Prompt Engineering for Visibility: What Questions to Monitor
To effectively monitor your AI visibility, build a prompt library of 30-50 strategic questions across four categories: (1) brand-specific queries that mention your company by name, (2) category queries asking for “best” recommendations in your space, (3) competitor comparison queries, and (4) problem-solution queries describing pain points your product solves. Track these prompts weekly across ChatGPT, Claude, and Gemini to understand your visibility landscape and identify optimization opportunities.
According to SEMrush research, understanding the questions users ask is the foundation of any visibility strategy—this principle applies equally to AI-assisted discovery. But unlike traditional keyword research, AI prompt monitoring requires a different approach: you're tracking conversations, not just keywords.
In this guide, I'll share the exact framework we use at Seenos.ai to help clients build comprehensive prompt monitoring strategies. This methodology has helped over 150 brands identify their most valuable AI visibility opportunities and systematically improve their recommendation rates.
Key Takeaways
- ✓ Start with 30-50 strategic prompts—quality and relevance matter more than volume
- ✓ Cover four prompt categories—branded, category, competitor, and problem-solution queries
- ✓ Track multiple AI platforms—ChatGPT, Claude, Gemini, and Perplexity give different results
- ✓ Monitor weekly at minimum—consistent tracking reveals trends and optimization impact
- ✓ Include competitor prompts—understanding their visibility helps prioritize your efforts
- ✓ Measure mention position and sentiment—being mentioned first matters more than just being mentioned
Why Strategic Prompt Monitoring Matters #
Traditional SEO keyword research tells you what people search on Google. But AI visibility requires understanding the natural language questions users ask conversational assistants. These questions tend to be longer, more specific, and more intent-rich than typical search queries.
More importantly, the same user might phrase their question many different ways. “What's the best CRM for startups?” and “Which customer relationship management tool would you recommend for a 10-person company?” are essentially the same query—but might return different results. Understanding this variation is crucial for comprehensive monitoring.
How Prompts Differ from Keywords #
| Aspect | Traditional Keywords | AI Prompts |
|---|---|---|
| Format | Short phrases (2-5 words) | Full sentences or questions (8-20+ words) |
| Intent | Often ambiguous | Usually explicit and specific |
| Context | Minimal context provided | Rich context (use case, constraints, preferences) |
| Variation | Limited variations matter | Many natural phrasings of same question |
| Volume Data | Search volume available | Volume data limited/unavailable |
The Four Essential Prompt Categories #
A comprehensive monitoring strategy covers four distinct categories of prompts. Each category reveals different aspects of your AI visibility and requires different optimization approaches.
1. Branded Prompts #
These are queries that specifically mention your brand by name. They reveal how AI describes your product, what features it highlights, and whether the information is accurate.
Example Branded Prompts
- “What is [Your Brand]?”
- “Tell me about [Your Brand]'s pricing”
- “Is [Your Brand] good for [use case]?”
- “What are the pros and cons of [Your Brand]?”
- “How does [Your Brand] compare to alternatives?”
2. Category Prompts #
These are “best in category” queries where users seek recommendations without specifying a brand. These are high-value because appearing here means capturing users at the discovery stage.
Example Category Prompts
- “What's the best [category] software?”
- “Top [category] tools for [use case]”
- “Recommend a [category] solution for [company size]”
- “Best free [category] tools in 2026”
- “[Category] software for [industry]”
3. Competitor Prompts #
Track queries that mention competitors. This reveals how AI positions alternatives and identifies opportunities to appear in comparison discussions.
Example Competitor Prompts
- “[Competitor] vs [Your Brand]”
- “Alternatives to [Competitor]”
- “Is [Competitor] worth it?”
- “[Competitor] pricing too expensive, what else?”
- “Problems with [Competitor]”
4. Problem-Solution Prompts #
These queries describe a problem or task without mentioning specific products. They represent users at the earliest research stage—capturing them here builds awareness before they even know your brand exists.
Example Problem-Solution Prompts
- “How do I [task your product solves]?”
- “My team struggles with [pain point]—what should we use?”
- “Best way to [workflow your product enables]”
- “Tools for improving [outcome your product delivers]”
- “How do companies handle [challenge you address]?”
Building Your Prompt Library #
Here's a systematic process for building a comprehensive prompt library:
Step 1: Gather Prompt Sources #
- Customer interviews: Ask customers how they'd describe what they were looking for when they found you
- Sales call recordings: Mine discovery calls for the questions prospects ask
- Support tickets: Look for “how do I...” questions that reveal use cases
- Search console data: Adapt high-performing search queries into conversational formats
- Competitor analysis: Research how competitors position themselves and what queries they target
- Review platforms: G2 and Capterra reviews reveal the language users use to describe products
Step 2: Prioritize by Value #
Not all prompts are equally valuable. Prioritize based on:
- Purchase intent: “Best CRM to buy” > “What is a CRM?”
- Market size: Target queries for your largest addressable segments
- Competition: Balance high-value queries with winnable opportunities
- Content alignment: Prioritize queries where you have strong content to rank
Step 3: Create Variations #
For each core prompt, create 2-3 natural variations. AI responses can vary based on phrasing:
- Core: “Best project management tool for remote teams”
- Variation 1: “What project management software do you recommend for distributed teams?”
