🤔 The Question Every SEO Needs to Answer
Here's something that's been bugging me for months: when does ChatGPT actually search the web?
If the AI doesn't search, it's pulling from training data - which could be months old. Your latest content? Invisible. Your updated pricing page? Doesn't exist. But if it DOES search, you suddenly have a shot at getting cited.
So I built an experiment to find the triggers. And the data was NOT what I expected.
In this post, I'm breaking down exactly what makes ChatGPT reach for the search button - and how you can use these insights to get your brand cited by AI.
🧪 The Experiment
I used Python and the OpenAI Responses API to test 24 prompts across 4 dimensions. Each dimension had paired prompts - one designed to trigger search, one designed NOT to.
The dimensions:
| Dimension | Trigger Prompt | Non-Trigger Prompt |
|---|---|---|
| Recency | "Best CRM tools right now" | "Best CRM tools" |
| Brand Familiarity | "What is Strique?" | "What is Salesforce?" |
| Specificity | "HubSpot's pricing for startups in 2025?" | "Tell me about HubSpot" |
| Comparison | "Monday.com vs Asana" | "What is Monday.com?" |
For each prompt, I tracked:
- Did it search? (yes/no)
- How many search queries? (the AI often fires multiple)
- How many sources retrieved? (total pages pulled)
- Answer length (character count)
- Citations used (links in final answer)
The goal? Find predictable patterns in when the AI goes hunting vs. when it relies on training data.
📊 The Results
Here's where it gets interesting. Some hypotheses held up perfectly. Others completely fell apart.
1️⃣ Brand Familiarity = Clean Binary Signal
This one worked exactly as expected.
| Prompt | Searches | Sources |
|---|---|---|
| "What is Salesforce?" | 0 | 0 |
| "What is Strique?" | 2 | 9 |
| "What is HubSpot?" | 0 | 0 |
| "What is Folk CRM?" | 3 | 12 |
| "What is Slack?" | 0 | 0 |
| "What is Pumble?" | 2 | 8 |
✅ 3/3 pairs confirmed. If ChatGPT doesn't know your brand, it WILL search. If it knows you, it relies on training data.
The Insight: This is huge for emerging brands. The AI's "I don't know you" response is actually your advantage - it forces a fresh web lookup where you can control the narrative.
2️⃣ Comparison Queries ALWAYS Triggered Search
Every single comparison triggered search. No exceptions.
| Prompt | Searches | Sources |
|---|---|---|
| "What is Monday.com?" | 0 | 0 |
| "Monday.com vs Asana" | 2 | 15 |
| "What is Notion?" | 0 | 0 |
| "Notion vs Coda" | 4 | 22 |
| "What is Airtable?" | 0 | 0 |
| "Airtable vs Smartsheet" | 3 | 18 |
✅ 3/3 pairs confirmed. The moment users pit brands against each other, the AI goes hunting for fresh data.
Comparison queries also produced the highest source counts - pulling 15-22 sources compared to 8-12 for other search-triggered queries.
The Insight: Comparison content is a citation goldmine. The AI fires 2-5x more searches for "X vs Y" queries than single-entity questions.
3️⃣ Recency Words Don't Matter (Wait, What?)
This one broke my brain.
I expected "Best CRM tools right now" to trigger search while "Best CRM tools" would pull from training data.
Wrong.
Both triggered search. Every time. Why? Because ChatGPT auto-injected "2025" into its search queries even when I didn't ask for it.
The AI treats ALL recommendation queries as needing fresh data. It doesn't wait for you to say "right now" - it assumes you want current information.
❌ Hypothesis failed. But in the most useful way.
The Insight: You don't need to stuff "2025" or "right now" into your prompts. The AI is already looking for fresh content. Your job is to BE that fresh content.
4️⃣ Phrasing Matters More Than I Thought
Here's a weird one.
| Prompt | Searches | Sources |
|---|---|---|
| "What is HubSpot?" | 0 | 0 |
| "Tell me about HubSpot" | 4 | 31 |
❌ Hypothesis failed - but in an interesting way.
"What is X?" signals a definition request. The AI feels confident answering from training data.
"Tell me about X" signals "give me everything." That triggers a deep dive with multiple searches and massive source pulls.
The Insight: The phrasing of user queries changes everything. "Tell me about" is essentially asking for a research report, which forces search.
🧠 What This Means for AEO/GEO
Let's translate this data into strategy.
Search-triggered responses averaged:
- 4.5 search queries per prompt
- ~4,200 characters in the answer
- 5-65 sources retrieved
Non-search responses averaged:
- 0 search queries
- ~2,100 characters
- 0 sources
The difference is massive. Search-triggered queries produce answers that are twice as long and actually cite sources. Non-search queries rely entirely on training data that could be 6+ months old.
Here's why this matters: if you're not triggering a search, you literally cannot be cited.
Your content could be perfect. Your page could be fully optimized. But if the AI decides it already "knows" the answer, your page never enters the conversation.
🛠️ The Playbook
Based on this data, here's exactly what to do.
For Emerging Brands
Your obscurity is actually an advantage.
- ✅ The AI WILL search for you - it doesn't know you yet
- ✅ Optimize for the exact queries the AI runs (brand name + category keywords)
- ✅ Make your site THE definitive source for what you do
- ✅ Build out comparison pages positioning yourself against known alternatives
The AI's lack of familiarity forces it to find you. Make sure what it finds is good.
For Established Brands
You have a problem you might not know about.
- ⚠️ The AI might NOT search for basic queries about you
- ⚠️ It's relying on training data that could be outdated
- ✅ Create "vs competitor" content before competitors do
- ✅ Force searches by building pricing and feature comparison pages
- ✅ Keep your core pages fresh - update dates, current stats, recent features
If ChatGPT thinks it knows you, it won't look. You need to give it reasons to look.
For Everyone
Regardless of brand size, these tactics apply:
1️⃣ Build comparison pages. "X vs Y" queries trigger 3-5x more searches than single-entity queries. Create content for every real competitor comparison.
2️⃣ Year-stamp your content. The AI is actively looking for "2025" in search results. Put dates on your pages.
3️⃣ Test your own brand. Right now, go prompt ChatGPT: "What is [YourBrand]?" Does it search? If not, what's it saying about you? Is it accurate?
4️⃣ Target specific, detailed queries. Generic "about" pages don't trigger search. Pricing pages, feature comparisons, and technical details do.
5️⃣ Monitor for stale citations. AI search often relies on indexes like Bing that may be out of date. Check what URLs are being surfaced for your brand queries.
💡 Pro Tip
Here's something most people miss: ChatGPT's search behavior is predictable.
Unknown brands + comparison queries = search triggered Known brands + simple questions = training data only
Once you understand this, you can reverse-engineer your content strategy. Don't just optimize for Google. Optimize for the AI's decision tree.
The brands winning at AEO in 2025 are the ones who understand when the AI reaches for search - and position themselves to be found when it does.
The Bottom Line
The AI's decision to search isn't random. It follows clear patterns:
- Brand unfamiliarity forces search
- Comparison queries always trigger search
- Specific questions (pricing, features) trigger search
- Recency words don't matter - the AI assumes freshness anyway
- Phrasing ("tell me about" vs "what is") changes behavior
If you're building an AI SEO strategy, start here. Test your own brand. Build comparison content. Keep your pages fresh.
The search box isn't optional anymore. It's how AI learns about you.
CHEERS!