CITARA INSTITUTE · REPORT

Citara AI Visibility Index Method before ranking.

The Citara AI Visibility Index is a planned Citara measurement system with a defined sample, fixed prompt or assessment framework, repeatable rules and visible limitations. Results are published only when the method and aggregation support responsible interpretation.

Direct answer

The Citara AI Visibility Index is a planned Citara measurement system with a defined sample, fixed prompt or assessment framework, repeatable rules and visible limitations. Results are published only when the method and aggregation support responsible interpretation.

Author: Thorsten KellerUpdated: 2026-07-30

Measurement dimensions

What the report actually observes.

Model accessibility, business comprehension, category relatability, recommendation coverage, citation diversity, competitive share, evidence gaps and change over time.

01

Access and context

Defined fields, fixed assessment rules and traceable sources.

02

Recommendation and competition

Defined fields, fixed assessment rules and traceable sources.

03

Evidence and change

Defined fields, fixed assessment rules and traceable sources.

Methodology

Every release must explain how it can be repeated.

Date, models and versions, country, language, prompt set, sample, scoring, repeatability rules, limitations and data type are documented visibly.

FieldRequirement
Research frameDate, models, country and language
SampleDefinition, size and exclusion rules
MeasurementPrompt set or assessment, scoring and repetition
TransparencyObserved, inferred or customer-provided
LimitationsUncertainty, coverage and aggregation threshold

Privacy

No identifiable confidential customer cases in public benchmarks.

Sectors and groups below the minimum aggregation threshold are suppressed. Private customer documents, quotations and precise performance figures are not used publicly.

Frequently asked questions

Direct answers before the next step.

Is the report already published?+

The methodology page is live; results follow only with a stable method and sample.

Which models are tested?+

Each release lists models and versions where available.

How are prompts selected?+

Through a documented buyer, category or readiness logic.

How are small samples handled?+

Results below the aggregation threshold are not published.

Can the measurement be repeated?+

The prompt set, rules and time frame are documented for repetition.