dynamic negative keyword ranking becomes crucial when your campaign has significant search term diversity or budgets at stake. For teams or agencies handling large sets of products and keywords, surfacing top problem areas saves time and helps protect ad spend. Workflows that prioritize candidates by data—not guesswork—support smarter and more efficient Amazon Ads management.
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Ranking negative keyword candidates is an essential step in fine-tuning Amazon Ads for profitability, especially when focusing on product-level CPA. Want to understand when CPA-based decisions outweigh ROAS? See more about these strategies in our main guide on Amazon Ads Product-Level CPA.