Issue #90: How to Show Up in ChatGPT, Claude, Gemini

Good morning.

I'm watching two companies sell the exact same product.

One shows up in 85% of AI search results. The other (despite ranking #1 on Google for their category) appears in less than 10%.

Same category. Same target customer. Completely different futures.

The gap is semantic. And if you're not tracking it, you're invisible to half your market.

A new layer of search has arrived. Not replacing Google but layering on top of it. Your prospects are asking these tools for recommendations. And the answers they're getting have almost nothing to do with your Google rank.

The data backs this up: only 12% of URLs cited by ChatGPT, Perplexity, and Copilot rank in Google's top 10 results. 80% of AI citations don't even rank in Google's top 100 for the original query.

The brands winning this game aren't the ones with the most backlinks. They're the ones that control the narrative, the sentiment, and the entity relationships in the data AI models consume.

Welcome to GEO: Generative Engine Optimization. The game you didn't know you were playing. And the gap that's about to separate winners from ghosts.

— Sam

IN TODAY’S ISSUE 🤖 

• The GEO Gap: Why Google rank no longer predicts AI visibility

• How AI Search Actually Works (the mechanism behind citations)

• The Citation Hierarchy: What AI platforms actually trust

• The Sentiment Filter: How Reddit threads override domain authority

• 10 Case Studies: Winners, losers, and surprises in AI search

• Entity SEO: The deeper game beyond content

• Technical GEO: The infrastructure layer most brands are missing

• The AI Visibility Stack: Tools and tactics to track your GEO performance

Let’s get into it.

The Split: SEO vs. GEO

For the last decade, you optimized for Google's crawler.

You built backlinks. You targeted keywords. You fought for position zero. 

And if you won that game, you assumed visibility was guaranteed.

That assumption just broke.

Because now there's a second game running in parallel. And the rules are completely different.

SEO (Search Engine Optimization) optimizes for how Google indexes your content.

GEO (Generative Engine Optimization) optimizes for how AI models reason about your brand.

Now, I think peopel are still arguing over whether it should be GEO or AISEO or AEO, or whatever.

It’s a waste of time, frankly. Focus on how to get mentioned and let people with too much time on their hands argue over words.

Here's the difference in practice:

Zoho CRM

• Google rank for "best CRM software": Top 3

• AI search visibility (ChatGPT, Perplexity, Gemini): Bottom 20%

• The reason: Reddit threads call the UI "clunky." AI reads those threads, weights user sentiment heavily, and recommends competitors instead.

Linear (Project Management)

• Google rank for "project management software": Top 10

• AI search visibility: #1 recommendation for "modern" teams

• The reason: Thousands of Reddit and Twitter threads describe it as "fast," "keyboard-first," and the "anti-Jira." AI repeats this positioning verbatim.

Same category. Opposite outcomes.

The gap is about controlling what the AI reads about you—not just what you publish about yourself.

How AI Search Actually Works

Before we go further, you need to understand the mechanism. AI search doesn't work like Google.

The Two Modes of AI Response

Model-Native Synthesis

When you ask ChatGPT a question, it generates answers from patterns learned during training. This is fast and coherent, but the model can only cite what it "remembers" from training data, which has a cutoff date and can hallucinate.

Retrieval-Augmented Generation (RAG)

This is where GEO lives. When ChatGPT, Perplexity, or Gemini needs current information, they:

1. Take your query

2. Run a real-time web search (ChatGPT uses Bing, Perplexity has its own index, Gemini uses Google)

3. Retrieve the top 5-10 sources

4. Synthesize a response grounded in those retrieved documents

5. Cite the sources they used

This is critical to understand: AI visibility is a two-stage game. First, you need to be retrieved by the underlying search engine. Then, you need to be selected by the AI as cite-worthy.

Perplexity's founding principle captures this perfectly: "You are not supposed to say anything that you didn't retrieve."

