Starting an AI chat

The AI chat is a peer of the guided form — a different way to interact with the same search engine. It’s also a research conversation surface for follow-up questions, “what about” pivots, and analysis of results.

In this guide:

  • Open the chat
  • Send a first message
  • Recognize the two modes
  • Run a search inline

Step 1: Open the chat

From the Product Research home, click Chat in the toggle row, or open it from the sidebar.

The chat is anchored as a chat panel — a familiar messaging UI with a composer at the bottom and a thread above it.

Step 2: Send a first message

Type whatever you want — a search request, a question about the SellerScore, a follow-up on a previous result. Claude figures out which.

Two examples:

A search request:

“Show me bamboo socks under $20 in the UK with low competition.”

A conversational question:

“How does the demand sub-score work when SFR isn’t available?”

Both are valid messages. Claude routes them differently.

Step 3: The two modes

Claude has exactly two tools available:

ToolWhen Claude picks itCost
extract_search_paramsThe message describes a research goal.1 credit (for the triggered search).
no_search_intentThe message is conversational, exploratory, or a question.Free.

You see the difference in the response:

  • Search: A short ack (“Searching for…”) → search runs inline → results render in the chat → AI analysis of the top 5.
  • Conversational: A streamed, plain-text answer.

Intent extraction for the full mechanics.

Step 4: Run a search inline

When Claude triggers a search, you see:

  1. Acknowledgement — “Searching for [extracted parameters]…”
  2. search_triggered event — the parameters Claude extracted, displayed for transparency.
  3. search_completed event — top 5 results render as cards inline in the chat.
  4. Streamed AI analysis — Claude reads the results and offers a paragraph of synthesis.

The cards in the chat are tappable just like results in a list — open a detail, add to watchlist.

Continuing the conversation

After a search runs, you can refine without starting over:

  • “Tighten that to 25%+ margin.” (re-runs with adjusted params; 1 credit)
  • “Why did the top one score that way?” (conversational; free)
  • “Add product 3 to my watchlist.” (executes the action; free)

The AI keeps context across the conversation.

When chat shines

  • Exploratory phase“what’s a good niche for a new seller in the UK in 2026?” — broad questions Claude can think through.
  • Iterative refinement — easier to say “narrow to under $30” than to re-fill the form.
  • Cross-question synthesis“compare the top 3 in this search to the top 3 from yesterday.”
  • Analysis on demand“explain why the trend sub-score is dragging this product.”

When to fall back to guided

  • Reproducibility — if you need exactly the same parameters every time.
  • Power-user workflows — when filter/weight tuning matters more than chat-style flow.
  • Faster — for repeated searches with known parameters, the guided form is fewer keystrokes.

The two modes use the same engine; pick whichever fits the moment.

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