Content tactics: what helps and what hurts
Based on the foundational Princeton GEO research, which showed visibility gains on the order of ~40% from structured content changes, here's what the data says.
Princeton GEO methods, visibility impact
| Method | Visibility boost | How to apply |
|---|---|---|
| Cite sources | +40% | Link to studies, official data, experts |
| Statistics | +37% | Concrete numbers, not vague claims |
| Quotations | +30% | Attributed quotes from authorities |
| Authoritative tone | +25% | Confident, evidence-based writing |
| Improve clarity | +20% | Short sentences, clear structure |
| Technical terms | +18% | Precise terminology where relevant |
| Unique vocabulary | +15% | Distinct phrasing, not generic |
| Fluency | +15–30% | Natural, readable prose |
| Keyword stuffing | −10% | Hurts visibility; avoid |
✓What helps
📊 Statistics & data
Concrete numbers are easier to extract and cite than vague claims. "Visibility gains of ~40%" beats "much better."
💬 Quotes & citations
Attributing claims to studies, experts, or official data strengthens E-E-A-T and gives the model something to reference.
🔤 Fluency & clarity
Well-written, scannable content (short sentences, clear headings, one idea per paragraph) is selected more often.
🏗️ Answer blocks
Heading-as-question → 40–60 word nugget → evidence. This pattern matches how models synthesize answers.
✕What hurts
🔁 Keyword stuffing
Repeating target phrases unnaturally has been shown to *decrease* performance in LLM retrieval. Models prefer natural language.
🧱 Walls of text
Long unbroken paragraphs make extraction hard. Break content into scannable blocks, one idea each.
📢 Promotional copy
Thin or purely promotional content loses out to depth and evidence. LLMs prioritize content that's useful to the asker.
🚫 JS-only content
If your core content only appears after JavaScript runs, ChatGPT's crawler (and others) will never see it.
💡Example on this site