Executive brief
Stage: InstrumentedA word-level decision engine that aggregates thousands of search-term queries into 1-, 2-, and 3-gram patterns, so one fix (killing the word 'free') applies everywhere instead of getting buried in noise no human can review manually.
Mandate this when
Mandate this once search volume exceeds roughly 1,000 terms/month and manual search-term review has stopped scaling — waste patterns are repeating month after month because one-off negatives don't generalize.
What breaks without it
Search term reports in large accounts are unmanageable — manual review doesn't scale past a few hundred queries, so high-waste word patterns stay hidden and negative lists grow reactively instead of systematically, while PMax runs with minimal negatives and high waste.
What it changes
What it takes
1-2 weeks with a PPC Manager. Needs 1,000+ search terms/month, working conversion tracking, clear CPA/ROAS targets, and CRM access for down-funnel validation.
Where AI fits
Not an AI-run system — the value is aggregation math (n-grams) that turns thousands of individually-invisible queries into a handful of word-level decisions, then feeds those decisions straight into the negative-keyword operating system (play_020) as a continuous loop.
N-Gram Analysis for Search Term Optimization
Break search queries into word patterns to find hidden waste and scale what converts — at the word level, not just the query level.
Goal: Build a systemized decision engine that steers Search + PMax at the word level and continuously reduces waste
Complexity
Medium
Tools
6
Context
The Problem
Search term reports in large accounts are unmanageable. Thousands of queries make it impossible to spot patterns manually. One-off negatives don't scale, so waste patterns repeat month after month.
- Manual review doesn't scale beyond a few hundred queries.
- High-waste word patterns stay hidden across many terms.
- Negative lists grow reactively, not systematically.
- Valuable word patterns get buried in noise.
- PMax campaigns run with minimal negatives and high waste.
A single word like "free" can drive thousands in waste across hundreds of queries. N-gram analysis surfaces patterns so you act once and fix them everywhere.
Resolution
The Solution
- Export search terms (last 90 days, Search + PMax).
- Run 1-gram analysis to identify zero-conversion words.
- Filter for 0 conversions and >150 clicks.
- Add top 10 negatives (validated) at account level.
- Log decisions.
- Use 1-, 2-, and 3-grams to aggregate performance at the word/phrase level.
- Apply decision thresholds by clicks, conversions, and CPA.
- Use longer lookback windows with broad + Smart Bidding.
- Run unified Search + PMax n-gram analysis (since March 2025).
- Layer analysis: check 2-grams and 3-grams before excluding 1-grams.
The goal is a continuous decision engine that feeds play_020 and keeps Search + PMax clean without manual overload.
Expected Metrics
-20-35%
Wasted spend reduction
-70-85%
Time spent on search term review
+200-500%
Negative keyword coverage
10-30 per cycle
New keyword ideas discovered
-10-25%
Cost per conversion
Traditional N-Gram Usage vs Mazorda
Objective
Traditional
One-off cleanup
Our Approach
Continuous decision engine
Data basis
Traditional
Google Ads conversions
Our Approach
CRM pipeline and revenue signals
Scope
Traditional
Search-only
Our Approach
Search + PMax unified
Tooling
Traditional
Single script or UI
Our Approach
Hardened scripts + play_020 integration
Cadence
Traditional
Ad-hoc
Our Approach
Weekly/monthly by spend tier
Outcomes
Traditional
Lower CPA
Our Approach
Higher qualified pipeline
| Aspect | Traditional | Our Approach |
|---|---|---|
| Objective | One-off cleanup | Continuous decision engine |
| Data basis | Google Ads conversions | CRM pipeline and revenue signals |
| Scope | Search-only | Search + PMax unified |
| Tooling | Single script or UI | Hardened scripts + play_020 integration |
| Cadence | Ad-hoc | Weekly/monthly by spend tier |
| Outcomes | Lower CPA | Higher qualified pipeline |
Tools & Data
Required (Minimum Viable)
