Information gain
Useful new value a page adds beyond what existing sources already say.
What is Information gain?
Information gain can come from original data, first-hand experience, clearer synthesis, unique examples, or a better decision framework. Repeating the consensus with different wording gives answer engines little reason to prefer a new source.
A company publishes anonymized conversion benchmarks from 8,000 campaigns instead of another generic checklist.
Why it matters for AI visibility
AI answers can shape awareness and buying decisions before a person visits a website. Understanding information gain helps teams connect what a model says with the prompts, sources, and technical signals that influenced the result. The useful next step is to observe the evidence, compare it over time, and act on the specific gap.
How to measure or use it
- Define the scope. Choose the relevant market, prompts, models, locations, and time window.
- Keep the evidence. Save the complete answer, its citations, and the page or claim being evaluated.
- Compare patterns. Look for repeated movement across prompts and models instead of reacting to one response.
- Take a specific action. Improve the owned page, correct a claim, earn third-party inclusion, or create better evidence.