Intent classification

Every conversation turn is classified into one of nine intent buckets. The bucket determines which demand tiers are eligible, which format renders, and what outcome is measured.

Bucket	Signal	Example
Purchase	Active buying intent	”I want to buy a standing desk”
Transactional	Ready to complete a transaction	”Where can I order this tonight”
Consideration	Evaluating options	”Should I get the hybrid or the foam one”
Comparison	Directly comparing products or services	”Explorer vs Highlander for a family of five”
Research	Gathering information before a decision	”What matters in a mattress for back pain”
Informational	General knowledge seeking	”How do memory foam mattresses work”
Navigational	Looking for a specific brand or destination	”Tempur-Pedic official site”
Support	Help with an existing product	”My robot vacuum won’t dock”
Entertainment	Non-commercial conversation	Casual chat, games, creative writing

What is not documented here

Classification model internals are proprietary. Publishers do not need to pass an intent value; classification runs on the conversational context your integration already provides.

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What is not documented here

​What is not documented here

What is not documented here