About Joel House
Joel House is an AI marketing strategist, entrepreneur, and the founder of MentionLayer — the platform that helps brands and agencies get recommended by AI models like ChatGPT, Perplexity, Gemini, and Claude.
Joel has spent over a decade building digital marketing companies and advising brands on organic growth. He is the founder and CEO of Xpand Digital, an agency that has driven measurable results for clients across music, legal, finance, and e-commerce verticals. Recognizing that the search landscape was shifting from ten blue links to AI-generated answers, Joel pioneered Generative Engine Optimization (GEO) — the discipline of optimizing brands to appear in AI responses rather than (or in addition to) traditional search results.
He is the author of AI for Revenue, a practical guide for business owners and marketers on integrating AI into their revenue operations. The book distills Joel's hands-on experience running AI-first campaigns and building the internal tools that eventually became MentionLayer.
MentionLayer operationalizes GEO at scale: seeding citations in high-authority Reddit and Quora threads, auditing AI visibility across five pillars, managing digital PR distribution, and tracking share-of-model across the major AI platforms. Joel built the platform to solve a real problem he faced with his own clients — the inability to measure or influence whether a brand appears when a potential customer asks an AI for a recommendation.
Joel is based in Australia and works with brands and agencies globally. He speaks regularly on the intersection of AI and marketing, and is recognized as one of the early practitioners defining the GEO discipline.
Areas of Expertise
Articles by Joel House(39)
The Glossary Play: How Definition Pages Build Topical Authority for AI
Glossary and definition pages are the hidden authority builders of AI search. They answer "what is" queries directly, create natural internal linking targets, and signal comprehensive topic coverage to AI models.
The Content Refresh Playbook: How Updating Old Content Boosts AI Citations
76.4% of ChatGPT\'s cited pages were updated within 30 days. This playbook covers when to refresh, what to update, and a monthly cadence that keeps your best content earning AI citations indefinitely.
What Is Information Gain in AI Search? How Unique Content Wins
Information gain measures how much new, unique value a piece of content adds beyond what already exists on a topic. AI models prioritize sources with high information gain because they provide answers other sources cannot.
Internal Linking Strategy for AI: Helping Both Google and AI Models Understand Your Site
Internal linking is the connective tissue that transforms scattered content into recognized topical authority. This guide covers the 5-layer linking framework, anchor text strategy, orphan page detection, and the specific linking patterns that increase AI citation probability.
Pillar Pages and Topic Clusters: Building Authority That AI Recognizes
How to structure pillar pages and topic clusters so both Google and AI models recognize your expertise. Includes templates, linking patterns, and the specific formatting that maximizes AI citation probability.
How to Build Topical Authority That AI Models Trust
A step-by-step implementation guide for building the kind of topical authority that earns AI model citations. Covers cluster planning, content creation, linking, and the off-site signals that validate on-site expertise.
What Is Topical Authority and Why AI Models Care About It
Topical authority is the depth of expertise a website demonstrates on a specific subject. This glossary entry explains what it is, how AI models evaluate it, and why it determines whether your content gets cited.
Topical Authority: The Complete Guide to Dominating Your Niche in 2026
The definitive guide to building topical authority that both Google and AI models recognize. Covers content clusters, pillar pages, internal linking, information gain, semantic SEO, and the specific signals AI models use to determine niche expertise.
Share of Model vs Share of Voice: Measuring What Matters in 2026
Share of Model measures AI recommendation visibility. Share of Voice measures traditional media and search visibility. This comparison explains why you need both metrics, how they differ, and how to track each one effectively.
Why ChatGPT Recommends Your Competitors Instead of You
When users ask ChatGPT for recommendations in your category and your competitor appears instead of you, there are specific, traceable reasons. This guide diagnoses the four most common causes and provides a focused action plan to shift the recommendation.
The AI Visibility Gap: 76% of Businesses Have No AI Search Strategy
New data reveals that 76% of businesses have no strategy for appearing in AI search results, even as AI referral traffic grows 527% year-over-year. This analysis examines the gap, who is exploiting it, and what happens to businesses that wait.
10 Best Ways to Get Your Brand Recommended by AI Models
A ranked list of the 10 most effective tactics to get ChatGPT, Perplexity, and Gemini to actively recommend your brand. Each tactic includes implementation steps, expected timeline, and impact level based on campaign data.
What Is the Consensus Layer in AI Search?
The consensus layer is the mechanism AI models use to decide which brands to recommend by triangulating mentions across multiple independent sources. This glossary entry explains how it works and why it matters for your visibility strategy.
Perplexity vs Google: Which Drives Better Business Traffic?
A data-backed comparison of Perplexity AI and Google as sources of business traffic. Covers citation behavior, conversion rates, user intent differences, and how to optimize for both simultaneously.
Why Your Brand Doesn\'t Appear in AI Search Results (and How to Fix It)
If ChatGPT, Perplexity, and Gemini skip your brand when users ask about your category, there are specific, diagnosable reasons. This guide identifies the six most common causes and provides fix-by-fix action steps.
25 AI SEO Statistics Every Marketer Needs to Know in 2026
The definitive collection of AI SEO statistics for 2026. Covers AI search adoption rates, citation behavior, traffic conversion, platform preferences, and the metrics that define the new search landscape.
What Is an AI Visibility Score? How to Score Your Brand
An AI visibility score measures how often and how prominently your brand appears in AI-generated answers. This guide explains how scores are calculated, what benchmarks look like by industry, and how to improve a low score.
How to Monitor What AI Models Say About Your Brand
A step-by-step guide to tracking your brand\'s presence across ChatGPT, Perplexity, Gemini, and Claude. Covers free manual methods, paid tools, prompt design, and building a monitoring cadence that catches changes before they cost you customers.
