AIQ Score

AIQ v1 publishes two deliberately separate recommendation signals. Overall AIQ combines Best + Most affordable + Easiest to set up. These three core buyer intents determine the category’s Overall rank, weekly movement, and overall recognition.

Rising AIQ measures only the Rising question. It uses the same repeated-query protocol, assistant and regional weights, reciprocal-position formula, and 1–100 normalization, but it does not contribute to Overall AIQ. A strong Rising result therefore cannot raise or lower a product’s Overall position.

Rising is a question-based measure of which newer or emerging tools assistants recommend. It is not an independently verified product-age ranking; product age and launch status are not yet used as eligibility filters. Any future eligibility rule will be versioned and documented before it affects a published edition.

AIQ is not a product-quality or customer-satisfaction score. It does not evaluate feature depth, reliability, usability, support quality, retention, revenue, or market share. A highly recommended product can still be a poor fit for a specific buyer, and a strong product can receive a lower AIQ when assistants do not recommend it prominently.

AIQ does not reveal model training data or hidden influence. Cooper measures the answers and citations returned during a defined snapshot. A cited page is part of the observable evidence trail, but it does not prove why a model selected a product or whether that source appeared in the model’s training data.

AIQ is not a universal measure of AI visibility. It covers the published assistants, questions, category, company scope, scoring version, and week. Recommendations generated for other prompts, regions, languages, user histories, or untracked assistants are outside that score.

AIQ cannot be purchased or edited by a vendor. Profile ownership, subscription status, advertising, sponsorships, and commercial relationships are excluded from collection, scoring, tie-breaking, and publication. Claiming a profile changes descriptive product information only.

Assistant responses are probabilistic. Repeating an identical prompt can produce a different ordering or set of products. A Cooper edition is therefore a time-bound observation, not a guarantee that every user will receive the same answer. Weekly repetition makes directional changes more useful than treating one response as permanent.

Controlled web sessions do not reproduce every personal consumer experience. Cooper uses the subscribed consumer interfaces and measured geography, but intentionally excludes prior conversation history and personal account context. Individual users may still encounter personalization, interface experiments, account settings, or model routing that differs from the controlled session.

Evidence availability varies by assistant. Providers expose different citation formats and levels of source detail. Citation counts are useful for examining the returned evidence trail, but they are not directly comparable to model confidence and cannot establish causation.

Coverage is bounded by the current taxonomy and query set. Newly launched products, ambiguous names, uncommon market language, and use cases outside the published query matrix may be underrepresented until they can be verified and incorporated into a versioned measurement scope. Rising reflects assistant recommendations for emerging tools, but it does not independently verify product age or launch date.

Public editions do not expose every underlying observation. Cooper publishes the methodology, aggregate results, coverage, source summaries, and correction history needed to interpret AIQ while retaining raw queries and anti-manipulation controls for internal QA and controlled audits. The full boundary is documented under Operational Confidentiality.

AIQ v1 is Cooper’s first public scoring version. It defines the three-question Overall score and the standalone Rising score as separate scopes under the same collection, weighting, and normalization rules.

Every current and archived board identifies its scoring version. Values should only be compared when category, question scope, measurement window, and scoring version are compatible.

Future scoring versions may publish query-level variance, consensus strength, and confidence indicators from the repeated observations already collected, helping readers distinguish durable recommendation patterns from short-lived answer variation.

Cooper also intends to expand coverage across additional assistants, buyer contexts, company segments, regions, and languages when each addition can be collected consistently and supported by enough historical data to be interpreted responsibly.

Evidence reporting will become more granular as source classification improves, including clearer separation between vendor-controlled pages, independent editorial sources, communities, documentation, and marketplace listings.

Any material change to questions, assistant weights, normalization, or coverage boundaries will receive a new methodology version. Existing archive editions will retain the rules under which they were originally published.