Have you ever wanted to customize your Google Search experience? Now you can build your own apps right within Google Search.
I discovered this amazing feature powered by Google Antigravity and Gemini 3.5, which lets me set up a search feature that delivers exactly the kind of information I need, formatted just how I like it, and sourced from where I trust.
During this year’s Google I/O, Liz Reid, head of Google Search, unveiled this innovation. She mentioned, “Search can build the ideal response, in the right format for your question – completely on the fly. You’ll get custom generative UI, including visual tools and simulations, tailored to your needs.”
Exciting Examples
Imagine creating custom layouts for understanding astrophysics or how your wristwatch works. Google assembles interactive visuals, tables, and real-time simulations to suit your learning style.
I’ve also been able to manage ongoing tasks like wedding planning or home moves with customized dashboards that act as helpful companions throughout the process.
Let’s not forget fitness! I asked Google Search to build me a custom fitness tracker. It taps into live data like weather and reviews to keep me on track, making my health goals more achievable.
Visualizing the Experience
These custom search experiences, including generative UI examples, will become widely available this summer. I’m particularly excited as they roll out first to Google AI Pro and Ultra subscribers in the U.S.
Why This Matters
It’s groundbreaking to have the ability to code mini apps within Google Search, answering questions in ways that are uniquely mine. It’s a level of personalization I’m thrilled about, achievable only through such advanced generative-AI tools.
I recently came across Google’s fresh guide on optimizing for its generative AI features, highlighting key tools like AI Mode and AI Overviews. This guide compiles insights from previous Google communications into a comprehensive help document titled Optimizing your website for generative AI features on Google Search.
Inside the Guide: This document delves into multiple essential topics, which include:
– SEO’s continued relevance for AI search, adhering to Google’s SEO best practices.
– Creating valuable, non-commodity content for your audience.
– Offering a unique perspective
– Developing content that is helpful, reliable, and prioritizes users
– Organizing content effectively for reader assistance
– Incorporating high-quality images and videos
– Focusing on user needs, avoiding unnecessary complexity
– Ensuring AI tools comply with Google’s guidelines
– Maintaining a clear, technical site structure:
– Meeting technical search requirements
– Adhering to best practices for web crawling
– Emphasizing human-readable semantic HTML
– Following Google’s guidelines for JavaScript
– Providing an excellent page experience
– Reducing duplicate content
– Focusing on optimizing local business and e-commerce details.
– Dispelling myths around AI optimization:
– No need for LLMS.txt files
– Avoidance of special markup
– Refraining from ‘chunking’ content
– No content rewrites for AI systems required
– Avoid seeking inauthentic mentions
– Not overly focusing on structured data
– Exploring agentic experiences and what steps to take next.
Why It Matters to Me: This guide is a comprehensive resource that summarizes Google’s past advice across various platforms and events. It’s invaluable for understanding how to align my site with Google’s expectations for AI-powered search engines.
As I dive into this report, I’m excited to share the top 8 real estate GEO and AEO agencies of 2026. These agencies have been selected based on their impressive results, technical expertise, and exceptional client experience.
Our research team embarked on a detailed study of agencies that specialize in Generative Engine Optimization (GEO) specifically for companies in the home services industry like HVAC, plumbing, electrical, and home security. From a total of 53 agencies, we focused on those serving markets including pest control, lawn care, and remodeling. Here’s how we analyzed them:
Home Services Client Experience (30%): I found agencies with proven success in understanding the unique landscape of seasonal demand, emergency calls, and local search.
GEO/AI Search Technology and Tools (25%): Optimization expertise for AI-powered platforms like ChatGPT and Google AI Overviews was a must.
Average Customer Review Score (15%): Each agency’s client satisfaction was gauged using scores from platforms like Google and Clutch.
Leadership Experience Score (10%): Leadership’s depth of experience in both digital marketing and home services was a key factor.
Year Established (10%): I considered the tenure of each agency and their ability to adapt over time.
Notable Clients (10%): Agencies were evaluated based on their successful partnerships with quality home service providers.
After an in-depth analysis using data from company websites, reviews, and direct outreach, I’ve ranked these firms. The table below showcases the leading home services GEO agencies to keep companies visible across both traditional and AI-powered platforms.