Why You Should Pay Attention To All This

Ranking in Bing matters for ChatGPT. ChatGPT retrieves live information primarily through Bing's search API. If you're not indexed in Bing, you won't appear in ChatGPT responses. This is the most overlooked factor in GEO.

Freshness is weighted heavily. RAG systems prioritize recently updated content because they're trying to reduce hallucination risk. Content updated within 30 days gets 3.2x more AI citations than older content.

Structure determines citation probability. AI systems parse content looking for clear, extractable answers. Content structured as question-answer pairs performs dramatically better in retrieval algorithms.

The Citation Hierarchy: What AI Platforms Actually Trust

I analyzed citation patterns across ChatGPT, Google AI Overviews, and Perplexity using data from Profound's study of 680 million citations (August 2024 – June 2025). 

Here's what the data shows:

ChatGPT's Source Preferences

ChatGPT's pattern: Encyclopedic, authoritative sources. Wikipedia dominates because it provides canonical, structured content with clear attribution chains. The model avoids user-generated forum content unless queries specifically request community opinions.

Google AI Overviews

Google's pattern: User-generated content and multimedia dominate. Google is pulling heavily from platforms where real humans share unfiltered experiences. YouTube transcripts are being mined for step-by-step instructions.

Perplexity

Perplexity's pattern: The most Reddit-dependent of all platforms. Community-driven, user-generated content is the backbone of Perplexity's citation strategy. It's also the most likely to send referral traffic—users on Perplexity click through to sources at 6.2x the rate of other platforms.

The Pattern Across All Platforms

Wikipedia and Reddit are the twin pillars of AI search. Wikipedia provides the factual anchor. Reddit provides the sentiment filter. Together, they shape more AI answers than any corporate content strategy.

Commercial .com domains still dominate total volume. Over 80% of all AI citations come from .com domains. But within that, the hierarchy favors established publishers, review aggregators, and official documentation.

Newer TLDs like .ai are gaining traction. Tech-focused domains ending in .ai show notable presence despite being newer—early signal of emerging opportunity.

The Sentiment Filter: How Reddit Shapes AI Answers

This is where it gets dangerous for legacy brands.

AI models treat Reddit threads and forum discussions as expert testimony. Not noise—signal.

The Mechanism

When a user adds qualifiers like "actually use," "honest review," or "worth it," the AI shifts from citing official rankings to citing Reddit threads.

Generic query ("Best CRM"): Reddit = 15% of reasoning Nuanced query ("Is HubSpot worth it?"): Reddit = 60-70% of answer

The September 2025 Disruption

Something important happened in September 2025. Google removed the num=100 parameter from its search URLs, a technical change that blocked AI companies from easily scraping the top 100 results.

ChatGPT's Reddit citations dropped from ~12% to ~1% almost overnight. Wikipedia's share increased to fill the gap.

What this means for you: The citation landscape is volatile. Platforms are actively fighting over access to data sources. Reddit remains critical (it's still #1 on Perplexity and Google AI Overviews), but diversification matters more than ever.

Real Examples of Sentiment Override

Typeform

Typeform ranks #1 on Google for "online form builder." But when you ask ChatGPT for the best form builder, it often recommends Tally or Google Forms instead—with a warning that Typeform is "expensive" and "locks basic features behind paywalls."

Where did that warning come from? Reddit threads. Hundreds of them. Users complaining about pricing, cancellation friction, and feature gates.

The AI read those complaints and encoded them as fact. Now it actively steers users away from Typeform unless they specifically ask for "advanced" features.

Jira

Jira dominates Google for "agile project management." But in AI search, it's only recommended for "enterprise" use cases. For startups, the AI suggests Linear, Notion, or ClickUp.

Why? The volume of "how to configure Jira permissions" and "Jira is too complex" content signals to the AI that the tool is difficult. The AI interprets complexity as a negative unless enterprise scale is specified.

Norton Antivirus

Norton ranks #1 on Google for "antivirus software." But when you ask AI for the "best lightweight antivirus," it recommends Bitdefender or Windows Defender instead.