Recommended (Scale)
Industry Benchmarks
| Metric | Benchmark | Source |
|---|---|---|
| Wasted spend in unoptimized B2B SaaS accounts | 57% average, 73% median | Aimers (2025) |
| Share of budget wasted without negative strategy | 15-30% of budget | groas (2025); PostAffiliatePro (2025) |
| Waste reduction from n-gram negatives | 25-35% immediate reduction | groas (2025) |
| Manual search term review time | 10-15 hours/week per manager | Negator (2025) |
| Time savings with automation | 2-3 hours/week | Negator (2026) |
Team Responsibilities
| Role | Responsibility |
|---|---|
| PPC Manager | Run analysis, validate findings, implement negatives, maintain decision log. |
Failure Patterns
| Pattern | What Happens | Why | Prevention |
|---|---|---|---|
| Tool mislabels targets | Core target phrases get flagged as negatives. | Tools rely on shallow conversion signals. | Validate against CRM-qualified outcomes before negating. |
| Over-pruned negatives | Conversions drop after aggressive exclusions. | Exact-match negatives block winning queries. | Use minimum thresholds and layered 2-gram/3-gram checks. |
| Script incompatibility | Old scripts fail in new Ads Scripts experience. | Deprecated versions not updated. | Use updated Nils Rooijmans scripts and test environments. |
| Search-term burnout | Manual review consumes 10-15 hours/week. | No automation or pattern analysis. | Automate n-gram extraction and batch triage. |
| Negative neglect in PMax | PMax runs with few or zero negatives. | Teams ignore PMax search term visibility and limits. | Run unified Search + PMax n-gram analysis and apply campaign-level negatives. |
ICP Fit Notes
Best fit
- •Accounts with 1,000+ search terms/month.
- •Broad/phrase match heavy accounts.
- •Lead gen with high non-commercial query volume.
- •Agencies managing multiple accounts.
Also works for
- •B2B SaaS with high waste from low-intent terms.
- •Any account spending >$5K/month on search.
Insight: First-time analysis often uncovers 15-20% waste that has compounded for months.
Implementation Checklist
Week 1: Setup
- Export search terms report (last 90 days, Search + PMax).
- Set up n-gram analysis method (script/tool/manual).
- Define thresholds for clicks and conversions.
- Run first n-gram analysis.
- Create decision log spreadsheet.
Week 2: Action
- Identify top 10-20 negative candidates.
- Validate each against converting query overlap and CRM outcomes.
- Add negatives at appropriate match type and level.
- Document decisions with rationale.
- Set up automated script for ongoing runs.
Ongoing
- Weekly/bi-weekly quick review (high spend).
- Monthly deep dive for high-CPA and scale opportunities.
- Quarterly review of negative impact and list hygiene.
FAQ
Sources
- 1. Mazorda operator archive (40+ years combined): patterns from systems we built, fixed, and retired across B2B SaaS GTM.
- 2. GoogleAdsOpenResearch — Advanced N-Gram Analysis for Google Ads (2024)
- 3. WordStream — Keyword Optimization Script (2024)
- 4. Adalysis — Manage search terms and n-grams (2024-2026)
- 5. Optmyzr — Search Query and Keyword Management (2024-2025)
- 6. Aimers — Google Ads for SaaS (2025)
- 7. groas — Negative Keyword Limits (2025)
- 8. PostAffiliatePro — Negative Keywords Guide (2025)
- 9. Negator — Automating Search Term Review (2025-2026)
- 10. Search Engine Land — PMax Search Terms visibility (2025)
- 11. Google Ads Help — Smart Bidding with broad match (2026)
- 12. Nils Rooijmans — Updated N-Gram Scripts (2025)
- 13. Paid Search Podcast — Negative keyword usage report (2025)
- 14. PEMAVOR — Keyword N-Gram Analyzer (2025)
- 15. Karooya — Keywords & Negative Keywords (2025)
- 16. Reddit r/PPC — N-gram discussions (2024-2025)
- 17. Lunio — PMax N-Gram Analysis (2024)
When NOT to Use
- •Very low-volume accounts (<500 search terms/month).
- •Early-stage Smart Bidding (first 2-4 weeks).
- •Brand-only campaigns.
- •Exact match only campaigns.
- •Hyper-narrow B2B niches with tiny volume.
- •Severe search term blindness (<10-20% visibility).
- •New accounts with <60 days data.
Tools & Tech