Under the guidance of CEO Evan Bailyn, First Page Sage has developed a robust GEO strategy that elevates home services companies. They’ve propelled names like Mighty Dog Roofing and Pipe Restoration Solutions to the top of search results by creating service-specific landing pages and geotargeted content.
Their strategic focus on building a network of high-quality content ensures recommendations by AI platforms like ChatGPT. When homeowners inquire about the best local services, First Page Sage clients confidently come up as top recommendations.
Year Founded: 2009
Founder Led: Yes
Leadership Experience Score: 4.8
Average Review Score: 4.9
Home Service Focus: Broad home services experience
Notable Clients: Mighty Dog Roofing, iFOAM Insulation
Specialty: Lead gen-focused GEO and SEO
Summary of Online Reviews
Clients rave about First Page Sage’s “fastidious understanding of home services GEO” and “organized, communicative teams.” While their strategies drive quality leads, some mention the need for a longer ramp-up period for business research.
Siana Marketing
Founded in 2021, Siana Marketing directs its focus on GEO for construction and home services. Despite being young, they excel in securing appearances for architects and contractors in both traditional search and AI-generated results.
The leadership team brings deep industry knowledge, with a strong grasp on sales cycles and influencing homeowner decisions. This expertise has helped maintain solid client retention, which is impressive for their relatively short tenure.
Year Founded: 2021
Founder Led: Yes
Leadership Experience Score: 4.6
Average Review Score: 4.8
Home Service Focus: 100% construction and home services
Notable Clients: Corcoran, HomeVestors
Specialty: Construction-only GEO agency
Summary of Online Reviews
Clients highlight Siana’s “industry knowledge” and understanding of the AEC sector’s growth strategies. There’s high demand and selective client acceptance due to their expertise.
Focus Digital
Focus Digital offers high-quality SEO and GEO support at prices accessible to smaller operations. They’ve built credibility by focusing on personalized client attention and staying ahead with innovative strategies.
What makes them unique is their ability to provide premium strategic advice and execution, making them a top choice for businesses with tighter budgets seeking sophisticated search solutions.
Year Founded: 2018
Founder Led: Yes
Leadership Experience Score: 4.5
Average Review Score: 4.8
Home Service Focus: Small business contractors
Notable Clients: Stego Wrap, Twin Home Experts
Specialty: Budget-friendly SEO and GEO solutions
Summary of Online Reviews
Focus Digital’s clients commend their meticulous focus and state of constant innovation. They’re seen as “punching above their weight,” delivering value usually associated with bigger firms.
Welcome to the ultimate guide on Generative Engine Optimization (GEO)! As we move into 2026, knowing how to optimize for AI-driven platforms like ChatGPT, Gemini, Perplexity, and Claude is crucial. This guide will help you ensure that your brand is easily discovered in AI-generated responses.
Imagine having the skills to make your brand the first choice for AI-powered searches. With our comprehensive insights, you’ll learn how to elevate your visibility across key AI platforms and gain a competitive edge.
Whether you’re a seasoned marketer or new to AI optimization, this guide offers strategies that align with both current trends and future predictions. By mastering Generative Engine Optimization, you’re setting the foundation for sustainable success in a rapidly evolving digital landscape.
In the 1990s, web copywriting was a wild ride of keyword stuffing and meta tag mayhem. Those days are long gone, as SEO copywriting has evolved alongside smarter algorithms.
Today, with advanced retrieval systems, our priorities have shifted. It’s no longer about tricking crawlers with repetitive keywords. We need a fresh, more sophisticated approach.
Let me share a playbook focusing on AI-friendly copywriting. It’s packed with actionable insights and high-density concepts that are ready to be implemented.
The ‘Grounding Budget’: Quality Over Quantity
Large language models, or LLMs, don’t need more information—they need better information. According to DEJAN AI’s analysis, Google’s Gemini uses a set budget of information, making precision crucial.
Your content allocation is roughly 380 words per webpage, so accuracy in those words is key to helping the AI accurately match your content.
Think of Schema.org as the building’s skeleton, and structured language as the supportive internal framework. This framework makes sentences machine-readable, enhancing the power of “semantic triplets”—subject, predicate, object.