Why? Sentiment decay. While Norton pays for top Google slots, AI models are trained on Reddit threads where sentiment is overwhelmingly negative ("bloatware," "impossible to cancel," "slows down PC"). The AI treats this as fact.

The Pattern

User sentiment overrides domain authority. If your category has a "cheaper alternative" ecosystem, the AI is reading those comparison threads. And if users prefer the alternative, the AI will too.

The Case Study Database

Let me show you exactly how this plays out across real brands.

The Winners: Brands Dominating AI Search

1. HubSpot (CRM / Marketing Platform)

• AI Visibility: 85% share of voice in CRM queries

• Google Rank: #1 or #2 for primary keywords

What they do right:

They publish original research. The "State of Marketing 2025" report contains stats that bloggers cite constantly. When AI models need to back up a claim about email open rates or marketing budgets, they cite HubSpot's data.

They own integration documentation. Thousands of pages explaining how to connect HubSpot to Zapier, Slack, OpenAI, and every other tool in the modern stack. When someone asks "How do I automate my CRM?", HubSpot appears because they literally documented the answer.

The lesson: Be the source AI cites to support its own arguments. Original data + exhaustive how-to content = citation dominance.

2. Linear (Project Management)

• AI Visibility: #1 for "modern" or "fast" teams

• Google Rank: Top 10, but often below Jira/Asana

What they do right:

They own the sentiment. Reddit and Twitter are flooded with threads calling Linear the "anti-Jira"—fast, opinionated, keyboard-first. The AI doesn't just read these threads. It repeats them. Word for word.

They update constantly. Their changelog is updated weekly with dense, specific feature descriptions. That "freshness" signal keeps them top-of-mind for any query mentioning "2025" or "AI features."

The lesson: If your users love you vocally, AI amplifies their voice. Cultivate advocates in the places AI scans most (Reddit, Twitter, Product Hunt).

3. Zapier (Automation / iPaaS)

• AI Visibility: The default connector (mentioned in 90% of automation queries)

• Google Rank: #1 for "automation tools"

What they do right:

They own the how-to monopoly. Zapier has published "How to connect [App A] to [App B]" guides for 6,000+ app pairings. When you ask an AI "How do I automate X?", the AI has to cite Zapier—because they're the only source with a tutorial for that specific workflow.

The lesson: Programmatic SEO at scale creates a citation moat. If you document every possible use case, you become impossible to not cite.

The Improvers: Brands Closing the Gap

4. Clay (Data Enrichment / Sales)

• AI Visibility: Jumped from "unknown" to top recommendation for B2B lead gen

• Google Rank: Low domain authority vs. ZoomInfo

What changed:

User-generated documentation. Clay's community shares "Claybooks"—detailed workflow templates on social media. The AI scrapes these templates, recognizes them as high-value resources, and cites them for "how to scrape leads" queries.

The lesson: Community-created content scales faster than brand content. Enable users to document your tool publicly.

5. Beehiiv (Email / Newsletters)

• AI Visibility: Beating Substack for "monetization" queries

• Google Rank: Strong, but newer domain than Mailchimp/Substack

What changed:

They own specific keywords. "Ad Network." "Boosts." "Newsletter growth." When someone asks "How to grow a newsletter," AI cites Beehiiv because it's the only brand strongly associated with growth features. Substack is associated with "writing." Mailchimp with "emails." Beehiiv with "revenue."

The lesson: Own a specific outcome. AI needs clear entity relationships to generate confident recommendations.

The Losers: Strong Google Rank, Weak AI Visibility

6. Zoho CRM

• Google Rank: Top 3 for "best CRM software"

• AI Visibility: Barely mentioned (bottom 20%)

Why they're invisible:

Sentiment poisoning. While Zoho ranks high on Google due to massive feature breadth and affordability, Reddit threads consistently criticize the UI as "clunky" or "unintuitive." AI reads this as disqualifying for "best user experience" queries.

