Discover 5 proven ways to find GEO prompts—from GSC and Reddit to PAA and sales calls—and adapt your content for AI search

Are you still creating content with the old keyword-first SEO mindset?

Users aren’t going to Google and typing fragmented phrases like “CRM software small business” anymore. In ChatGPT, they ask things like:

“What’s the best CRM for a 10-person sales team with a limited budget that also needs email integration?”

The average Google search is about 9.2 words. The average ChatGPT prompt is around 23 words. That’s nearly 3x longer.

Which means a huge chunk of the keyword lists you’ve built over the years is far less useful in an AI-driven search environment.

So the real question is: if the way people ask has changed, where do you actually find these prompts?

You can’t just guess.

In this article, I’ll walk through five proven sources you can use right away.

Turn Long-Tail Keywords into GEO Prompts

Many of the long-tail keywords and question-based queries you already use for SEO are basically ready-made GEO prompts.

You do not need to reinvent the wheel.

One of the most valuable assets you already have is your query data in Google Search Console (GSC). Most people look at rankings and impressions, but ignore the actual search terms. Open GSC and filter for queries longer than 10 words. Those are often very close to the way people naturally phrase questions.

You’ll usually find lots of searches starting with “how to,” “vs,” and “best for.” Those are often direct prototypes for ChatGPT-style prompts.

Here’s how to do it:

Open SEMrush or Ahrefs, search your core keywords, and check the Questions tab
Enter a keyword into AnswerThePublic to generate real user questions built around “what,” “how,” and “why”
Pull raw search terms from your Google Ads search term report—even the misspellings matter, because that’s how real users actually talk
Expand your most important long-tail keywords into fuller prompt-style variations

A common mistake: don’t treat short-tail keywords as prompts. No one asks AI “CRM software.” You need queries with real context, like “Is HubSpot or Salesforce better for a startup?”

It also helps to group these long-tail queries by intent:

Informational: the user wants to understand a concept (“What is GEO?”)
Exploratory: the user is looking at options (“What are the best CRM tools?”)
Comparative: the user is comparing products (“Which is better, A or B?”)
Purchase decision: the user is close to buying (“How much does X cost?”)

Bottom line: don’t underestimate the SEO data you already have. Those long queries sitting in GSC may be some of your best GEO prompt inputs.

Use LLMs to Predict What Users Might Ask

Feed an LLM your brand information, audience profile, and core keywords, and let it generate likely user prompts across different stages of the buying journey.

This is one of the fastest ways to work.

Instead of trying to manually imagine every question your audience might ask, let AI do the heavy lifting.

Here’s a simple workflow:

Open ChatGPT or Claude and use a prompt like: “You are a GEO researcher. Generate prompts users might ask AI about [your topic]. Rank them by importance.”
Provide your audience profile: age, job title, pain points, goals
Add your product or service category
Include your core keywords

Then ask it to generate prompts by stage:

Problem awareness: “Why does my small business need a CRM?” “How can I improve sales team efficiency?”
Solution exploration: “What are the best CRMs for small businesses?” “What’s the difference between free and paid CRM tools?”
Purchase decision: “Is X product a good fit for a 10-person team?” “Which offers better value, Y or Z?”

A common mistake: don’t stop after generating 20 prompts. Run the exercise multiple times from different angles. Generate 200, then filter. AI-generated prompts still need human review—some will be too broad, some too narrow, and some won’t reflect real demand at all.

Bottom line: think of LLMs as prompt expansion engines. You give them the seed terms, and they give you useful variations at scale.

Mine Reddit and Quora for Real User Language

Forum content gets cited heavily in LLM outputs—not because it has great SEO, but because upvotes act as quality signals.

This is one of the most underrated prompt sources.

Why does Reddit show up so often in AI training data? Because once a post gets a few upvotes, it has effectively been validated by real people as useful. For anyone collecting training data, that’s free labeling.

The result: upvoted Reddit content often carries outsized weight compared with its actual share of web traffic.

So how do you mine it?

Find subreddits in your niche. If you work in CRM, start with places like r/CRM, r/sales, and r/smallbusiness
Search your core topics and sort by Top to see how users naturally phrase their questions
Save the titles and content from highly upvoted posts—the original wording is often exactly how users ask AI
Do the same on Quora: search your topic and look at the questions behind the highest-engagement answers

A common mistake: don’t go into Reddit trying to push your product. GEO is not a posting strategy—it’s a content strategy. You’re there to study user language, not chase referral traffic.

Also, LLM training data works on update cycles. If you miss a training window, it may take 6–12 months before the next major refresh.

Bottom line: Reddit and Quora are not just promotion channels. They’re user-language sampling tools. If you want to know how people really ask questions, start there.

Use Google PAA and Trends to Find the “Subtext” Behind Search

Every question in People Also Ask (PAA) is a ready-made GEO prompt.

And Google Trends tells you which directions are gaining momentum.

How to use PAA:

Search your core keyword on Google
Open the People Also Ask box
Collect the questions you see—they reflect real user search behavior and are naturally phrased in a way that works well for AI
Use tools to scale the process:
- Answer Socrates (free, up to 60 questions at a time)
- SearchResponse (supports Bing and Yahoo)
- RightBlogger (AI-assisted generation)

Key move: don’t stop at the first layer. Keep expanding the follow-up questions inside PAA. A few clicks can uncover dozens of related question patterns.

How to use Google Trends:

Enter your core keyword
Look at the Rising section under related queries
Compare trend lines across different terms to spot growth areas
Turn those rising searches into fuller prompt formats

A common mistake: Trends gives you direction, not polished prompts. A rising term like “CRM small business” may need to become something more natural, such as “How do I choose a CRM for a small business in 2025?”

You still need to add context.

Bottom line: PAA is a goldmine for prompt discovery, and Trends is your directional signal. Use them together to find both the questions people already ask and the topics that are starting to grow.

Pull Real Pain Points from Sales Calls and Support Tickets

Internal data is one of the most overlooked prompt sources.

The exact language customers use in sales calls and support tickets is often the same language they use when asking AI for help.

And it’s usually more accurate than anything you’ll get from external tools.

Think about it:

Your sales team may hear the same objection every week:

“Your product costs so much more than competitors—is it really worth it?”

Your support team may handle the same question every day:

“How do I migrate my data from our old system?”

That’s real user language. And there’s a good chance those same people are asking AI those same questions.

Here’s how to use it:

Review sales call recordings from the last 3 months and identify recurring objections
Pull the original wording from support tickets—don’t rewrite it
Extract pain-point language from customer interviews and satisfaction surveys
Turn that language into prompt-style queries

Key move: build a tracking list of 20–30 core prompts. Run them weekly in ChatGPT, Perplexity, and Google AI Overviews, and record whether your brand appears—and where.

A common mistake: don’t overreact to one week of movement. AI outputs are volatile. It’s normal to appear one day and disappear the next. Focus on 3–6 month trends, not weekly noise.

Bottom line: your company is probably already sitting on a high-quality prompt database. Your sales and support teams are doing user research every day—you just need to capture it.

Final Thoughts

GEO prompt research isn’t mysterious.

It’s simply the evolution of SEO—from keyword thinking to user-language thinking.

You don’t need brand-new tools, either. Google Search Console, SEMrush, AnswerThePublic, Reddit, Quora, PAA, Google Trends, and even your own sales recordings are all valid prompt sources.

Only one thing really matters: stop obsessing over short-tail keywords and rankings.

The way users ask AI has changed. Your content strategy needs to change with it.

Start today. Add prompt discovery to your workflow. Build a list of 20 core prompts, review them every week, and within 3 months, you’ll start seeing the difference.