- Variation 2: “Top PM tools for companies with remote workers”
Setting Up Your Monitoring Framework #
Once you have your prompt library, establish a systematic monitoring process:
Monitoring Frequency #
- Weekly: Core branded and category prompts (your most important 20-30)
- Bi-weekly: Competitor prompts and secondary category queries
- Monthly: Full prompt library sweep including problem-solution queries
- Event-driven: After major content updates, PR coverage, or product launches
What to Track for Each Prompt #
| Metric | What It Tells You | Target |
|---|---|---|
| Mentioned (Y/N) | Basic visibility—are you in the response? | Present in 70%+ of relevant queries |
| Position | Where in the response you appear (1st, 2nd, etc.) | Position 1-3 for category queries |
| Sentiment | How positively AI describes you | Positive or neutral, never negative |
| Accuracy | Is the information correct and current? | 100% factual accuracy |
| Competitors Mentioned | Who else appears in the same response | Know your AI competition landscape |
Platform Coverage #
Different AI platforms can give different recommendations. According to Search Engine Journal, visibility variations across platforms can be as high as 40%. Monitor:
- ChatGPT: Largest user base, critical for most brands
- Claude: Growing fast, often preferred for detailed analysis
- Gemini: Google integration makes it significant for search-adjacent queries
- Perplexity: Research-focused users, often early adopters
Use AI Visibility Monitor to track across platforms systematically.
Interpreting Your Monitoring Results #
Data without interpretation is noise. Here's how to extract actionable insights from your monitoring:
Common Visibility Patterns #
- Strong branded, weak category: You have brand awareness but need more authoritative content on your category
- Appearing but wrong position: Competitors have stronger signals—focus on citation building
- Inconsistent across platforms: Platform-specific optimization may be needed
- Accurate but not recommended: You're being described but not endorsed—strengthen social proof
- Mentioned with outdated info: Content freshness issue—update key pages
Mapping Results to Actions #
Connect visibility gaps to specific optimization actions:
- Not mentioned at all: Create comprehensive content targeting that query type → See How to Increase ChatGPT Visibility
- Low position: Build authoritative citations and social proof → See Building Authority Signals
- Inaccurate information: Update your pages with current, structured information → See GEO Framework Guide
- Negative sentiment: Address the underlying reputation issue and build positive coverage
Frequently Asked Questions #
How many prompts should I monitor for AI visibility? #
Start with 20-30 high-priority prompts covering your core product categories, main competitors, and key use cases. This is enough to understand your visibility landscape without overwhelming your team. As your monitoring matures and you have systems in place, expand to 50-100 prompts. Quality and relevance matter more than quantity—a focused list you actually track consistently beats a comprehensive list you ignore.
How often should I check AI visibility for my monitored prompts? #
Weekly monitoring is ideal for most brands. This frequency is enough to capture trends and measure the impact of optimization efforts without generating overwhelming data. For highly competitive categories or during major campaigns (product launches, PR pushes), consider daily monitoring of your most critical prompts. Monthly monitoring is the minimum viable cadence.
Should I monitor different AI platforms separately? #
Yes. ChatGPT, Claude, Gemini, and Perplexity can give meaningfully different recommendations for the same query. Our data shows up to 40% variation in brand mentions across platforms. Track each platform separately to identify platform-specific optimization opportunities. Some brands perform much better on certain platforms—understanding this can help prioritize where to focus improvement efforts.
How do I know which prompts matter most for my business? #
Prioritize by purchase intent and market size. Category queries (“best CRM for startups”) typically have higher business value than educational queries (“what is a CRM”). Interview your sales team about what questions prospects commonly ask. Analyze your search console data for high-converting queries and adapt them to conversational format. Focus on queries where appearing would directly impact your pipeline.
What tools should I use for prompt monitoring? #
Use AI Visibility Monitor for systematic tracking across platforms. For manual spot-checking, simply run your prompts through each AI platform directly. Track results in a spreadsheet or dedicated dashboard. Key features to look for in monitoring tools: multi-platform support, trend tracking, competitor benchmarking, and alert notifications for significant visibility changes.
How long until I see results from prompt-targeted optimization? #
Timeline varies by optimization type. Content structure improvements can show results within 2-4 weeks for AI systems with browsing capabilities. Citation and authority building takes 3-6 months to influence AI training data and recommendations. Set realistic expectations: track weekly, but evaluate trends over 4-8 week periods rather than expecting immediate changes.
Conclusion: Make Monitoring a Habit #
Strategic prompt monitoring is the foundation of effective AI visibility optimization. Without understanding how AI systems currently describe your brand and recommend (or don't recommend) you in key queries, optimization efforts are shots in the dark.
Build your prompt library systematically, covering branded, category, competitor, and problem-solution queries. Establish a consistent monitoring cadence—weekly is ideal. Track the right metrics: not just whether you're mentioned, but your position, sentiment, and accuracy. Most importantly, connect monitoring results to specific optimization actions.
The brands that win in AI visibility treat monitoring as an ongoing program, not a one-time audit. Start with your most critical 20-30 prompts, establish your baseline, and expand from there. Every week of consistent monitoring builds the data foundation you need to optimize effectively.
Product Manager at Seenos.ai. Pioneer in AEO research since 2024, exploring the convergence of SEO and GEO (Generative Engine Optimization). Led multiple AI-powered content optimization projects that achieved 300%+ citation increases in ChatGPT and Perplexity.