The nuance: Zoho Bigin (their SMB product) actually gets favorable citations from Perplexity because PCMag named it "Editor's Choice." The brand isn't uniformly invisible—just the flagship product.

The lesson: Negative sentiment overrides feature count. If users complain loudly enough, AI hears it as consensus.

7. Jira (Atlassian)

• Google Rank: #1 for "agile software"

• AI Visibility: Cited only for enterprise, discouraged for startups

Why they're struggling:

Complexity bias. The volume of "how to configure Jira" and troubleshooting content signals to AI that the tool is difficult. AI interprets this as a negative unless enterprise scale is explicitly mentioned.

The lesson: Too much troubleshooting content = perceived complexity. Balance technical docs with success stories and "quick start" content.

8. Vimeo (Video Hosting)

• Google Rank: Top 3 for "video hosting"

• AI Visibility: The "middle child" (no clear use case)

Why they're invisible:

Lack of outcome ownership. AI links YouTube to "reach/SEO" and Wistia to "marketing analytics." Vimeo is defined vaguely as "high quality player." Without a sharp use-case hook, AI can't slot it into a specific recommendation.

The lesson: Generic positioning = invisible in AI search. Own a specific job-to-be-done.

The Surprises: Brands Punching Above Their Weight

9. Tally (Form Builders)

• AI Visibility: #1 for "free Typeform alternative"

• Google Rank: Page 2-3 for generic "form builder" keywords

Why they punch up:

The value narrative. Tally's visibility is driven entirely by "Best Free Tools" listicles and Reddit threads. AI has learned: Tally = "99% of Typeform features for free." That simple equation makes it the default answer for budget-conscious queries.

The lesson: If you can own the "alternative" positioning, you win the comparison query.

10. Lark (Productivity Superapp)

• AI Visibility: Rising contender in "Google Workspace alternative" queries

• Google Rank: Historically weak in US market

Why they punch up:

Aggressive listicle SEO. Lark flooded the web with articles like "10 Best Project Management Tools for 2025" (ranking themselves #1). Because these articles were fresh (late 2025), Gemini picked them up as current information.

The lesson: Freshness can temporarily override authority. Strategic content blitzes work if timed correctly.

Entity SEO: The Deeper Game

Everything we've discussed so far (content, sentiment, citations) sits on top of a deeper layer. 

AI doesn't think in keywords. It thinks in entities and relationships.

What Entities Are

An entity is any "thing" that AI systems can identify, categorize, and relate to other things: a person, brand, product, location, concept. 

Entities are the atomic units of meaning in Google's Knowledge Graph and every AI model's understanding of the world.

When Nike releases the Pegasus 41, it becomes a new product page on Nike.com and it  becomes an entity in Google's Shopping Graph, connected to "running shoes," "Nike," "marathon training," and hundreds of other nodes. The system knows it's a shoe before anyone optimizes a single keyword.

Why Entity SEO Matters for GEO

If your brand isn't a recognized entity, AI has no "hook" to associate you with queries.

When you search "Nike running shoes," Google isn't matching strings—it's connecting the Nike entity to the running shoes entity. AI systems do the same thing at scale.

Consider this: both "barnes and noble" and "bn" bring up a Knowledge Panel for Barnes & Noble. Google closely associates both search terms with the same entity. The brand has entity recognition regardless of how users type the query.

Entity relationships determine default recommendations.

When an AI podcast guest says, "I moved from Asana to Notion for task management," that competitive relationship gets encoded. AI learns: Asana and Notion are alternatives. When someone asks "What's an alternative to Asana?", Notion surfaces—not because of any SEO work, but because the entity relationship exists.

How to Build Entity Presence

1. Wikipedia and Wikidata

Wikipedia serves as ChatGPT's most cited source at 7.8% of total citations. Having a Wikipedia page (if notable enough) or robust Wikidata entries establishes your brand as a recognized entity.

Check your Wikidata presence. Does it include your industry, founding date, URL, social profiles, offerings, and partnerships? Competitors who invest here create more entity hooks for AI to reference.

