Position-Adjusted Word Count (PAWC)
The composite metric from the Princeton GEO study that combines brand mention volume with positional weight — higher score means more prominent AI coverage.
Plain Language Definition
Position-Adjusted Word Count is a visibility score that counts how many words AI dedicates to discussing your brand, giving extra weight to those that appear earlier in the answer. It combines the quantity of brand coverage with the positional quality of where that coverage appears. The Princeton GEO study used PAWC as its primary metric for measuring the impact of content optimization tactics.
Technical Definition
Quantitative visibility metric measuring total word count attributed to the source brand in AI-generated text, weighted by a linear or logarithmic positional decay function that amplifies the score contribution of tokens appearing earlier in the generated sequence.
Why This Matters for AI Search Visibility
PAWC is the primary empirical metric from the Princeton GEO study that demonstrated specific content techniques produce measurable, reproducible citation improvements. Tracking PAWC provides a single composite number that captures both how much and how prominently AI covers your brand.