Negative Keywords: The Design Philosophy for Systematic Waste Elimination

Introduction

Every click costs money. But not every click leads to a sale. The difference between profitable and unprofitable Amazon PPC campaigns often comes down to one overlooked tactic: negative keywords.

While most sellers focus on finding new keywords to target, experienced advertisers know that excluding the wrong traffic is equally—if not more—important. A well-designed negative keyword strategy can reduce wasted spend by 20-40% without sacrificing impressions or sales.

This guide introduces a systematic design philosophy for negative keywords: the 3-type framework, exclusion criteria, hierarchical application, and maintenance schedules that prevent over-exclusion.

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Table of Contents

1. What Are Negative Keywords?
2. Why Negative Keywords Matter
3. The 3-Type Framework
4. Exclusion Targets and Criteria
5. Hierarchical Design
6. Weekly Maintenance Workflow
7. Avoiding Over-Exclusion
8. Case Study: 35% Waste Reduction
9. FAQ
10. Summary and Next Steps

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What Are Negative Keywords?

Negative keywords are terms you exclude from triggering your ads. When a search query contains a negative keyword, your ad will not appear—saving you from irrelevant clicks.

Example:

• Product: Premium leather wallet (£45)
• Negative keywords: cheap, free, DIY, knockoff, replica

If someone searches "cheap leather wallet," your ad won't show—protecting your budget from low-intent traffic unlikely to convert at your price point.

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Why Negative Keywords Matter

1. Direct Cost Savings

Before negatives:

• 1,000 clicks
• 120 sales
• CVR: 12%
• CPC: £0.80
• Ad spend: £800
• ACoS: 25%

After negatives (excluding 200 irrelevant clicks):

• 800 clicks
• 120 sales (same)
• CVR: 15%
• CPC: £0.80
• Ad spend: £640
• ACoS: 20%

Result: Same sales, £160 saved (20% reduction in ad spend)

2. Improved Quality Score

Amazon's algorithm rewards campaigns with high relevance. By excluding mismatched queries, you improve:

• Click-through rate (CTR)
• Conversion rate (CVR)
• Overall campaign quality

This leads to lower CPCs over time as Amazon favors your ads.

3. Budget Reallocation

Money saved on wasted clicks can be reinvested in:

• Higher bids on profitable keywords
• Testing new products
• Expanding to Sponsored Brands or Display

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The 3-Type Framework

Negative keywords come in three match types, each with distinct use cases:

1. Negative Exact Match

Definition: Blocks only the exact phrase, character-for-character.

Example: Negative exact "leather wallet"

• Blocked: "leather wallet"
• Not blocked: "leather wallets", "brown leather wallet", "leather wallet men"

When to use:

• You want to block a specific phrase but allow variations
• Surgical precision required (rare)

Typical usage: < 5% of all negatives

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2. Negative Phrase Match

Definition: Blocks queries containing the phrase in that order, but allows additional words before or after.

Example: Negative phrase "leather wallet"

• Blocked: "leather wallet", "brown leather wallet", "leather wallet for men"
• Not blocked: "wallet leather", "leather wallets", "leather men wallet"

When to use:

• You want to block a concept but allow singular/plural variations
• Balancing precision and coverage

Typical usage: 60-70% of all negatives

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3. Negative Broad Match

Definition: Blocks queries containing all terms in any order.

Example: Negative broad "leather wallet"

• Blocked: "leather wallet", "wallet leather", "brown leather mens wallet"
• Not blocked: "leather purse" (missing "wallet"), "wallets leather" (plural)

When to use:

• You want maximum coverage
• The term is clearly irrelevant in any combination

Typical usage: 25-35% of all negatives

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Match Type Decision Tree

Is the term completely irrelevant (e.g., "free")?
└─ YES → Negative Broad

Does the term have some relevance but in wrong context?
└─ YES → Negative Phrase

Do you only want to block one exact variation?
└─ YES → Negative Exact (rare)

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Exclusion Targets and Criteria

Category 1: Irrelevant Products

What to exclude:

• Products you don't sell
• Adjacent categories
• Competitor brands (if you're not competitive)

Examples:

• You sell yoga mats → Exclude: "yoga pants", "yoga blocks", "yoga DVD"
• You sell men's wallets → Exclude: "women", "ladies", "girls"

Criteria: Exclude immediately (no waiting for data)

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Category 2: Wrong Purchase Intent

What to exclude:

• Research/educational queries
• Free-seeking behavior
• Non-buying intent

Examples:

• "how to make a wallet"
• "wallet tutorial"
• "free wallet"
• "wallet template"
• "DIY wallet"

