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Position bias is the tendency for users (and LLMs themselves) to give disproportionate attention and credibility to items listed first in a sequence. In AI-generated answers, the first brand mentioned receives more reader attention than the fifth brand mentioned — even when the AI does not explicitly rank its suggestions. This effect is well-documented in traditional search (users click the first result far more than the tenth) and carries over into AI answer consumption.

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Why it matters

Position bias means that average position is not just a vanity metric — it has real downstream impact on brand perception and consideration. A brand consistently mentioned in positions 1-3 receives materially more reader engagement than a brand consistently mentioned in positions 7-10. Moving from position 6 to position 3 can produce larger business impact than increasing mention rate by several percentage points.

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How it applies in practice

Cited tracks average position as a core metric precisely because of position bias. The Cited Index shows a median average position of 5.6 across all brands — roughly middle-of-pack. Top-decile brands achieve average position 3.3, placing them consistently in the high-attention zone where position bias works in their favor.