How Does Intent Capture Work?
Intent Capture works through three patterns: Answer Page Context, Progressive Confirmation, and Downstream Capture. When ChatGPT cites an Answer Page, the URL structure encodes the intent cluster — environment, asset, problem, constraints — without needing the original query. Navigators then refine with one question ("Chemical exposure too, or just humidity?"), upgrading confidence from inferred to confirmed. Forms and product selectors capture commercial facts (budget, timeline) deterministically.
The 3 Capture Patterns
Pattern 1: Answer Page Context (Primary)
This is the Hyperize thesis: the page URL is the intent signal.
When a customer asks ChatGPT a detailed question and ChatGPT cites a specific Answer Page, the click-through tells you the intent cluster. You don't need ChatGPT to pass you the query. The page selection is the intent signal.
Example URL structure:
Extracted facts (deterministic from URL):
environment: hospital— confidence: 0.95asset: AHU— confidence: 0.95problem: clogging— confidence: 0.95constraints: [high_humidity]— confidence: 0.95
Pattern 2: Progressive Confirmation (Refinement)
Once we have the intent cluster, we refine with minimal friction. One question, not fifteen:
"Are you also dealing with chemical exposure, or just humidity?"
This converts implicit selection into explicit confirmation, upgrading authority from deterministic_url to user_confirmed.
Pattern 3: Downstream Capture (Commercial Facts)
Budget, timeline, and authority aren't encoded in Answer Page URLs. These emerge later through:
- Navigator conversations: LLM extraction from natural language
- Form submissions: Deterministic capture
- Product selector behavior: Deterministic from clicks/selections
- Sales notes: CRM integration
The Capture Cascade
Each touchpoint adds to the customer's intent profile. By the time Sales receives the lead, they have the full context — without asking a single qualification question the customer already answered upstream.