For Google and AI models like ChatGPT, properly structured sentences are key. They require specific criteria sure to aid in retrieval.
Names entities: Clearly identifies subjects and objects (e.g., “Notion Team Plan”).
States relationships: Defines interactions with clear verbs (e.g., “costs”).
Preserves conditions: Adds context for authenticity (e.g., “$10 per user per month”).
Includes specifics: Offers verifiable detail over fluff (e.g., “includes 30-day version history”).
Transitioning from marketing fluff to structured language not only boosts readability but also enhances machine utility.
Best Practices for AI-Friendly Copywriting
Like a line of dominoes, traditional copywriting flows smoothly. But AI technology “chunks” text, breaking that flow if sentences aren’t independently robust.
Rule 1: Every Sentence Must Survive in Isolation
Each sentence should be able to stand alone, naming its subject clearly. Vague pronouns are problematic when content is extracted by AI.
Broken: “It also includes unlimited cloud storage.”
Anchorable: “The Dropbox Business Standard Plan includes 5TB of encrypted cloud storage.”
Rule 2: State Relationships, Don’t Just List Entities
Keyword stuffing leads to errors; clear, structured language explicitly states the relationships between entities.
The keyword dump: “We offer SEO, PPC, and content marketing services.”
The structured relationship: “Our agency integrates PPC data into SEO strategies to lower cost per acquisition (CPA) by an average of 15% within 90 days.”
Rule 3: Build ‘Anchorable Statements’
Deliver clear claims with evidence, ensuring your passages hold weight in dense AI environments.
“Ramon Eijkemans specializes in enterprise SEO with a focus on platforms exceeding 100,000 pages. He developed the LLM Utility Analysis framework, which includes five lenses crucial for content scoring.”
The AI Inverted Pyramid: Engineering ‘Citation Bait’
Research shows claims positioned near the start or end of text are more likely to be extracted by LLMs. Therefore, too much additional content can dilute effectiveness.
“Pages under 5,000 characters see around 66% extraction. Exceeding 20,000 characters reduces this to 12%.”
For creating effective citation bait, follow these four steps:
The direct answer: Begin with a concise answer in 40-60 words.
Context and detail: Continue with nuanced, dense information.
Structured evidence: Provide easy-to-extract data through lists, tables, etc.
Follow-up alignment: Use clear subheadings for potential queries.
Improving the relevance (cosine similarity) to AI, clear headings assist by up to 17.54%.
The 5 Lenses of LLM Utility
Ramon Eijkemans developed a robust scoring system measuring content’s citation likelihood:
Structural fitness: Builds clear hierarchies and relationships.
Selection criteria: Ensures information density.
Extractability: Avoids broken references or vague pronouns.
Entity completeness: Clearly names subjects and relationships.
Natural language quality: Is structurally rich but not robotic.
Practical Content Testing Tips
Four tests to ensure your pages are programmatically extractable:
The Isolation Test
Action: Select a random sentence from the webpage middle. Can it stand alone?
Goal: Ensure each sentence is self-contained, avoiding reliance on prior text.
The Context Test (‘Scroll Twice and Read’)
Action: Scroll the homepage until the banner disappears, start reading.
Goal: Ensure mid-page text can standalone without the primary layout for context.
Goal: Specific language ensures AI maps statements to correct entities.
The URL Accessibility Test
Action: Test your live URL with an LLM agent.
Goal: Ensure readability without blockers like JavaScript or bot protection.
AI Search Content Optimization FAQs
Here are some frequently asked questions about optimizing for AI-driven search.
Is Generative Engine Optimization (GEO) Legitimate?
Yes, it is. Focused on optimizing citation frequency, GEO uses dense, structured sentences. It’s about embedding explicit entity relationships into copy.
What’s the Ideal Section Length for Chunking?
Start with a tight 40-60-word statement. Long, buried information is often ignored by AI.
Does AI Search Copywriting Help Traditional SEO?
Yes! Structured content for AI also boosts traditional visibility due to vector embeddings.
Is Longer Content Better?
No, it’s not. Dense information beats length. Pages below 5,000 characters see more effective extraction.
