# Prompt Research vs Keyword Research: How to Find What People Actually Ask AI **URL:** https://organikpi.com/blog/seo-strategy/prompt-research-vs-keyword-research/ **Published:** 2026-04-27 **Modified:** 2026-06-26 **Author:** Daniel Shashko > Prompt research finds the questions people ask AI assistants; keyword research finds the strings typed into Google, and live June 2026 data shows how little they overlap. Head terms stay in Google (keyword research: 368,000 Google searches vs 1,298 AI queries monthly), while some terms have inverted: prompt research is asked 2.5x more in AI (50 vs 20). Long constraint-loaded prompts show no volume anywhere because most prompts occur only once. No AI provider publishes prompt logs; DataForSEO models AI keyword volumes, Semrush tracks decision-stage prompts, and Sistrix clusters 62M questions into topics (Germany only). The free workflow: interrogate the model, mine People Also Ask, harvest Reddit questions, cluster to canonical questions, track AI mentions monthly. --- > Prompt research finds the questions people ask AI assistants; keyword research finds the strings typed into Google, and live June 2026 data shows how little they overlap. Head terms stay in Google (keyword research: 368,000 Google searches vs 1,298 AI queries monthly), while some terms have inverted: prompt research is asked 2.5x more in AI (50 vs 20). Long constraint-loaded prompts show no volume anywhere because most prompts occur only once. No AI provider publishes prompt logs; DataForSEO models AI keyword volumes, Semrush tracks decision-stage prompts, and Sistrix clusters 62M questions into topics (Germany only). The free workflow: interrogate the model, mine People Also Ask, harvest Reddit questions, cluster to canonical questions, track AI mentions monthly. Keyword research finds the strings people type into Google. Prompt research finds the questions people ask AI assistants. The two barely overlap, and for the first time you can put real numbers on both sides. We pulled live June 2026 data to show exactly where each method sees, and where each one is blind. One keyword is one string. One information need becomes dozens of differently-phrased prompts. ## Google volume vs AI volume: live data, same keywords We ran the same keyword set through Google Ads volume data and through [DataForSEO’s AI Keyword Data API](https://docs.dataforseo.com/v3/ai_optimization-overview/), which models how often keywords appear in queries to ChatGPT and other LLMs. United States, June 2026, monthly figures: QueryGoogle searchesAI assistant queriesWhat it tells you keyword research368,0001,298Head terms still live in Google best crm for small business3,600197Commercial terms: Google dominates, AI share growing how to do keyword research1,300120How-to intent is migrating generative engine optimization4,40027Trend terms spike in Google first prompt research2050Asked 2.5x more in AI than in Google best crm for a 10 person startupno data0 recordedThe shared blind spot: long conversational queries Three things jump out. AI query volumes run at roughly 0.5 to 5 percent of Google volumes for established terms. Some terms have already inverted: “prompt research” is asked more inside AI assistants than it is searched in Google. And the most valuable queries, the long, constraint-loaded ones, show no volume anywhere, because [most prompts appear only once](https://www.sistrix.com/blog/prompt-research/). ## Why prompts and keywords are different languages - **Length and structure.** A Google query averages 3 to 4 words. A [ChatGPT](https://organikpi.com/blog/geo-ai-search/chatgpt-fast-answers-brand-impact/) prompt routinely runs 15 words or more, with context, constraints, and budget baked in. - **First person framing.** “How hard is it to import all our contacts from a messy Excel spreadsheet” is a prompt. “crm import contacts” is a keyword. Same need, different language. - **One prompt, many retrievals.** AI engines decompose a prompt into multiple sub-queries through [query fan-out](https://organikpi.com/blog/geo-ai-search/ai-mode-follow-up-questions-conversational-search/), then synthesize one answer. Your content competes at the sub-query level, which is exactly what we measured in our [42,971 citation study](https://organikpi.com/blog/geo-ai-search/decoded-42971-ai-citations-google-research/): the engine retrieves short, atomic answers to the decomposed pieces. ## What prompt research can and cannot see in 2026 Be clear-eyed about the tooling. No AI provider publishes prompt logs. There is no Google Keyword Planner for ChatGPT. Everything on the market is a model built on proxies: - **[DataForSEO AI Keyword Data](https://docs.dataforseo.com/v3/ai_optimization-overview/)** estimates keyword-level AI [search volume](https://organikpi.com/blog/gtm-strategy/share-of-voice-vs-search-volume/) with 12 months of trend. It is keyword-shaped, not prompt-shaped, but it is queryable by API today: the table above cost about one cent to produce. - **[Semrush Prompt Research](https://www.semrush.com/blog/prompt-research-for-ai-seo/)** builds on a clickstream-informed prompt database and focuses on tracking decision-stage prompts where AI actually recommends brands. - **[Sistrix Prompt Research](https://www.sistrix.com/blog/prompt-research/)** clusters 62 million real user questions into 1.4 million analyzable topics with intent and journey stage. Currently Germany only, which tells you how early this category is. So is prompt research possible right now? Partially. You can get modeled AI volumes per keyword, clustered topics in some markets, and brand-mention tracking across engines. You cannot get