Prompt-Level SEO: Optimizing for the Question Behind the Question

Prompt-level SEO is the practice of researching, mapping and writing for the full natural-language questions buyers ask AI engines, not the 2–4 word keyword fragments they used to type into Google. The unit of optimization is no longer the keyword — it's the prompt, including its implicit follow-ups.

Table of contents

1. What is prompt-level SEO? · 2. Why keyword research alone misses 70% of AI demand · 3. How do I find the prompts my buyers are actually using? · 4. The question-behind-the-question framework · 5. How do I structure a page to answer multi-turn prompts? · 6. Measuring prompt coverage · 7. FAQ

What is prompt-level SEO?

Prompt-level SEO researches the full conversational queries users send to ChatGPT, Perplexity, Gemini and Claude, then maps each prompt — and its likely follow-ups — to a page or section designed to answer it completely. It replaces the keyword as the atomic unit of SEO planning.

Why keyword research alone misses 70% of AI demand

Google Trends and Semrush capture the head terms users type into a search box. They do not capture the long, contextual questions users now type into a chat box. According to Pew Research, **34% of U.S. adults already use generative AI, and the share treating it as their primary research tool roughly doubled between 2024 and 2025**. Most of those queries never appear in any keyword tool.

How do I find the prompts my buyers are actually using?

Combine four sources: (1) AlsoAsked, AnswerThePublic and Google's 'People also ask' for question-shaped variants of your head terms; (2) sales-call transcripts and support tickets for the exact phrasing prospects use; (3) Reddit and Quora threads in your niche, which are heavily over-represented in LLM training data; (4) prompt-tracking tools like Profound, Otterly and AthenaHQ that show the actual queries triggering AI answers in your category.

The question-behind-the-question framework

Every prompt has a surface question and an underlying decision the user is trying to make. 'What is the best CRM for a 5-person team' is the surface; 'I'm a founder, I have $200/mo, I need email + pipeline + reports, will I outgrow it in 12 months' is the question behind the question. **Pages that answer both get cited; pages that answer only the surface keyword get skipped.** Map every target prompt to its underlying decision before you start writing.

How do I structure a page to answer multi-turn prompts?

Open with a 2–3 sentence summary that fully describes the topic (the GEO summary). Then use question-shaped H2s for the surface query and at least three predictable follow-ups, each with a 40–60 word direct answer in the first paragraph. Close with an FAQ section covering five real follow-ups not already covered as H2s. The pattern matches how LLMs chunk and re-rank passages.

Measuring prompt coverage

Build a tracker of 50–200 priority prompts in your category. Re-run them weekly across ChatGPT, Perplexity, Gemini and Google AI Overviews. Score each as Cited / Not Cited / Mentioned-Without-Link. Citation rate, share of voice vs competitors and trend over time are the three KPIs that matter — I covered the full measurement playbook in my measure-AEO-performance guide.

Frequently Asked Questions

Is prompt-level SEO different from long-tail keyword SEO?

Yes. Long-tail keywords are still single search-box phrases. Prompts are full natural-language questions, often 15–40 words, with embedded context and an implicit follow-up. The research methods, page structure and measurement are different.

Do I still need traditional keyword research?

Yes — Google still drives the majority of click-through traffic for most niches. Run both: keywords for blue-link rankings, prompts for AI citations. The two often share underlying topics but rarely share the exact phrasing.

How many prompts should I track per category?

Start with 50 priority prompts that map to your top revenue topics. Scale to 200–500 once you have a baseline. Beyond that you're better off tracking share of voice across a representative sample than chasing every variant.

Can one page rank for multiple related prompts?

Yes — that's the goal. A well-structured pillar page with question-led H2s, a deep FAQ and clean schema can be cited for dozens of related prompts. Thin pages targeting one keyword apiece are an old playbook.

What tools do you actually use for prompt research?

AlsoAsked + AnswerThePublic for question seeds, Profound for prompt-level citation tracking, ChatGPT and Perplexity directly for live prompt validation, and a private spreadsheet of every question I've ever heard on a sales call. Combined cost is under $200/month.