2. Knowledge Graph Presence

Google's Knowledge Graph powers Knowledge Panels, AI Overviews, and entity understanding across search. Getting into the Knowledge Graph requires:

• Consistent NAP (name, address, phone) across the web

• Structured data (schema markup) on your website

• Mentions in authoritative sources that already have entity recognition

• Official social profiles linked and verified

3. Entity Linking in Your Content

Help AI understand which entities your content references. If you write about "Bronco," are you talking about the Ford SUV or a horse? Entity linking—connecting your content to recognized concepts in Wikidata or Google's Knowledge Graph—disambiguates meaning.

Schema markup makes these relationships explicit. Article schema with clear datePublished, Organization schema linking to your brand entity, Product schema connecting to your category—all of this helps AI "understand" your content's context.

4. Outcome Ownership

The brands winning in AI search don't just exist as entities—they own specific outcomes.

• HubSpot = "marketing automation for SMBs"

• Linear = "fast project management for developers"

• Beehiiv = "newsletter monetization"

Pick one job-to-be-done and dominate the entity relationship between your brand and that outcome.

Technical GEO: The Infrastructure Layer

Most brands focus on content and sentiment. They're missing the technical foundation that makes AI visibility possible.

llms.txt: The New Standard

Just as robots.txt tells search engine crawlers what to access, a new proposed standard called llms.txt helps AI systems understand which content to prioritize.

What it is: A plain-text file at yourdomain.com/llms.txt that provides a "table of contents" for AI crawlers—helping them skip ads, navigation, and noise to find your best content.

What to include:

• Primary content areas with summaries

• Authority signals (credentials, experience)

• Last updated dates

• Preferred citation language

• Links to key resources

Example structure:

# [Your Company Name]
> Brief description of your company and what you do.

## Primary Content Areas

### [Topic/Product 1]
- Location: /services/
- Summary: What this content covers
- Authority: Relevant credentials or expertise
- Last Updated: 2025-12-01

### [Topic/Product 2]
...

Current adoption: Still emerging, but early movers are implementing it. Some SEO practitioners report that sites with llms.txt see improved AI comprehension of their content structure.

AI Crawler Access

AI bots now account for ~20% of Googlebot's crawl volume. The major crawlers:

Critical checks:

1. Review your robots.txt. Are you accidentally blocking AI crawlers? Some sites blocked AI bots during the 2023-2024 copyright debates and forgot to update.
   

2. Most AI crawlers don't execute JavaScript. If your content loads dynamically via client-side rendering, AI crawlers may see nothing. Critical content must be server-side rendered or in the initial HTML response.
   

3. Page speed matters. AI crawlers are less patient than Googlebot. Sites loading under 2 seconds get preferential treatment from Perplexity.
   

4. Fix broken links and 404s. Broken links and inconsistent structure reduce citation probability.

Schema Markup: The Machine-Readable Layer

Sites with schema markup are 2-4x more likely to appear in AI Overviews.

Priority schema types for GEO:

• Article schema: Include datePublished and dateModified. Freshness signals matter.

• FAQ schema: FAQ pages perform exceptionally well in AI retrieval. The question-answer format mirrors how AI likes to extract and cite.

• Organization schema: Establish your brand as a recognized entity with official URLs, social profiles, and credentials.

• Product schema: Connect products to categories and brands in ways AI can parse.

• HowTo schema: Step-by-step content with proper markup gets cited for procedural queries.

Google and Microsoft both confirmed in 2025 that structured data makes content "machine-readable" and eligible for AI-driven features.

Bing Indexing: The Hidden Dependency

If you're not indexed in Bing, you won't appear in ChatGPT responses.

ChatGPT retrieves live information primarily through Bing's search API. Many brands obsess over Google rankings while neglecting Bing—and wonder why they're invisible in ChatGPT.

Action steps:

• Submit your site to Bing Webmaster Tools

• Verify indexing status

• Check for crawl errors specific to Bing

• Consider IndexNow for faster indexing of new content

Content Formatting That Works

Research shows specific formatting patterns get cited more often.