Criteria: Exclude after 10 clicks with 0 conversions

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Category 3: Mismatched Attributes

What to exclude:

• Wrong size, color, material, or spec
• Price qualifiers that don't match your product

Examples:

• You sell premium (£50+) → Exclude: "cheap", "budget", "under £20"
• You sell small wallets → Exclude: "large", "oversized", "big"
• You sell leather → Exclude: "vegan", "fabric", "nylon"

Criteria: CVR < 2% AND Clicks ≥ 10

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Category 4: Low-Value Queries

What to exclude:

• Queries with terrible CVR despite relevance
• High-CPC, low-ROI terms

Examples:

• "best wallet" (informational, low intent)
• "wallet review" (research phase)
• Generic terms with poor performance

Criteria: CVR < 2% AND Clicks ≥ 10 AND ACoS > 2× target

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Hierarchical Design

Negative keywords can be applied at three levels. Apply them at the highest relevant level to minimize management overhead.

Level 1: Campaign Level

When to use:

• The term is irrelevant to ALL products and ad groups in the campaign
• Broad, category-wide exclusions

Examples:

• Campaign: "Men's Wallets" → Negatives: women, ladies, girls, kids
• Campaign: "Premium Leather Goods" → Negatives: cheap, budget, knockoff

Benefit: Apply once, protects entire campaign

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Level 2: Ad Group Level

When to use:

• The term is irrelevant to specific ad group but not the entire campaign
• Product-specific exclusions

Examples:

• Ad Group: "Bifold Wallets" → Negatives: trifold, money clip, card holder
• Ad Group: "Black Wallets" → Negatives: brown, tan, red, blue

Benefit: More granular control, allows other ad groups to still target those terms

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Level 3: Product (ASIN) Level

When to use:

• The term is irrelevant to ONE specific product in a multi-ASIN ad group
• Rarely used (consider restructuring instead)

Benefit: Maximum precision (but high management cost)

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Hierarchical Application Strategy

1. Start at Campaign Level for broad exclusions (week 1)
2. Add Ad Group Level negatives after 2-4 weeks of data
3. Use Product Level only for special cases (avoid if possible)

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Weekly Maintenance Workflow

Negative keyword management is not a one-time task. Implement this weekly routine:

Step 1: Download Search Query Performance Report (SQPD)

• Go to Seller Central → Reports → Advertising Reports
• Select "Search Term" report
• Date range: Last 7 days

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Step 2: Apply Filters

Primary filter:

• Orders = 0
• Clicks ≥ 10

Secondary filter:

• Orders > 0 BUT CVR < 2%
• Ad Spend ≥ £5

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Step 3: Classify and Exclude

For each flagged query:

1. Irrelevant product? → Negative Broad
2. Wrong intent? → Negative Phrase
3. Mismatched attribute? → Negative Phrase or Broad
4. Borderline (5-9 clicks, no sales)? → Add to watchlist, revisit next week

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Step 4: Bulk Upload

Use Amazon's bulk upload feature:

1. Prepare CSV with: Campaign Name, Ad Group Name (if applicable), Negative Keyword, Match Type
2. Upload via Campaign Manager → Bulk Operations

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Step 5: Document Changes

Maintain a log (spreadsheet):

Date	Campaign	Negative Keyword	Match Type	Reason	Clicks Wasted
2025-01-20	Men Wallets	cheap	Broad	Price mismatch	15
2025-01-20	Men Wallets	DIY	Broad	Wrong intent	8

Why? If you over-exclude and need to reverse a decision, you'll know why you added it.

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Avoiding Over-Exclusion

Negative keywords are powerful, but over-exclusion can kill your campaigns. Watch for these red flags:

Warning Sign 1: Impressions Dropping Sharply

If impressions drop >20% after adding negatives, you've likely blocked too much.

Solution: Review recent additions, remove over-broad negatives.

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Warning Sign 2: Excluding Terms with Sales

Bad practice:

• "wallet men" → 50 clicks, 2 sales, CVR 4%, ACoS 30% (your target is 25%)
• Decision: Exclude because ACoS is high

Why it's wrong: CVR is decent (4%). Lower bid instead of excluding entirely.

Good practice: Only exclude when CVR < 2% AND significant spend wasted.

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Warning Sign 3: Too Many Exact Match Negatives

If 50%+ of your negatives are Exact Match, you're micro-managing unnecessarily.

Solution: Consolidate into Phrase or Broad Match negatives.

