Assigning search queries to labels — like intent categories — so they can be routed, mapped to content, and reported at scale.
Query classification is the task of assigning search queries to labels — commercial vs informational intent, industry categories, funnel stages — so they can be routed, mapped to content and reported at scale. It's how a system turns a raw stream of keywords into structured intent.
Our own Universal Query Classifier takes this further with an open-set, zero-shot design: you hand it any list of labels at inference time and it scores which ones fit each query, with no retraining. Because labels are treated as text rather than fixed IDs, it can apply several at once, including labels it has never seen. It was trained on 114k pairwise rows across more than 40 industries using a binary relevance objective.
For AI SEO this powers query-intent mapping straight from Search Console exports, SERP intent-gap analysis, and dashboards that track shifting intent over time. It's a close cousin of query fan-out and feeds directly into relevance engineering.
