RESEARCH METHODOLOGY

AEO Research Methodology & Evidence Standard

This protocol defines how Charles Brian International will collect, classify, score and report AI visibility evidence. It is a public operating standard, not a claim that a benchmark has already been executed.

Enterprise team reviewing an AI visibility benchmark and evidence-led research

RESEARCH METHODOLOGY

Study Design Sequence

01

Define the decision

State the buyer decision, category boundaries, audience and commercial question before prompt collection begins.

02

Build the corpus

Create prompt families across discovery, comparison, risk, proof, implementation and procurement.

03

Freeze the protocol

Record surfaces, models, geography, dates, session conditions, repetitions and scoring rules.

04

Capture evidence

Preserve answers, citations, links, brand order, recommendation language, caveats and timestamps.

05

Review quality

Apply duplicate checks, adjudication rules, outlier handling and documented exclusions.

06

Publish limits

Report what the sample supports, what it does not support and what may change over time.

RESEARCH METHODOLOGY

Measurement Rules

Unit of analysis

An individual answer to a frozen prompt on a named surface at a recorded time.

Presence

Whether a defined entity appears, not whether the wording feels favorable.

Recommendation

Whether a brand is explicitly suggested for the use case, separated from incidental mention.

Framing

The strengths, limitations, risks and use-case fit attached to the entity.

Citation

A visible source or link captured with exact provenance and access date.

Stability

The degree to which results persist across controlled repetitions, reported without false precision.

RESEARCH METHODOLOGY

What This Page Proves, And Does Not

Evidence boundary

This page proves that a reporting method has been specified. It does not prove market performance, model preference, category leadership or any company score.

Next Useful Step

Request An AI Visibility Diagnostic

Choose one company, one competitive set and one revenue-critical buyer journey. We will identify the decision questions, representation gaps and evidence requirements that matter most.