The "Short Answer + Deep Dive" Format

AI systems retrieve by looking for direct answers first, then context.

Structure that works:

1. Open with a direct, concise answer (2-3 sentences)

2. Follow with detailed explanation

3. Include supporting data and examples

This mirrors how AI likes to retrieve: grab the answer, cite the source.

Example:

Question: "What is the best CRM for small businesses?"

Weak opening: "Choosing a CRM is an important decision that depends on many factors including your budget, team size, and specific needs..."

Strong opening: "HubSpot CRM is the best free option for most small businesses. For sales-focused teams, Pipedrive offers better pipeline management at $15/user/month."

Structural Patterns That Increase Citations

• H2 → H3 → bullet point structures are 40% more likely to be cited

• FAQ sections perform exceptionally well

• Opening paragraphs that directly answer the query get cited 67% more often

• Data tables and original statistics get 4.1x more citations

• Pages loading under 2 seconds get preferential treatment

What to Avoid

• Keyword-stuffed content optimized for traditional search underperforms in AI retrieval

• Walls of text without clear structure

• Content that buries the answer after lengthy introductions

• Clickbait headlines that don't match content

The Traffic Reality: Why This Matters Now

AI search traffic is growing exponentially and converts dramatically better.

The Numbers

• Current AI traffic share: 0.15-1% of total web traffic (depending on industry)

• Growth rate: 527-700% increase from 2024 to 2025

• ChatGPT dominance: 77-80% of all AI referrals come from ChatGPT

• Perplexity: 15-20% of AI referrals (but highest referral efficiency—6.2x)

• Google sends 345x more traffic than all AI platforms combined—for now

The Quality Difference

This is where it gets interesting:

• AI visitors convert 4.4x to 23x better than organic search visitors

• AI traffic bounce rates are 23% lower than traditional traffic

• Session duration from AI referrals: 9-10 minutes average (vs. ~3 minutes for organic)

• Page views per session: 12% higher from AI traffic

Why? AI pre-qualifies intent. Users arrive further along in the decision journey. They've already used AI to research options, compare alternatives, and narrow choices before clicking through.

Platform Differences: How Each AI Answers Differently

Not all AI search engines work the same way. 

Here's how ChatGPT, Perplexity, and Gemini differ when answering "What's the best CRM for small businesses?"

ChatGPT (OpenAI)

The vibe: The "Modern Tech Stack" consultant.

Top recommendations:

• HubSpot (the freemium standard)

• GoHighLevel (AI agent marketing buzz)

• Folk (AI-native choice)

• Monday.com (flexibility)

Unique behavior: ChatGPT consumes high volumes of marketing Twitter and "Make Money Online" YouTube transcripts where GoHighLevel dominates. It leans toward tools with "AI buzz" and moves away from legacy enterprise unless specifically asked.

Citation preferences: Wikipedia (47.9%), Reddit (11.3%), news outlets, official documentation.

Perplexity (Pro Search)

The vibe: The aggregator/librarian.

Top recommendations:

• Zoho Bigin (specific distinction from Zoho CRM)

• Pipedrive (sales focus)

• Nimble (social media integration)

• Salesforce Starter (scalable option)

Unique behavior: Perplexity relies heavily on PCMag reviews. Since PCMag's late-2025 review explicitly names Bigin as Editor's Choice for small business, Perplexity picks up this nuance. Most "academic" answer—less likely to recommend hype tools, more likely to cite structured review data.

Citation preferences: Reddit (46.7%), YouTube, LinkedIn, industry publications.

Gemini (Google)

The vibe: The "Google Search" mirror.

Top recommendations:

• HubSpot (definitive #1)

• Monday.com (heavily advertised in Google Search)

• Zoho CRM

• Lark Suite (newer "superapp" entrant)

Unique behavior: Near-perfect reflection of current Google organic results. If it ranks Page 1 on Google, it's in Gemini's answer. Freshness matters heavily—Gemini picked up Lark's late-2025 SEO blitz because Google indexed their content recently.

