15 prompts to find untapped keywords with ChatGPT

ChatGPT, Claude, and Gemini are now part of every serious keyword-research workflow. Not as a final answer — they hallucinate volumes — but as idea generators that surface phrasings keyword tools miss. Here are 15 prompts that produce useful raw material.

1. Customer-language harvest

"You are a [niche] customer. List 20 phrases you would type into Google when you have problem X but don't yet know the technical term for it."

Bypasses jargon. Surfaces beginner-phrased searches that tools under-report.

2. Pain-point inversion

"List 15 frustrations someone in [niche] has, phrased as the search query they'd type when frustrated."

Mines emotional intent. Pain-point queries convert disproportionately.

3. Sub-niche expansion

"What are 20 sub-niches inside [broad niche] that have active practitioners but aren't well-served online?"

Identifies under-served clusters before competitor tools surface them.

4. Adjacent-task discovery

"What 15 tasks does someone do AFTER they've solved [main problem]?"

Long-tail clusters around the core query. Often unaddressed.

5. Pre-purchase research

"What are the 10 most common research questions someone asks in the 7 days before buying [product]?"

Decision-stage queries with high commercial intent.

6. Mistake mining

"What 15 common mistakes do beginners make in [niche]?"

Each becomes a "how to avoid X" query — classic listicle territory.

7. Comparison generation

"List 20 product comparisons people make in [niche] (X vs Y format)."

Comparison keywords keep their organic clicks even with AI Overviews active.

8. Tool / alternative discovery

"What are alternatives to [popular tool in niche], and how would someone search for each?"

Alternative-keyword traffic is steady and commercial.

9. Role-specific phrasings

"How would a [specific job role] phrase the question 'what should I learn about X'?"

Professional vocabulary differs from consumer vocabulary. Tap both.

10. Generational phrasings

"How would a 60-year-old vs a 20-year-old search for [topic]?"

Age-based phrasings surface entire keyword clusters most tools miss.

11. Geographic variation

"Same search intent — how do British, American, Australian, and Indian English speakers phrase it differently?"

Country-specific phrasings open whole regional markets.

12. Voice-search variants

"Convert these 10 short keywords into the full conversational queries someone would speak to Siri or Google Assistant."

Voice queries are longer, more specific, and under-targeted.

13. Trending angle

"What's a new angle on [evergreen topic] that's emerged in the last 12 months?"

Surfaces freshness-driven keywords competitors haven't caught up to.

14. Reverse from a competitor

"This site [URL] ranks for [topic]. What 20 related queries could a competitor target that this site doesn't?"

Competitor-gap discovery. Even rough output kicks off real research.

15. AI Overview avoidance

"List 20 [niche] keywords where the answer requires opinion or recommendation (not a single fact), so AI Overviews would avoid them."

Specifically targets keywords that retain organic CTR in the AI-search era.

The crucial second step

ChatGPT outputs are RAW. Volumes, difficulty, SERP weakness — none of that is real until you validate. Drop the AI-generated list into a real keyword tool to filter for actual demand and ranking opportunity.

SERPTool ingests up to 1,000 keywords per analysis, so an entire prompt's output goes in one batch. You get back the ones with real volume AND weak SERPs.

Try the validator step — 40 free credits on signup.