What is the AI Copywriting Inverted Pyramid?
The pyramid strategy involves placing key details upfront for seamless machine extraction.
Write for Humans, Structure for Machines
As a content creator, I see my role evolving into one of a machine-readability engineer. Crafting content that both engages humans and can be precisely extracted by neural networks is crucial.
Without explicit entity relationships and self-contained, anchorable statements, AI might overlook your content entirely.
As I dive into the intriguing world of Generative Engine Optimization (GEO), I find myself exploring how we can fine-tune a company’s online presence to have their products or services recommended by generative AI chatbots. Although still a budding marketing avenue, GEO’s potential reminds me of the early days of SEO, ripe for exploration and growth. I’m convinced that the deep insights from this research will pave the way for much-needed best practices in the market.
My team and I embarked on an extensive study from March 2024 through December 2025, focusing on the recommendation algorithms of the four most popular generative AI chatbots in the United States. We meticulously conducted 11,128 commercial queries across various sectors, seeking to unravel the factors these chatbots use to recommend products and services. We’ve continued to update our insights, the latest being on March 12, 2026.
The table below gives a detailed breakdown of our research findings, listing the factors influencing chatbot recommendations in terms of weight. Following the table, I delve into each factor, elucidating how each chatbot incorporates them into their recommendation process.
Allow me to take you through the key factors that guide commercial recommendations across these generative engines. Although they share common factors, each employs a unique weighting system to determine recommendations.
NOTE: The more advanced versions of these AI chatbots may personalize their suggestions as more personal data is provided, potentially altering factor weightings.
Authoritative List Mentions
When it comes to predicting content, generative AI engines draw information from multiple authoritative sources. They echo the voices of experts, offering recommendations rooted in well-regarded lists and rankings. I find it fascinating how they lean heavily on top-ranking Google searches to refine their recommendations, which are potently informed by these highly authoritative sources.
Claude stands apart, favoring traditional compendiums over Google-reliant lists, perhaps embracing a more traditional approach.
Awards, accreditations, and affiliations
Mentioning an award or accreditation on a trustworthy website signals authority, nudging AI to recommend the associated company or product more frequently. It’s quite interesting to see this recognition elevated in the virtual world.
Online Reviews
Online reviews hold substantial sway for ChatGPT, Gemini, and Perplexity, especially reviews from platforms like Amazon, Better Business Bureau, and Glassdoor. I see how a confluence of positive reviews can significantly boost recommendation weight.
Social Sentiment
It’s intriguing to see how the way a company is discussed online, including on news sites and social platforms like Reddit, subtly shapes ChatGPT’s recommendations. Its current influence is modest but poised for growth as trust builds in digital communities.
Customer Examples & Usage Data
Recognized endorsements and partnerships visibly boost a product’s credibility. This factor, used by ChatGPT and Claude, reinforces the reputational weight of significant customer associations or user data.
Google Website Authority
Google attributes site authority based on factors like consistent content publication. Gemini values this significantly, drawing from Google’s well-established credibility measures.
Local Business Reviews
For local queries, Gemini and Perplexity lean on reviews from Google Business Profiles and Yelp. This localized trust mechanism brings a nuanced understanding to the recommendation landscape.
Traditional Databases & Directories
Generative AI chatbots like Claude often delve into established resources like encyclopedias and business directories. This approach weights well-established data heavily in crafting precise business recommendations.
ChatGPT’s Recommendation Algorithm
In my exploration of ChatGPT’s algorithm, I’ve noticed its reliance on Bing to gather authoritative lists, reviews, and rankings. It aggregates and refines recommendations through a blend of sources, ensuring a comprehensive outcome.
Often, top Bing search results heavily guide its recommendations, but in their absence, ChatGPT factors in alternative data like awards, reviews, and social sentiment. An illuminating example involved its interpretation of lawnmower choices guided largely by trusted reviews from notable publications.
Google Gemini’s Recommendation Algorithm
Gemini’s algorithm intrigues me with its Google-centric approach, harnessing authority and reviews together from search results to guide recommendations. Its unique method prioritizes recognized achievements, often steering clear of poorly reviewed companies.
