Running Keyword Research with AI: A Hands-On Companion

Running Keyword Research with AI: A Hands-On Companion

Read the strategy first. The full framework — how AI reframes keyword research around intent, semantics, and trends, the tool landscape, and where human judgment decides — lives in AI-Powered Keyword Research. This page is the execution companion: the actual prompts you run to do the work.

This file exists so the “using AI for SEO” toolkit has the keyword-research prompts alongside the rest of the workflow. It deliberately doesn’t repeat the strategy — it shows how to drive an LLM (Claude, ChatGPT, Gemini, or an SEO suite’s built-in assistant) through the job.

Run order

Keyword research inside an assistant follows the same shape whichever model you use: expand → classify → cluster → prioritize → validate. Do it in that order, keep the outputs in a sheet, and treat the model’s work as a draft your strategist signs off.

The three prompts that do most of the work

1. Expand a seed.

You are an SEO keyword strategist. Seed topic: "<topic>".
Generate 40 keyword ideas covering long-tail, semantic/related-entity,
and question-based variants. Return a table: keyword | type | why it matters.
Do not invent search volumes.

2. Classify intent across a list.

Classify each keyword below by dominant search intent
(informational / commercial investigation / transactional / navigational)
and suggest the content format that best serves it.
Return: keyword | intent | recommended format.
<paste keyword list>

3. Cluster into topics.

Group these keywords into thematic clusters, each mapping to a single page.
For each cluster give: cluster name, member keywords, the one primary keyword,
and the page type. Flag any keywords that overlap clusters (cannibalization risk).
<paste keyword list>

Keep the prompts you refine in the shared SEO Prompt Library rather than rewriting them each time.

The two guardrails that matter here

  • Never trust invented numbers. Models will happily fabricate search volumes and difficulty scores. Pull real metrics from a keyword tool (Ahrefs, Semrush, Google Keyword Planner); use the LLM for language, intent, and structure only.
  • A human prioritizes. The model surfaces options; your strategist decides which clusters are worth the content investment, per the canonical guide.

Keep going

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