The AI Visibility Index: We Tested 1,004 Businesses Across 5 AI Models. 66% Are Completely Invisible.
Original research: 95,392 data points across 1,004 businesses, 10 industries, and 5 AI models. Two-thirds of businesses receive zero mentions. Domain Authority and Google Reviews are the twin pillars. llms.txt is overhyped. Full methodology, data tables, anonymized dataset, and the 90-day action plan.
Your Brand Is Invisible to AI — Here’s How to Check in 60 Seconds
37% of consumers now start searches with AI instead of Google. Most brands score 0% visibility. Here’s a 60-second test to check yours.
AI SEO vs Traditional SEO: What Changed and What Didn’t in 2026
SEO isn’t dead — but the game now has two courts. Traditional SEO ranks you on Google. GEO gets you recommended by AI. Here’s what shifted and what stayed the same.
What Is Generative Engine Optimization (GEO)? The Complete Guide for 2026
GEO is the practice of optimizing your brand to be recommended by AI models. This comprehensive guide covers the 5-pillar framework, strategy, execution, and measurement.
Share of Model: The AI Marketing Metric Replacing Share of Voice
Share of model measures what percentage of relevant AI prompts result in your brand being mentioned. Here’s how to measure, benchmark, and improve it.
The AI Citation Index: Where Do ChatGPT, Perplexity, and Gemini Get Their Data?
Perplexity averages 21.87 citations per answer vs ChatGPT’s 7.92. Reddit accounts for 46.7% of Perplexity’s top citations. Here’s the complete citation source breakdown.
How AI Models Decide Which Brands to Recommend (And Why Yours Might Not Make the List)
AI models don’t rank pages — they build consensus from dozens of independent sources. Learn exactly how this consensus layer works, which sources carry the most weight, and why 94% of AI brand mentions never become actual recommendations.
Reddit Is the Most Important Platform for AI Visibility (And Most Brands Ignore It)
Reddit appears in 68% of AI answers and 95% of product-review queries on Google. It’s the number-one source Perplexity cites. Yet most brands have zero presence in the Reddit threads AI models reference about their industry.
Citation Seeding: The Reddit & Quora Strategy That Feeds AI Recommendations
Citation seeding is the practice of placing authentic, valuable responses in forum threads that AI models already reference. This is the complete tactical playbook for finding threads, writing responses, posting strategically, and measuring impact.
Platform-by-Platform GEO: How to Optimize for ChatGPT vs Perplexity vs Gemini vs Claude
Only 11% of cited domains appear across multiple AI platforms. Each engine has radically different citation behaviors. A single GEO strategy won’t work. Here’s the platform-specific playbook.
The AI Visibility Audit: How to Score Your Brand Across 5 Pillars
The 5-pillar AI visibility audit measures Citations, AI Presence, Entities, Reviews, and Press to produce a composite score from 0-100. Learn how each pillar is scored, what the numbers mean, and how to use the audit to build your action plan.
Schema Markup for AI Search: What Actually Gets You Cited in 2026
Content with comprehensive schema markup has a 2.5x higher chance of appearing in AI-generated answers. Here is which schema types matter most and how to implement them for maximum AI visibility.
Digital PR in the AI Era: Why Brand Mentions Now Beat Backlinks 3:1
90% of citations driving LLM visibility come from earned media. Digital PR has gone from brand awareness tactic to critical AI visibility infrastructure.
Your Robots.txt Is Blocking ChatGPT: The AI Crawler Decision Framework
79% of top news sites block AI training bots. But blocking the wrong crawlers means AI literally cannot cite your content. Here is the framework for deciding what to allow.
Zero-Click Search Is Here: What the AI Overviews Data Actually Shows
AI Overviews appear in 48% of Google queries. When they do, organic CTR drops 61%. The question is not how to rank #1 anymore — it is how to become the brand AI cites in the answer.
Entity SEO for AI: How to Build a Knowledge Graph That AI Models Trust
AI models evaluate brands as entities, not pages. If your brand is a recognized entity in knowledge graphs, you are far more likely to appear in AI recommendations.
AI Visibility Tools Compared: How to Choose the Right Platform in 2026
A comprehensive comparison of every major AI visibility and GEO tool on the market — from monitoring-only platforms to full-stack action systems. Includes feature tables, pricing, and a decision framework.
GEO for Agencies: How to Add AI Visibility to Your Service Offering
A playbook for agencies ready to add AI visibility to their service menu. Covers positioning, pricing, packaging, the audit-as-sales-tool approach, monthly workflows, and scaling to 100+ clients.
GEO for SaaS Companies: Getting Your Product Recommended by AI
A SaaS-specific playbook for Generative Engine Optimization. Covers why G2/Capterra reviews dominate AI software recommendations, how to seed citations in the right subreddits, and the schema markup that makes your product findable.
The ROI of AI Visibility: How to Calculate and Prove Value
A framework for calculating and reporting the return on investment from GEO campaigns. Covers the 4-layer measurement model, dollar-value formulas, client reporting templates, and business case construction.
From Invisible to Recommended: A 90-Day AI Visibility Campaign Playbook
The definitive week-by-week execution plan for building AI visibility from scratch. Covers the full 90-day arc: audit and entity cleanup (weeks 1-2), citation seeding sprint (weeks 3-6), PR and reviews (weeks 7-10), re-audit and optimize (weeks 11-12). With expected trajectories, budgets, and team requirements.
See Your AI Visibility Score
Run a free 5-pillar audit and find out where your brand stands across ChatGPT, Perplexity, Gemini, and Claude.
Run Free Audit →