While associations test open-ended recall to determine which brands an AI naturally surfaces for a given entity or query, relevance tests explicit recommendation through repeated binary queries. This separates passive memory recognition from direct commercial validation, measuring whether a model merely recognizes a brand in a general space or consistently endorses it across multiple sampled trials.