Stopwords are high-frequency terms that add little intent value. Managing them can reduce query noise and improve precision for the meaningful terms that remain.
Prerequisite: Review the Get Started articles before using this article, especially the analytics workflow and the guidance on cookies and session interpretation.
When to Use This Lever/Report
Use Stopwords when generic filler words reduce result quality for important terms.
- Queries include repeated common terms with little discriminative value.
- Precision drops because broad tokens overwhelm intent-bearing terms.
- You need tighter relevance behavior for domain-specific search tasks.
Do not remove high-intent domain terms that users rely on for precision.
How to Configure or Analyze
- Confirm targeted search fields are tokenized full-text fields.
- Add stopwords gradually through manual entry or TXT upload.
- Use one term per line for uploads and track list ownership.
- Publish changes and keep rollback options available.
- Review list quality periodically to remove terms that became meaningful over time.
How to Validate Impact in Analytics
Validate stopword changes against targeted query sets:
- Searches with No Click: Confirm noisy queries get more useful outcomes.
- Average Click Position: Confirm useful results move upward.
- No Result patterns: Confirm stopword changes do not introduce new gaps.
If quality regresses, revert recent additions and reintroduce smaller sets after review.
Review Schedule: Review this analysis on a regular schedule, such as weekly for active programs and monthly for stable programs. Keep a short change log with the date, owner, target query or feature, and expected outcome. Use the same scope and date ranges each cycle so you can connect metric changes to specific edits.
When to Ask Your Developer or Web Team
Escalate when you need field-tokenization specifics, platform limits, or environment-specific caveats beyond marketer workflow scope. Use Stopwords as the canonical deep reference.