the raw distribution of prompts. The free workflow below fills that gap. ## The free prompt research workflow (with live examples) ### 1. Interrogate the model directly Ask the assistant what people ask it. We gave [Gemini](https://organikpi.com/blog/technical-seo/ai-search-api-integration-guide/) one prompt: “What are the 15 most common questions people ask you when they are choosing a CRM for a small business?” The output is a ready-made list of first-person, constraint-loaded prompts: Gemini returns the prompts verbatim: integration worries, messy spreadsheet imports, exit risk Notice the language: “my sales guys”, “messy Excel spreadsheet”, “what happens if we decide to leave”. No keyword tool surfaces that phrasing. Each of those is an H2 or FAQ candidate. ### 2. Mine People Also Ask at scale PAA boxes are Google’s own question-shaped data and the closest free proxy for conversational phrasing. Pulling the live PAA set for “keyword research” returns: “What is keyword research?”, “Can I use ChatGPT for keyword research?”, “How to do keyword research for free?”, “What are the 4 types of search intent?”, and “Can I do SEO by myself?”. The ChatGPT question appearing twice in one PAA tree is the market telling you where this topic is heading. ### 3. Harvest forums where people already write prompts [Reddit](https://organikpi.com/blog/distribution/reddit-seo-ai-citations/), Quora, and Stack Exchange questions are written in the same first-person, multi-constraint register as AI prompts, with upvotes as a free demand signal. Scrape question titles in your niche weekly and treat them as prompt candidates. ### 4. Cluster prompts into topics and write to the canonical question - Cluster 50 to 100 raw prompts into 8 to 12 intent themes. - Pick the canonical question per theme and phrase one H2 exactly as that question. - Open the section with a direct 1 to 2 sentence answer, then add depth. That structure matches how engines pick citable sentences. - Prioritize themes with constraints (budget, team size, industry): constraint prompts are where assistants compare options and recommend brands. ### 5. Track whether AI actually mentions you Prompt research without response tracking is half a loop. Re-run your 10 to 20 highest-value prompts monthly and log [brand mentions across engines](https://organikpi.com/blog/seo-strategy/ai-brand-visibility-tracking-metrics/), your [share of voice against competitors](https://organikpi.com/blog/seo-strategy/ai-search-brand-share-of-voice/), and the referral sessions landing in [GA4](https://organikpi.com/blog/technical-seo/ga4-ai-search-referral-attribution/). ## Where keyword research still wins - **Demand sizing.** Google volumes remain the only robust demand estimator. AI volumes are modeled and a fraction of the size. - **Commercial intent with CPC signal.** Cost-per-click data tells you what a click is worth. Prompts have no CPC. - **Trend history.** Keyword databases go back years; AI volume data starts in 2025. - **Surfaces that are still Google.** [AI Mode](https://organikpi.com/blog/seo-strategy/google-ai-mode-optimization-playbook/) and AI Overviews sit on Google queries, so classic keyword targeting still feeds the AI layer above it, even as [clicks decline](https://organikpi.com/blog/geo-ai-search/zero-click-ai-search-strategy/). The operating model for 2026: size demand with keywords, phrase content with prompts, and measure both sides with the [GEO KPI framework](https://organikpi.com/blog/seo-strategy/geo-kpi-measurement-framework/) and the [AI search metrics that matter](https://organikpi.com/blog/seo-strategy/ai-search-analytics-metrics-that-matter/). If you are new to the discipline, start with [what GEO is](https://organikpi.com/blog/geo-ai-search/what-is-geo-generative-engine-optimization/). ## Frequently Asked Questions ### What is prompt research? Prompt research is the process of finding the questions people ask AI assistants like ChatGPT, Gemini, and Perplexity, then shaping content around those questions. It plays the role for AI visibility that keyword research plays for SEO, but the unit is a conversational question with constraints, not a typed search string. ### Is there a search volume tool for AI prompts? Partially. No AI provider publishes prompt logs, so all numbers are modeled. DataForSEO's AI Keyword Data API estimates monthly AI query volume per keyword, Semrush offers a clickstream-informed prompt database with prompt tracking, and Sistrix clusters 62 million real questions into topics with estimated AI volumes, currently for Germany only. Treat every figure as an estimate, not a measurement. ### Does keyword research still matter for AI search? Yes. Google volumes are still the only robust way to size demand, CPC still prices commercial intent, and Google AI Mode and AI Overviews sit on top of Google queries. Keywords size the market; prompts tell you how buyers phrase the decision. Run both. ### How do I find AI prompts for free? Four free sources: ask the assistant directly what questions people ask it about your topic, mine People Also Ask boxes at scale, harvest question titles from Reddit, Quora and Stack Exchange in your niche, and review your own chatbot or support logs if you have them. Cluster the results into 8 to 12 themes and write to the canonical question of each theme. ### How many prompts should I track? Start with 10 to 20 decision-stage prompts per product, focused on different personas and constraints rather than wording variations. Re-run them monthly across ChatGPT, Gemini, and Perplexity, and log whether your brand is mentioned, how it is framed, and which competitors appear instead.