AEO Keyword Strategy: How to Find and Optimize Prompts for AI Search

Traditional keyword research analyzes what people type into Google — short phrases like "best CRM" or "plumber near me." AI search is fundamentally different. When people interact with ChatGPT, Perplexity, or Google Gemini, they use natural language prompts that are longer, more specific, and more conversational than Google search queries. A Google user types "best CRM small business." A ChatGPT user types "I run a 15-person marketing agency and need a CRM that integrates with HubSpot and costs less than 50 dollars per user per month. What do you recommend?"

The prompt gap: where opportunities hide

These are not the same query. The Google user gets a ranked list and clicks through several results. The ChatGPT user gets a direct recommendation — one or two specific products named, explained, and compared. The prompt gap is the difference between what people search on Google and what they ask AI engines. This gap represents an enormous opportunity for businesses that understand it. Traditional keyword tools like Ahrefs or Semrush cannot show you what prompts people use in ChatGPT because that data is not public. Instead, you need a different approach: prompt research, which involves understanding the types of questions your target audience asks AI engines and optimizing your content to be the answer.

Since no tool provides direct access to ChatGPT prompt data, effective prompt research uses a combination of methods:

1. Ask the AI engines themselves. Go to ChatGPT, Perplexity, and Gemini. Type prompts your customers would use: "What is the best [your product category] for [your target customer]?" See which businesses get recommended and what language the AI uses to describe them. This is your competitive landscape.
2. Mine your customer conversations. Review support tickets, sales calls, and chat transcripts. The exact words your customers use to describe their problems are the exact prompts they type into AI engines. "We need something that handles invoicing and time tracking in one app" is a real prompt pattern.
3. Analyze "People Also Ask" on Google. Google's PAA boxes contain questions that closely mirror AI prompts. Tools like AlsoAsked can export these at scale.
4. Use LunimRank's prompt research feature. LunimRank tests your business against real prompt patterns across 7 AI engines and shows you exactly which prompts trigger citations of your business and which trigger competitor citations instead.

Building your prompt library

Create a spreadsheet with three columns: Prompt (the natural language question), Intent (purchase, comparison, informational, or navigational), and Current Status (cited, not cited, competitor cited). This becomes your AEO keyword file — the equivalent of a traditional keyword research spreadsheet, but for AI search. Start with 20 to 30 prompts covering your core products or services, then expand over time as you discover new patterns.

Just as SEO keywords have search intent, AI prompts have prompt intent — and the optimization strategy differs for each type:

Intent Type	Example Prompt	What AI Looks For	Your Content Strategy
Purchase (highest value)	"I need a plumber in Winnipeg for a kitchen renovation"	Specific business names, pricing, reviews, availability	LocalBusiness schema, Google Business Profile, review volume
Comparison	"Compare Mailchimp vs ConvertKit for small business email"	Feature-by-feature comparison, pricing tables, pros/cons	Comparison pages with HTML tables, honest pros/cons
Informational	"How does AI search optimization work?"	Comprehensive, authoritative explanation with cited sources	Long-form guides with structured headings and schema
Navigational	"LunimRank pricing page"	Direct link to the specific page requested	Clear site structure, schema, proper page titles

Weighting your optimization effort

Not all prompt intents are equal. Purchase intent prompts drive revenue directly — when someone asks an AI "who should I hire to build my deck in Toronto," they are ready to buy. Comparison prompts are the next most valuable because users are actively evaluating options. LunimRank's AI Readiness Score weights prompts by intent: purchase prompts count 3x, comparison 2x, informational 1.5x, and navigational 1x. This weighting ensures your score reflects business impact, not just citation volume.

Knowing which prompts to target is only half the strategy. The other half is structuring your content so AI engines actually extract and cite it. These content patterns have the highest citation rate across all major AI engines:

• Answer-first paragraphs. Start every section with a direct, complete answer. "The best CRM for small businesses is [X] because [reason]" not "When evaluating CRMs, there are many factors to consider..."
• Definitive lists with rationale. "The top 5 project management tools for agencies are: 1) Monday.com — best for visual workflows, 2) Asana — best for task dependencies..." AI engines love numbered lists with brief explanations because they can extract and present them cleanly.
• Comparison tables. HTML <table> elements with clear headers. AI engines parse tables more reliably than prose comparisons.
• Specific, quantified claims. "Reduces invoice processing time by 40 percent" gets cited. "Significantly improves efficiency" does not.
• FAQ sections. Questions and answers in FAQPage schema format. This is the single most-cited content format across all AI engines because it perfectly matches the Q&A interaction model.

The citation-killing anti-patterns

Equally important is what to avoid:

• Vague, hedge-filled language ("it depends," "results may vary")
• Content that builds up to the answer instead of leading with it
• Walls of unstructured text without headings or lists
• Outdated information without a visible "last updated" date
• Generic content that could apply to any business in your category

AI engines evaluate thousands of potential sources for each prompt. Content with any of these anti-patterns is filtered out in favor of content that is direct, structured, and specific.

Traditional SEO measures keyword performance through rankings, impressions, and clicks in Google Search Console. AEO keyword performance is measured differently because AI engines do not have positions or click-through rates in the traditional sense. The key AEO metrics are:

1. Citation rate — what percentage of relevant prompts result in your business being cited? LunimRank tracks this across 8 engines with weekly automated scans.
2. Citation quality — when you are cited, is it a passing mention or a primary recommendation? LunimRank's 5-dimension scoring measures mention depth, sentiment, positioning, and link inclusion.
3. Engine coverage — are you cited across all major AI engines or only one? Being cited by Perplexity but not ChatGPT means you are missing the largest audience.
4. Competitor gap — which prompts cite your competitors instead of you? This reveals exactly which content needs improvement.
5. Score trend — is your AI Readiness Score improving week over week? A rising score means your optimizations are working.

Building a feedback loop

The most effective AEO keyword strategy is iterative: research prompts, optimize content, measure results, identify gaps, optimize again. LunimRank automates the measurement step with weekly scans, so you spend your time on optimization rather than manual checking. Start with a free scan at lunimrank.com to see which prompts your business currently wins and which it loses.

How many prompts should I target initially? Start with 15 to 25 prompts covering your core products or services. Focus on purchase and comparison intent prompts first because they drive revenue directly. Expand to informational prompts once your high-intent coverage is solid.

Tools and timeline for AEO keyword research

Can I use traditional keyword tools for AEO research? They are a starting point but insufficient alone. Tools like Ahrefs and Semrush show Google search volume but not AI prompt patterns. Use them to identify topics, then rewrite the keywords as natural language prompts and test them directly in AI engines. How often should I update my prompt library? Monthly. AI engines update their models and browsing capabilities frequently, and new competitors enter the AI recommendation pool regularly. A prompt that cited you last month may cite a competitor this month if they published better content. Is there a "keyword difficulty" equivalent for AEO? Not exactly, but LunimRank's competitor gap analysis shows how many and which competitors are being cited for each prompt. More competitors cited = harder to displace. Focus first on prompts where few competitors appear.