Citation preferences: YouTube (18.8%), Reddit (21%), Google properties (23% combined), Forbes/Capterra.

Strategic Implications

• For ChatGPT visibility: Focus on Wikipedia presence, Bing indexing, and Reddit sentiment.

• For Perplexity visibility: Invest in review site rankings (PCMag, G2), community engagement, and UGC.

• For Gemini visibility: Traditional Google SEO still matters. Fresh content gets weighted heavily.

The AI Visibility Stack: Tools and Tactics

Here's how to track your GEO performance with the tools available today:

Monitoring Platforms

Free Tools

The Monthly Audit Process

Step 1: The Visibility Test

Query all three major AI platforms with your core category keywords:

• "Best [your category] for small businesses"

• "What's the best [your category] tool in 2025?"

• "[Your brand] vs [competitor]"

Screenshot the results. Document:

• Do you appear?

• Where do you rank?

• How are you described?

• Which competitors appear instead?

Step 2: The Sentiment Audit

Search Reddit for your brand name. Read the threads. That's what AI is reading.

Look for:

• Recurring complaints

• Feature requests

• Comparison discussions

• "Why I switched from X to Y" posts

These discussions are training data. If the sentiment is negative, the AI will encode that negativity into its recommendations.

Step 3: The Citation Trace

When AI mentions your brand, ask: "What sources did you use?"

Track which content gets cited:

• Your official docs?

• Third-party reviews?

• Reddit threads?

• Comparison articles?

This reveals your citation gaps. If AI never cites your blog, your blog isn't optimized for AI consumption.

Step 4: The Freshness Check

Review your top-performing content. When was it last updated?

If your best pieces are 18+ months old, update them:

• Change the year in the title ("2025" or "2026")

• Add a "What's New" section at the top

• Update stats, screenshots, pricing

• Add references to recent developments

Content updated within 30 days gets 3.2x more AI citations.

Step 5: The Technical Audit

• Is your site indexed in Bing? (Critical for ChatGPT)

• Are AI crawlers blocked in robots.txt?

• Is critical content server-side rendered?

• Do you have comprehensive schema markup?

• Does your site load in under 2 seconds?

The GEO Playbook: What to Do Now

Here's the tactical playbook.

For Established Brands (Losing AI Visibility)

Problem: You rank on Google but don't appear in AI search.

Fix:

1. Update your flagship content. Add "2025" or "2026" to titles. Refresh stats. The AI needs recency signals. Content updated within 30 days gets 3.2x more citations.
   

2. Document integrations. If your tool connects to other tools, write exhaustive how-to guides. "How to connect [Your Tool] to [Popular Tool]" for every major platform. This makes you cite-able when users ask workflow questions.
   

3. Cultivate positive sentiment. Encourage customers to share use cases on Reddit, Twitter, Product Hunt. User-generated content scales faster than brand content—and AI trusts it more.
   

4. Own a specific outcome. Vague positioning ("all-in-one platform") loses to specific outcomes ("best for lead generation," "fastest for small teams"). Pick one job-to-be-done and dominate it.
   

5. Check your Bing indexing. If you're not in Bing, you're invisible to ChatGPT. Submit to Bing Webmaster Tools immediately.
   

6. Implement schema markup. Article, FAQ, Organization, Product schemas. Sites with schema are 2-4x more likely to appear in AI Overviews.

For Rising Brands (Building AI Visibility)

Problem: You're new. Low domain authority. Not in the comparison tables yet.

Fix:

1. Target the "alternative" positioning. Write comparison content: "[Competitor] vs [Your Brand]." AI reads these to understand category relationships. If you explain why you're better for specific use cases, AI will repeat your positioning.
   

2. Publish original data. Even a small survey (100 respondents) gives you unique stats to cite. When bloggers reference your data, AI picks up those citations and attributes authority to your brand.
   

