Write for AI Fan-Out: Why best, reviews, comparisons and the current year drive ChatGPT citations

AI “citations” aren’t neutral — they’re shaped by the exact words the model quietly appends when it goes to look things up.

Someone analyzed ~5 million ChatGPT fan-out queries and published what ChatGPT is adding to its internal searches:

- **“best” — 15.33% of queries**
- **“reviews” — 6.84%**
- **current year (2026) — 5.44%**
- **“top” — 5.24%**
- **“comparison” — 4.48%**
- **“vs” — 4.27%**

Once you see that, a lot of the “why does ChatGPT keep citing *those* sites?” stuff makes more sense:

- Listicles + affiliate pages dominate because the model is literally searching **“best [thing]”** behind the scenes.
- G2 / Gartner / Clutch / Forbes show up constantly because it’s explicitly pulling **reviews** as validation signals.
- Updating pages boosts citation odds because it appends the **current year** to ~5% of searches — freshness becomes a direct factor.

**Practical implication:** content that naturally includes **“best X”**, review-style framing, **comparison tables**, and the **current year** can pull disproportionate AI citation volume. Not as keyword stuffing — but because it matches how the AI actually searches.

Write for **AI fan-out queries**, not just Google’s primary keyword.

Credit to **Tomek Rudzki** and **Peec AI** for the data.