The Invisible Agency Problem

TL;DR: Most marketing agencies are invisible to AI search engines like ChatGPT, Claude, and Perplexity. After testing 50+ queries across these platforms, I discovered the exact factors that determine which agencies get recommended - and why traditional SEO doesn't matter anymore.

When a potential customer asks ChatGPT "What's the best marketing agency for small businesses?" - does your company get mentioned?

Most marketing agencies assume they're visible online because they rank well on Google, but in the age of AI, search works completely differently. I spent 3 weeks systematically testing this to find out which agencies actually get recommended - and more importantly, why.

I ran 50+ different marketing agency queries across ChatGPT, Claude, and Perplexity, then dug deep into why certain companies kept getting cited while others (even well-known ones) remained invisible.

The patterns I discovered will change how you think about online visibility in the age of generative AI.

🔬 The Testing Process

To understand how AI systems make recommendations, I ran a systematic experiment over three weeks. Here's exactly what I did:

Phase 1: Query Testing

I tested queries like:

• "Best marketing agencies for small businesses"

• "Affordable marketing agencies"

• "Marketing agencies with proven results"

...across three major AI platforms: ChatGPT, Perplexity, and Claude. Each query was run in fresh incognito conversations to avoid bias from previous responses.

Phase 2: Deep Dive Analysis

From the initial responses I was able to gain some insight into citation patterns, but I didn't stop there. For every company that got cited, I drilled down with the AI to uncover its decision-making process.

Follow-up questions like:

• "Why did you choose [Company X] specifically?"

• "What makes them better than other options?"

• "What parts of their website helped you decide?"

...revealed the actual reasoning behind AI recommendations - not just speculation.

Phase 3: Competitive Analysis

Then came the detective work. I systematically analyzed the websites of cited companies versus their competitors who didn't get mentioned, looking for patterns in everything from pricing displays to case study formats to contact information placement.

The results were striking. Certain factors appeared repeatedly in the AI's explanations, while traditional SEO signals seemed to matter much less than expected.

📊 Key Findings

1 - 💰 The Pricing Transparency Factor

Winner by a landslide

Across all three platforms, transparent pricing was the strongest predictor of AI citations. When I asked follow-up questions about why certain agencies were chosen, AI systems consistently mentioned phrases like:

• "Clear pricing structure"

• "Transparent costs"

• "Upfront pricing information"

The reasoning makes sense: AI systems want to recommend businesses that help users make decisions without hidden surprises. When an agency displays clear pricing tiers, potential clients can immediately assess budget fit before reaching out.

Success Story: Lyfe Marketing

When I asked ChatGPT why it cited Lyfe Marketing, it specifically mentioned their "transparent pricing structure."

What they do right:

• Clear, tiered pricing displayed prominently

• No "contact for pricing" barriers

• Easy budget assessment for prospects

  
  

Missed Opportunity: Macedo Marketing

Compare this to a competitor that wasn't cited: Macedo Marketing, which offers custom pricing without publicly available rates. While custom pricing isn't inherently bad, AI systems seem to favor the transparency that helps them confidently recommend services to users.

2 - 📈 Case Studies Need Real Numbers, Not Vague Claims

Specificity wins every time

Case studies were one of the most important factors in AI recommendations, consistently appearing as sources of citation information for almost every agency in my queries. But there was a key distinction: not all case studies are equal in the eyes of AI systems.

Specific metrics in case studies were consistently mentioned in AI justifications for citations. When I asked follow-up questions about agency recommendations, AI systems repeatedly referenced phrases like:

• "Proven ROI results"

• "Measurable outcomes"

• "Specific performance metrics"

What Works vs. What Doesn't

The logic is straightforward: AI systems want to recommend businesses that can demonstrate concrete value rather than make empty promises. Numbers provide the kind of evidence AI systems can confidently cite to users.

3 - ⭐ Third-Party Validation Carries Serious Weight

External proof trumps self-promotion

One pattern that surprised me was how often AI systems referenced external validation when explaining their choices. Reviews, awards, and third-party recognition weren't just nice-to-haves - they were frequently the deciding factor between similar agencies.

The Validation Hierarchy That AI Systems Trust:

1. Review Platform Ratings (Clutch, Google Reviews, G2)

2. Industry Awards & Recognition

3. Third-party case studies & mentions

4. Client testimonials with verifiable details

   
   

Success Story: WeDiscover

When Perplexity recommended WeDiscover, it specifically noted their "excellent client reviews and industry recognition."

