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Query archetype is a category of query structure that describes how a question is framed. Cited’s Query Gen V2 pipeline classifies generated queries into six archetypes: problem_first, context_specific, budget_anchored, comparison, recommendation_seeking, and feature_curious. Each archetype reflects a different way real customers ask questions, and each produces different brand visibility patterns.

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Why it matters

Different archetypes surface different brands. A problem-first query (“my skin gets oily by afternoon”) may mention different brands than a comparison query (“boat vs noise earbuds”) or a budget-anchored query (“affordable noise cancelling earphones”). A brand that dominates recommendation queries but is invisible on comparison queries has a specific content gap to fill. Archetype-level analysis reveals these gaps.

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How Cited uses it

Query Gen V2 generates queries across all six archetypes with target distribution weights (problem_first 25%, context_specific 20%, budget_anchored 15%, comparison 15%, recommendation_seeking 15%, feature_curious 10%). This ensures a brand’s prompt library covers the full range of customer question styles. Dashboard analytics support archetype-level filtering for precise visibility diagnostics.