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Negative Keywords: The Most Underused Lever in Amazon PPC

In most Amazon PPC audits, negative keyword coverage is the single biggest source of recoverable waste. This guide explains how to find wasted spend, build a negative strategy, and implement it at the right level.

The Uncomfortable Truth About Your Auto Campaigns

Run a search term report on your auto campaigns from the last 90 days. Filter for spend with zero conversions. In most accounts we audit, this number is between 18% and 35% of total auto spend — money gone directly to Amazon's revenue with zero return to you.

That's not a bidding problem. That's a negative keyword problem.

Three Types of Negatives You Need

1. Irrelevance Negatives

Search terms that are simply unrelated to your product. If you sell premium yoga mats and you're showing for "cheap yoga mat under 500," "cheap" is an irrelevance negative. If you sell a premium water bottle and you're showing for "plastic water bottle," "plastic" is an irrelevance negative.

These are the easiest to find and the highest-impact to add. They usually represent the largest share of zero-conversion spend.

2. Competitor Negatives (Selective)

Competitor brand terms are a judgment call. If your product genuinely competes head-to-head on quality and price, showing on competitor searches can work. If your CVR on competitor terms is 30–50% below your brand term CVR, you're paying for visibility that doesn't convert — add the competitor names as negatives and redirect that budget to your own branded terms.

3. Internal Cannibalization Negatives

The most overlooked type. When your broad or phrase campaigns bid on exact match terms that also appear in your exact campaigns, you're in an internal auction with yourself, splitting impressions and inflating your own CPC. The fix: add your exact match keywords as negatives in your broad and phrase campaigns so traffic flows through the right tier.

"A Bidvista audit on a ₹3L/month account found 380+ negative keyword gaps. Adding them in the first two weeks recovered ₹40,000/month in wasted spend — before any bid changes were made."

Where to Add Negatives: Campaign vs. Ad Group vs. Account Level

Most sellers add negatives at campaign level and stop there. Professional accounts use all three levels strategically:

  • Account-level negative lists — For terms that should never trigger your ads regardless of product (adult content, DIY instructions when you sell finished goods, etc.). Create a shared negative list in Portfolio settings and apply it to all campaigns.
  • Campaign-level negatives — For terms irrelevant to this specific product category. If a campaign covers kitchen appliances, "garden tools" goes here.
  • Ad group-level negatives — For preventing internal cannibalization between match types within a campaign.

Pre-Load Negatives Before You Spend

The biggest waste in Amazon PPC happens in the first 2–4 weeks of a campaign — before you have enough data to know what's irrelevant. The fix is building a pre-load negative list from keyword research before you launch.

For a product in any category, you can identify 100–200 negative terms just from your keyword research and category knowledge. Load these before day one. You'll save weeks of irrelevant spend data collection.

Weekly Negative Keyword Routine

  • Pull the Search Term Report every Monday covering the previous 7 days
  • Filter for spend above ₹50 with 0 conversions — these are immediate add candidates
  • Filter for spend above ₹200 with 1 conversion and ACOS above 3× target — evaluate for negative or bid reduction
  • Add all confirmed negatives at the appropriate level (campaign or account)
  • Log every addition with the rationale in your weekly action log

Match Types for Negatives

Use negative exact for specific search terms you've confirmed are irrelevant (e.g. "yoga mat pink" when you only sell grey). Use negative phrase for entire topic exclusions (e.g. "second hand", "used", "refurbished" if you only sell new). Don't use negative broad — it's too aggressive and will exclude variations you didn't intend.


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