What they built:

• Strong Clutch profile with detailed client feedback

• Industry awards (Best PPC Agency in Europe)

• High ratings across multiple review platforms

• Verifiable client success stories

• 
  

Missed Opportunity: Bark.London

Meanwhile, agencies I found that weren't getting cited often had minimal third-party presence. Take Bark.London, which appears on some industry lists but has very little external validation - mostly just testimonials on their own website with few client reviews on independent platforms.

The takeaway is clear: AI systems trust businesses that others have publicly validated, not just companies that make claims about themselves.

4 - 📞 The Contact Trust Signal - It's All About Looking "Real"

Legitimacy markers that AI systems notice

Here's something that might seem obvious but turned out to be vital: how "real" and established a business appears through its contact information. I started noticing this pattern when AI systems kept using phrases like:

• "Established business"

• "Legitimate company"

• "Professional team information"

The Trust Signals That Matter:

The agencies getting cited weren't just easier to contact - they looked like actual businesses you could walk into or call. When I pressed Claude for specifics about why it recommended certain agencies, it often mentioned factors like "clear business presence" and "professional team information."

It makes sense: if you're an AI system recommending a business to someone, you want to feel confident that business actually exists and can be reached.

🚀 What This Means for Your Business

The Fundamental Shift

This isn't traditional SEO anymore. AI systems don't just crawl and rank - they evaluate and recommend. They're looking for businesses they can confidently suggest to users, which means entirely different optimization factors matter now.

The Numbers That Matter

While most companies are still focused on Google rankings, a fundamental shift is happening:

• ChatGPT: 100+ million users asking for business recommendations

• Perplexity: Rapidly growing search volume

• Claude: Being integrated into more workflows daily

These aren't future trends - they're current reality.

The First-Mover Advantage Window

The businesses optimizing for AI citations now will have a significant first-mover advantage. While competitors scramble to understand why they're invisible to AI search, early adopters will already be capitalizing on this growing source of qualified leads.

⚠️ The window for easy wins is closing fast. As more businesses catch on to AI search optimization, the competition for citations will intensify. The transparency, specificity, and credibility signals that work today might become baseline requirements tomorrow.

✅ What You Can Do Right Now

Immediate Action Items (This Week):

1. 💰 Audit Your Pricing Page

Question: Can visitors see specific costs, or do they have to contact you?

Action Steps:

• [ ] Display at least starting prices or price ranges

• [ ] Create clear pricing tiers if applicable

• [ ] Remove "contact for pricing" barriers where possible

• [ ] Add pricing FAQs to address common questions

2. 📊 Review Your Case Studies

Question: Do they include specific metrics and measurable outcomes?

Action Steps:

• [ ] Replace vague claims with specific numbers

• [ ] Add ROI percentages, revenue figures, or performance metrics

• [ ] Include before/after comparisons with real data

• [ ] Create at least 3 detailed case studies with measurable results

3. ⭐ Check Your Third-Party Presence

Question: When did you last update your review profiles?

Action Steps:

• [ ] Claim and optimize your Clutch profile

• [ ] Respond to recent Google Reviews

• [ ] Update your LinkedIn company page

• [ ] Submit for relevant industry awards

• [ ] Encourage satisfied clients to leave detailed reviews

4. 📞 Evaluate Your Contact Information

Question: Is it easy to find your phone number, address, and team details?

Action Steps:

• [ ] Add direct phone number to header/footer

• [ ] Display full business address prominently

• [ ] Create team page with photos and real names

• [ ] Add multiple contact methods (phone, email, chat)

• [ ] Include office photos or virtual tour if applicable

🔍 Want to Test Your AI Visibility?

I'm continuing this research across different industries and working with select businesses to optimize their AI search visibility.

Try this quick test:

1. Open an incognito window

2. Ask ChatGPT: "What are the best [your service type] for [your target market]?"

3. See if your company gets mentioned

4. If not, you're invisible to 100M+ potential customers

If you're curious how your company performs in AI searches or want to discuss what I'm discovering, feel free to reach out.

📧 Questions about AI search optimization? Drop me a line at jerryksoftware@outlook.com

💼 Connect with me on LinkedIn