Example:

• ❌ Negative Exact: "cheap wallet", "cheap wallets", "cheapest wallet"
• ✅ Negative Phrase: "cheap"

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The 10/2 Rule

Safe exclusion criteria:

• Clicks ≥ 10 AND CVR < 2%

If a term has <10 clicks, wait for more data. Exceptions:

• Obvious irrelevance (e.g., you sell shoes, query is "wallet")
• Brand registry violations

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Case Study: 35% Waste Reduction

Category: Home & Kitchen (Silicone Baking Mats)

Challenge: High ACoS (32%) driven by irrelevant traffic from broad match campaigns.

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Initial Audit (Week 0)

SQPD Analysis (30 days):

• Total queries: 487
• Queries with 0 orders: 312 (64%)
• Wasted spend: £485 out of £1,500 (32%)

Top wasted queries:

1. "silicone baking mat how to clean" (£45, 0 sales)
2. "cheap baking mat" (£38, 0 sales)
3. "baking mat vs parchment paper" (£32, 0 sales)
4. "DIY baking mat" (£28, 0 sales)

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Negative Keyword Strategy

Week 1: Campaign-Level Exclusions

Added 25 broad negatives:

• cheap, budget, discount, under £10
• DIY, homemade, tutorial, how to
• vs, versus, comparison, review

Result: Wasted clicks reduced by 18%

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Week 2-3: Ad Group-Level Exclusions

Analyzed ad group-specific poor performers:

• Ad Group "Standard Size" → Negatives: large, XL, oversized
• Ad Group "Premium" → Negatives: cheap, value pack, bulk

Result: Additional 10% waste reduction

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Week 4: Phrase Match Refinements

Added 40 phrase negatives based on specific poor-performing phrases:

• "how to clean"
• "how to use"
• "difference between"
• "parchment paper vs"

Result: 7% further reduction

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Final Results (Month 3)

Metric	Before	After	Change
Total Clicks	1,875	1,450	-23%
Sales	240	260	+8%
CVR	12.8%	17.9%	+40%
Ad Spend	£1,500	£975	-35%
ACoS	32%	20%	-12 pts

Key learnings:

1. "How to" queries accounted for 12% of wasted spend
2. Price qualifiers ("cheap", "budget") had <1% CVR
3. Comparison queries ("vs", "versus") had 3% CVR but required very high bids

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FAQ

Q1: How many negative keywords should I have?

A: There's no fixed number. A healthy campaign might have 50-200 negatives depending on niche competitiveness. Focus on impact, not count.

Q2: Can I use the same negatives across all campaigns?

A: Yes, for broad irrelevancies (e.g., "free", "DIY"). But product-specific negatives should be tailored to each campaign.

Q3: Should I add negatives to Auto campaigns?

A: Absolutely. Auto campaigns benefit even more from negatives since targeting is less controlled.

Q4: How often should I review negatives?

A: Weekly during setup phase (Month 1-3), then bi-weekly or monthly for maintenance.

Q5: Can I remove a negative keyword once added?

A: Yes. Go to Campaign Manager → Negative Keywords tab → Delete. If a term becomes relevant later (e.g., you launch a budget line), remove it.

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Summary and Next Steps

Key Takeaways

• ✅ Negative keywords eliminate wasted spend by blocking irrelevant traffic
• ✅ 3-Type Framework: Use Broad for maximum coverage, Phrase for precision, Exact rarely
• ✅ Exclusion Criteria: CVR < 2% AND Clicks ≥ 10 (the 10/2 rule)
• ✅ Hierarchical Design: Apply at Campaign level first, Ad Group second, Product rarely
• ✅ Weekly Maintenance: Review SQPD, exclude new waste, document changes
• ✅ Avoid Over-Exclusion: Don't exclude terms with decent CVR just because ACoS is high

Action Plan

1. Today: Download your last 30 days of SQPD
2. This Week: Identify top 20 wasted queries (0 sales, high clicks)
3. This Week: Add Campaign-level negatives for obvious irrelevancies
4. Next Week: Set up weekly SQPD review reminder
5. Month 1: Establish baseline negative keyword library (50-100 terms)

Automate Your Negative Keyword Management

Arctavia analyzes your search queries weekly, flags low-performing terms, and prepares negative-keyword suggestions based on your historical CVR and ACoS targets.

Explore Pricing or Learn About Search Query Optimization

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Related Resources

• Search Query Performance Report Deep Dive
• Match Types Explained: Exact, Phrase, Broad
• Auto Extraction Loop: Systematic Promotion & Exclusion
• Glossary: Negative Keywords

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Author Note: This guide is informed by analysis of 5,000+ Amazon PPC campaigns across UK and EU markets, collectively managing £2M+ in monthly ad spend.

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