What does the AI Discovery in Real Estate study measure?

The protocol is designed to evaluate agreement across supported AI providers, recommendation and visibility stability across repeated observations, source behavior, market and query differences, entity-resolution confidence, measured versus unavailable outcomes, and change over time.

Are findings published on this page?

No. This page documents the methodology and study protocol. Conclusions, benchmark claims, and market results are published only when completed stored observations meet AuthoritySignal Research privacy, suppression, provenance, and reproducibility rules.

Does the protocol claim causation or guarantee recommendations?

No. Provider observations are specific to the provider, query, market, and time. The protocol reports measured patterns and does not claim that an intervention caused a later visibility change or guarantee an AI recommendation.

AI Discovery in Real Estate: Provider Agreement, Recommendation Stability, and Source Behavior Across U.S. Markets

AuthoritySignal Research studies how AI systems discover, interpret, cite, compare, and surface real-estate professionals and organizations using transparent, repeatable measurement protocols.

This page documents a methodology and study protocol. It does not publish study conclusions, market findings, rankings, or benchmark results until completed stored observations meet the stated publication rules.

Study design

The protocol evaluates agreement across supported AI providers, recommendation and visibility stability across repeated observations, source and citation behavior, differences across markets and query types, entity-resolution confidence, measured versus unknown or unavailable outcomes, and changes over time.

AuthoritySignal preserves repeated observations over time so provider behavior, recommendation stability, source patterns, and changes can be evaluated longitudinally rather than from a single snapshot.

Evidence and interpretation limits

Provider observations are specific to the provider, query, market, and time. A missing, blocked, or unavailable field remains unknown or unavailable rather than becoming zero or a negative result. Submitted claims, verified evidence, provider observations, inferred readiness, and unresolved states remain separate evidence types.

The protocol reports descriptive measurements and does not claim that an intervention caused a later visibility change or guarantee an AI recommendation, citation, ranking, lead, or business outcome.