Keyword research still starts with real search data, but sorting hundreds of raw keywords into intent-based topic clusters is exactly the kind of pattern-matching work an AI assistant like Claude can take off your plate.
Feed It Raw Data, Not Just a Prompt
Paste in an exported keyword list with volume and competition figures and ask Claude to group the terms by search intent and topic — it's far more useful with real data in front of it than with a vague request to "brainstorm keywords."
Ask for the Reasoning, Not Just the List
Prompting Claude to explain why it grouped certain terms together surfaces intent distinctions you might otherwise miss, like separating "buy" and "compare" variants of the same core phrase.
Treat the Output as a Draft, Not a Final Answer
Claude is good at organizing and pattern-spotting, but actual search volume and difficulty still need to come from real keyword data — use it to structure the list, not to invent numbers.
Next step: Use the LSI Tool to pull related terms and feed them into Claude as raw material for clustering.