3. Get into the listicles. Reach out to PCMag, G2, Capterra. Offer demos. Get reviewed. AI weights comparison tables heavily—if you're not in them, you're invisible.
   

4. Build community documentation. Enable users to share templates, workflows, and case studies publicly. Clay's "Claybooks" are a perfect example. User-created content becomes training data.
   

5. Invest in Reddit authentically. Create an optimized profile, be transparent that you represent the brand, and follow the 90/10 rule: 90% non-promotional value, 10% product mentions. Reddit hates spam—but rewards genuine expertise.

For Everyone: The Minimum Viable GEO Strategy

This week:

• Query ChatGPT, Perplexity, Gemini with your category keywords

• Screenshot what they recommend

• Check if you appear

This month:

• Audit your sentiment footprint on Reddit

• Read every thread mentioning your brand

• Document recurring themes (positive and negative)

• Submit your site to Bing Webmaster Tools if not indexed

• Check robots.txt for AI crawler blocks

This quarter:

• Update your top 10 pieces of content with current dates and fresh examples

• Publish 3 comparison articles ("[Your Brand] vs [Competitor]")

• Document 5 integration workflows

• Implement schema markup on key pages

• Consider implementing llms.txt

The Citation vs. Traffic Paradox

One final reality check.

Even Wikipedia (the most-cited source across all AI platforms) saw an 8% decline in human pageviews despite being the #1 reference. 

Being cited doesn't automatically mean traffic.

The value of AI visibility is:

1. Brand awareness at decision moments. When someone asks "What's the best CRM?", appearing in the answer plants your brand in their consideration set—even if they don't click through immediately.
   

2. Trust signals when users do click. AI visitors convert 4-23x better because they arrive pre-qualified. The AI already vetted you.
   

3. Influence on downstream recommendations. AI models learn from patterns. The more you're cited, the more you'll continue to be cited. Citation momentum compounds.

This reframes success metrics. Track mentions and sentiment, not only referral clicks. The "AI Dark Funnel" means your true influence is larger than analytics show.

Quick Reference: The GEO Checklist

Technical Foundation

• Site indexed in Bing (critical for ChatGPT)

• AI crawlers not blocked in robots.txt

• Critical content server-side rendered

• Page speed under 2 seconds

• Schema markup implemented (Article, FAQ, Organization, Product)

• Consider implementing llms.txt

Content Optimization

• Top 10 pieces updated within last 30 days

• "Short Answer + Deep Dive" format on key pages

• FAQ sections on product/service pages

• Original data/statistics in content

• Clear H2 → H3 → bullet point structure

Entity Building

• Wikipedia page (if notable enough)

• Wikidata entry with complete information

• Consistent NAP across all platforms

• Organization schema on website

• One clear "outcome" your brand owns

Sentiment Management

• Monthly Reddit audit for brand mentions

• Active, authentic Reddit presence

• User-generated content encouraged

• Negative threads addressed or offset

• Comparison content positioning you favorably

Monitoring

• AI visibility tool in place (Profound, Otterly, or similar)

• Monthly visibility tests across ChatGPT, Perplexity, Gemini

• Citation tracking for key pages

• Competitor monitoring in AI answers

• [Sentiment trend tracking]

That should do it for today.

For 20 years, you optimized for Google's crawler.

You built backlinks. You targeted keywords. You fought for position zero.

Now there's a second game. And the rules are different.

Google measures authority. AI measures sentiment. 

Google indexes your content. AI reads about you. 

Google ranks by links. AI ranks by narrative. Google thinks in keywords. AI thinks in entities.

The brands that win this game are shaping the conversation in the places AI models scan most: Reddit threads, comparison blogs, integration docs, community forums, Wikipedia, Wikidata.

They're not just optimizing for crawlers. They're optimizing for reasoning engines.

AI traffic is still small, at about 0.15-1% of total web traffic. But it's growing 500-700% year over year. And visitors from AI convert 4-23x better than traditional search.

Your move.

Until next time,
Sam Woods
The Editor

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