Understand results
Fanout queries
See the searches and retrieval targets an AI system used while composing a tracked answer.
Some AI systems perform background searches before composing an answer. Selfwin calls those searches fanout queries.
Fanouts help explain why a particular page or competitor entered an answer. They can also reveal the language an AI system uses to decompose a customer’s question.
Observed evidence only
Selfwin stores fanouts that were visible in the browser interface, network activity, or provider grounding metadata. It does not ask another language model to guess which searches probably happened.
Each stored fanout can include:
- Query or retrieval target.
- Type, such as search, shopping, or synthetic where the collector identifies it.
- Order within the answer.
- Collection source.
- Evidence describing where it was observed.
Distinct queries and occurrences
The same normalized query is stored once per chat. Across many chats, Selfwin can distinguish:
- Distinct queries: Different query texts observed in the selected scope.
- Occurrences: The total number of chats in which those queries appeared.
A repeated query is valuable evidence that a topic or source pattern is stable rather than incidental.
Grouping
The Fanouts page can organize evidence by the prompt that triggered it. Prompt detail pages show the corresponding granular evidence for one question.
Use filters to keep the model, country, topic, tag, and date population aligned with the dashboard result you are investigating.
How the Visibility Agent uses fanouts
The agent clusters observed searches and associates them with winning URLs when evidence exists. It checks whether your brand is present, who owns the source, and whether the result appears winnable.
Fanouts can support actions such as:
- Retargeting an existing page to answer a recurring query.
- Creating a comparison or category page.
- Addressing a community thread that models repeatedly retrieve.
- Fixing indexing when an appropriate owned page exists but is not retrieved.
Fanouts are evidence for an action, not proof that executing the action will change a future model answer.