How do you find out which prompts trigger (or don't trigger) your brand in AI? Sharing my discovery process

This is THE challenge everyone faces when they start tracking AI visibility. You’re not alone.

The breakthrough for me was realizing Google Search is the prompt discovery goldmine:

1. People Also Ask (PAA) - These are literally the questions users ask. When you search for something on Google, those expanding question boxes? Each one is a potential AI prompt. Users ask AI assistants the same questions.

2. Related Searches - At the bottom of Google results. These show how users explore topics adjacent to your main keywords.

3. Autocomplete Suggestions - Start typing in Google and note what comes up. These are high-volume query patterns.

The manual version: Search your main topics on Google, screenshot all PAA questions and related searches, create prompts from them.

The automated version: Am I Cited does this automatically. When you monitor any prompt that includes Google search, it captures all PAA questions and related searches, then surfaces them as suggestions for new prompts. One-click to add them to your monitoring.

The discovery compounds - more prompts you monitor, more suggestions get discovered.

Let me share my systematic approach. I call it the “Prompt Expansion Framework”:

Level 1: Your Known Keywords Start with your brand, product names, and main category terms. These are table stakes.

Level 2: User Intent Variations For each Level 1 term, explore:

• “Best [category]”
• “How to choose [category]”
• “[Category] vs [category]”
• “[Category] for [use case]”
• “Is [brand] good for [use case]”

Level 3: Adjacent Questions This is where Google PAA shines. Each PAA question you find leads to more questions. It’s a rabbit hole of user intent.

Level 4: Long-tail Discovery Combine use cases + features + situations. “Best project management tool for remote teams with budget constraints” - specific, but these are exactly what AI gets asked.

The key insight: You’re not just tracking your brand. You’re tracking every question where your brand SHOULD appear. That’s a much bigger universe than most people realize.

From a data perspective, here’s what I’ve learned about prompt patterns:

High-value prompt indicators:

• Questions that appear in multiple PAA boxes (high search volume)
• Prompts where competitors get mentioned but you don’t (gap opportunities)
• Questions with commercial intent (“best,” “recommend,” “should I use”)

Lower-value prompts to deprioritize:

• Very generic questions (too broad to get specific brand mentions)
• Highly technical queries (unless that’s your niche)
• Questions already dominated by Wikipedia-style answers

I use Am I Cited’s suggestion occurrence feature to prioritize. If a suggestion appears 10+ times across my monitored prompts, it’s clearly important to my audience.

Pro tip: Don’t add every suggestion. Be strategic. Quality coverage beats quantity.

Running an e-commerce site, the prompt discovery aspect changed everything for us.

My specific example: We sell ergonomic office furniture. Started tracking “best ergonomic chair” type prompts. Standard stuff.

Through PAA discovery, we found prompts like:

• “What chair do programmers recommend”
• “Ergonomic setup for standing desk hybrid”
• “Chair for back pain from gaming”

These were goldmines. Different audience segments we hadn’t explicitly targeted.

The bulk add feature was key - found 15 relevant suggestions in one session, added them all with the same tag and schedule. Would have taken forever manually.

Now we track 120+ prompts across different user segments. Our AI visibility coverage went from maybe 30% of relevant queries to closer to 80%.

Great discussion. Let me add some context on WHY this discovery approach works:

AI systems are trained on search patterns

The questions in Google’s People Also Ask and related searches reflect:

• Actual user behavior
• Natural language patterns
• Common query structures

When users ask AI assistants questions, they use similar phrasing. The PAA questions are essentially a preview of what people will ask ChatGPT, Perplexity, etc.

The virtuous cycle:

1. Monitor prompts with Google Search integration
2. Discover new prompts from PAA/related searches
3. Add relevant ones to monitoring
4. Those new prompts discover MORE suggestions
5. Your coverage expands continuously

I’ve seen brands go from 20 prompts to 300+ over 6 months using this approach. The key is consistency - check suggestions weekly and add the relevant ones.

Warning: Don’t ignore suggestions just because they seem tangential. Sometimes the best opportunities are in adjacent topics you hadn’t considered.

We’re a small startup so here’s the scrappy version for anyone on a budget:

Manual PAA mining (free but time-consuming):

1. Create a list of your top 20 keywords
2. Search each on Google in incognito
3. Click through every PAA question (they expand to reveal more)
4. Document all questions in a spreadsheet
5. Search the PAA questions themselves (more PAAs appear)
6. Repeat weekly

After a month you’ll have 100+ prompt ideas.

When to upgrade: When the manual process takes more than 2-3 hours weekly, automated tools pay for themselves. I switched to Am I Cited when I realized I was spending half a day just on prompt discovery.

The auto-suggestion feature now saves me probably 10 hours a month, and catches things I would have missed.

We manage AI visibility for clients across different industries. Here’s what we’ve learned about prompt discovery:

By industry - what works:

E-commerce: Product comparison prompts, “best X for Y” patterns, “X vs Y vs Z” comparisons. PAA here is gold.

B2B SaaS: Problem-solution prompts, feature comparison, integration questions. Related searches often reveal competitor positioning.

Local services: Location-specific variations, “near me” patterns (less relevant for AI but still important), review/reputation questions.

Finance/Legal: Compliance questions, “is X legal in Y,” process explanations. High-value but competitive.

Our workflow:

1. Set up initial prompts with Google search enabled
2. Let it run for 2 weeks to gather suggestions
3. Review suggestions weekly with client
4. Batch add relevant ones (usually 10-20 per week initially)
5. Continue cycle - discovery never stops

The clients who engage with suggestions consistently outperform those who just “set and forget.”

Adding a product perspective here. When I joined my company, they were tracking 15 prompts. That’s it. For a product with 50+ features and dozens of use cases.

The discovery process revealed:

• 200+ unique questions users actually ask about our category
• 40+ competitor comparison queries we were invisible in
• Feature-specific questions we’d never considered (“does X have Y integration”)

What surprised me most: The long-tail prompts often had MORE visibility opportunity. Generic “best CRM” - super competitive. “Best CRM for real estate teams with follow-up automation” - we could actually win that.

My advice: Don’t limit yourself to branded terms. The biggest opportunity is in category and use-case questions where you SHOULD appear but currently don’t.

The suggestion discovery feature basically does keyword research for AI visibility. Invaluable.

This thread is incredibly helpful. Major insights I’m taking away:

Immediate actions:

1. Enable Google search integration on my monitored prompts (was only doing AI platforms)
2. Review the PAA/related search suggestions that are probably already building up
3. Set up a weekly process to review and add relevant suggestions

Strategic shifts:

• Thinking beyond branded terms to category and use-case questions
• Understanding that discovery is ongoing, not a one-time exercise
• Using occurrence data to prioritize which suggestions to add

The meta-realization: I was limiting myself to prompts I could think of. The real opportunity is in prompts users actually ask - which is much broader and different than what marketers imagine.

Thanks everyone. Will report back after a month of expanded tracking.