In practical application, Gemini reinterprets product searches by balancing authority with popularity, evidenced by its moisturizer recommendations, aligning sales volume with positive reviews.
Perplexity’s Recommendation Algorithm
What strikes me about Perplexity is its straightforward algorithm, largely favoring search lists and reviews. It often taps into the most readily available online viewpoints to construct its recommendations.
For local business queries, its focus on high-ranking lists underscores a strategy based on easily established credibility from popular review sites.
Claude AI’s Recommendation Algorithm
Unique in its approach, Claude AI depends on traditional databases, often highlighting historically established companies in its recommendations. This somewhat conservative method gives it a distinct identity in the generative AI landscape.
Focused purely on national businesses, it bypasses local recommendations altogether, streamlining its efforts towards broader-scale authority.
Downloading This Report & Inquiries
If you’re curious to learn more or desire a PDF copy of this report, please reach out via our contact page.
First Page Sage is also at the forefront of GEO services. Interested in knowing more? Don’t hesitate to contact us.
Ever wondered how to get your brand noticed by AI search engines? Let me walk you through the step-by-step process of getting your brand cited, recommended, and discovered by AI search platforms.
So, let me dive into the world of AI! Gartner forecasts a 25% drop in traditional search volume as AI engines take precedence. With Google’s AI Overviews attracting over 2 billion users monthly, and ChatGPT serving 800 million users weekly, the shift is here.
Gone are the days of just vying for a spot on Page 1. Now, it’s all about becoming the go-to source that AI engines cite in their answers.
This focus on generative engine optimization (GEO) is crucial in 2026. Here’s how to craft a GEO strategy that truly delivers.
What is GEO — and why 2026 is the tipping point
GEO is about aligning your content and digital identity so AI search platforms like ChatGPT, Google AI Overviews, Perplexity, and others, can easily find and recommend your brand.
If traditional SEO got you among the top 10 links, GEO aims to secure your position among the few domains cited in AI responses. It’s tougher in terms of competition, but the credibility from being mentioned by an AI engine is worth it.
Several forces make 2026 a milestone year. Users are becoming loyal to specific AI platforms, elevating GEO from experimental to essential. Universities and enterprises are backing this shift, highlighting AI engines’ preference for authoritative external sources over internal content.
Understanding this trend is vital for building an effective GEO strategy.
A practical GEO framework: assess, optimize, measure, iterate
Treating GEO as a mere content tweak is a misconception. Just like SEO, it requires ongoing commitment. Here’s a repeatable framework to master it.
Phase 1: Assess your AI search readiness
You need a baseline before optimization. Many brands monitor Google rankings but are blind to how AI engines portray them.
Ask yourself crucial questions: Are AI engines referencing your content? Can they read your structured data efficiently? How does your brand appear in AI-generated content? Are your competitors cited where you aren’t?
Consider using tools like Geoptie’s free GEO Audit for a quick assessment, providing actionable insights for optimization.
Phase 2: Optimize your content for AI engines
The heart of your GEO strategy is optimization. Focus on content structure, entity authority, technical foundations, and keeping content up-to-date.
Structure content for AI retrieval
AI breaks down content to assess relevance and clarity. Make sure each section stands independently.
Begin sections with straightforward answers followed by context. Use headings properly and add TL;DR summaries to enhance retrieval chances. FAQs are crucial as AI relies heavily on Q&A formats.
Build entity authority
GEO emphasizes brands and entities rather than single pages. Strengthen these signals for better recognition and citation by AI engines.
Ensure brand mentions are consistent, develop comprehensive about and author pages, and maintain a Wikipedia presence if applicable. A well-managed knowledge panel is also beneficial.
AI engines prefer coverage from third parties over personal content. Thus, digital PR and thought leadership have become essential GEO components.
Nail the technical foundations
Technical optimization in GEO includes traditional SEO elements plus AI-specific enhancements.
Utilize schema markup, verify robots.txt settings accommodate AI crawlers, and consider adding an llms.txt file to guide AI interactions with your site.
Don’t forget the basics. Fast load times, clean architecture, and mobile optimization remain crucial.
Prioritize freshness and depth
AI values recency in sources. A guide from 2024 without updates will be overshadowed by a 2026 version on the same subject.
