Fact Density

Low fact densityFact density describes how many concrete, verifiable pieces of information a text contains relative to general statements. It is an editorial quality criterion, not an official Google metric.Open glossary entry → shows up as many cliches, general statements and marketing language combined with few numbers, definitions, examples or data points. High fact density does not mean overloading every sentence with numbers; it means the text carries more concrete meaning.

Elements that create fact density include:

• definitions and time frames,
• numbers and proprietary data,
• concrete examples and comparisons,
• process steps, criteria and checklists,
• before-and-after comparisons.

A simple rule: delete any statement that sounds interchangeable, or make it more specific. Instead of Our solution saves a lot of time, Processing time drops from 12 to 5 minutes in the sample process is far more meaningful. Fact-dense content is more useful for readers and easier for machines to evaluate.

Why fact density matters for AI answers #

Language models extract and recombine facts. A page that states concrete numbers, dates, names and thresholds gives a model quotable material; a page of vague claims ("many users", "significantly faster") gives it nothing to cite. High fact density is one of the strongest predictors of being referenced in AI answers.

Raising fact density without hurting readability #

Replace vague quantifiers with real values, add units and reference dates ("as of August 2026"), name sources, and compress filler paragraphs. Tables and definition lists carry facts efficiently. The goal is not academic prose — it is that every paragraph contains at least one statement worth extracting.