Keep cornerstone content refreshed with up-to-date data and insights, distinctly marked with a “Last updated” timestamp. Original research and exclusive data enhance your chances of being cited by providing unique value.
Phase 3: Measure your AI search performance
Measurement is often a missing piece in GEO strategies. Many marketers lack clear insights into AI search visibility after mastering traditional SEO metrics.
Important metrics include AI citation frequency, share of voice, citation sentiment, and AI-referred traffic. Traditional tools fall short in tracking these, necessitating specialized GEO platforms.
Geoptie’s free Rank Tracker is a convenient way to check your standing on various AI platforms as an initial assessment.
Phase 4: Iterate and scale
GEO doesn’t end after initial implementation. The AI landscape continuously evolves, requiring rapid adaptation.
Analyze performance data to understand citation success and refine strategies. Focus on platforms delivering the most value and monitor competitor movements.
Replicate successful content across various formats and integrate GEO tasks among content, SEO, PR, and product teams.
Geoptie offers a comprehensive dashboard for managing audits, competitor analysis, citation tracking, and content optimization all in one place, simplifying the GEO workflow.
Now is the time to build GEO capability
GEO is not a fleeting trend. As AI adoption surges in 2026 and beyond, an early commitment to GEO sets the stage for long-term success.
Follow this clear playbook:
Assess your current standing
Enhance your content and technical readiness for AI
Track performance on relevant platforms
Iterate continuously
Brands laying this foundation will reap ongoing benefits as AI becomes a primary tool for customer engagement.
The crucial decision is whether you’ll pioneer or be a follower in GEO.
Ready to take control of your AI visibility?
With Geoptie, you have a one-stop solution for mastering GEO. From in-depth audits to tracking AI rankings, competitor analysis, and crafting AI-specific content, Geoptie equips you from the start.
Whether beginning your GEO journey or scaling an existing plan, Geoptie helps translate insights into real progress. Start your free 14-day trial to gauge your brand’s AI search standing.
I recently delved into the intriguing world of Answer Engine Insights and discovered a groundbreaking update: eight distinct citation categories. These categories reveal the true sources of AI visibility.
This update provides a fresh perspective, as it’s backed by insights derived from analyzing an impressive 85 million citations across ChatGPT, Gemini, and various AI Overviews. Now, isn’t that fascinating?
If you’ve ever wondered about the mechanics behind AI answers, this exploration into citation categories might just provide the clarity you’ve been seeking.
I’ve been diving deep into the fascinating world of Generative Engine Optimization, or GEO, as it’s reshaping the $80 billion SEO market. With insights from the renowned Andreessen Horowitz, I’m excited to explore how AI search engines like ChatGPT, Perplexity, Google AI, and Apple’s Siri are evolving and impacting our strategies.
The surge of AI-powered tools is transforming how we approach digital marketing. In such a rapidly changing environment, staying updated with GEO strategies is crucial. Thankfully, A16Z provides invaluable guidance to navigate these changes effectively.
As someone passionate about SEO and AI, I find the integration of AI in search engines like ChatGPT and Google’s AI Overviews captivating. These tools not only enhance user experience but also demand nuanced optimization tactics.
Apple’s Siri and AI-driven searches are continuously pushing the envelope, making it vital for us to adapt our SEO strategies. Leveraging these insights can significantly elevate our digital marketing efforts and ensure we remain competitive.
Join me as I delve into these transformative insights from A16Z, exploring how we can refine our GEO strategies for a future dominated by AI-driven search engines.
I recently came across some exciting data about AI search traffic, and I wanted to share it with you. AI-related searches are booming, with a whopping 900 million weekly users turning to ChatGPT. Meanwhile, Gemini isn’t far behind with 650 million users.
The explosive growth in AI search usage is not just a trend; it’s a significant transformation in how we interact with technology. To get a clearer picture, you can dive into the complete AI search traffic data breakdown, illuminating the shifts and spikes in user engagement.
Reflecting on these numbers, I can’t help but wonder about the future of AI and how it will continue to influence our digital landscapes. As we move into 2025 and 2026, AI’s role in search will be more pivotal than ever.
