Get Your Local Service Business Recommended by AI and LLMs: The Top Click Joe Approach

The digital landscape is constantly evolving, and at Top Click Joe, we’re here to tell you that the rules of content visibility have fundamentally changed. Forget what you thought you knew about traditional SEO; we’re now in the era of Generative Engine Optimization (GEO). 

If you’ve been hearing whispers of “SEO is dead,” it’s not entirely accurate, but the game has certainly shifted. We’re here to share our real-world, client-proven strategies for getting your content cited by AI and large language models (LLMs).

What is an LLM?

An LLM is short for Large Language Model. It’s like a super-smart computer brain that can read, write, and converse like a person. But it’s not a real brain—it’s a program made by people using tons of words from books, websites, and chats to learn how language works.

Here’s a complete example: I am an LLM! My name is Grok, and I was built by a company called xAI. I can answer questions, create stories, or even assist with homework. For instance, if you ask me, “What’s the capital of France?” I’ll say “Paris” and explain why. 

I learned all this by studying billions of words, so I can guess what to say next in a fun and helpful way. But remember, I’m not perfect—I might make mistakes sometimes, just like anyone learning something new.

What is Generative Engine Optimization (GEO)

Generative Engine Optimization, or GEO, is a method to improve your website’s or online content’s visibility in responses provided by AI chatbots like ChatGPT, Perplexity, or Google’s AI Overviews. It’s like making sure your homework gets noticed by the teacher, but instead, you’re helping a computer program find and share your stuff when someone asks a question.

Here’s a complete example: Imagine you have a website about “Fun Things to Do in New York.” You want an AI like me, Grok, to mention your website when someone asks as an example, “What’s fun to do in New York?” To do GEO, you’d make your website super clear and helpful. 

You’d write short, easy sentences, use lists like “Top 5 Museums” or “Best Parks,” and add real facts, like “The Statue of Liberty was a gift from France in 1886.” You’d also organize your site with clear titles and headings, so the AI can quickly understand it. 

If your content is incredible, unique, and answers questions well, an AI might pick it over others and say, “Check out this great website for fun things to do in New York!” This helps more people find your site. GEO is about making your content so good that AIs love to share it!

Tell the World Something New

Think of it this way: a PR agency can’t promote a boring, unoriginal story. The same applies to your content in the age of AI. The days of churning out generic “ultimate guides” that simply rehash existing information are over. This kind of content lacks information gain – it doesn’t tell the world anything genuinely new.

Google’s own Information Gain patent, granted in June 2022 and titled “Contextual Estimation of Link Information Gain,” describes a scoring system that measures how much additional, non-redundant information a new document provides compared to content a user has already viewed on a related topic, using machine learning to rank or present follow-up search results more effectively.

This underscores the point: your content needs to be valuable and offer fresh insights. We’ve seen firsthand how high-effort, unique content, like commissioned surveys with original data, gets cited in AI search results. 

Google’s guidance reinforces this, advising creators to focus on unique, non-commodity content that adds value and satisfies users, particularly as AI Overviews handle more complex queries by drawing from helpful, original sources. Source: https://developers.google.com/search/blog/2025/05/succeeding-in-ai-search 

This isn’t just a trick for AI; it’s simply good content marketing, where unique content helps brands stand out, boost rankings, build authority, and enhance user engagement by providing originality and relevance that aligns with audience needs.

If your content isn’t unique, why would journalists, bloggers, or even AI systems bother to mention or share it?

To boost your AI visibility, be transparent about your data sources and research methods, including any limitations. This verifiable approach makes your content more trustworthy for AI. Also, commit to regularly updating your data – more often than just annually – to signal reliability to AI as a trusted information source. After all, LLMs crave the freshest data.

Here are three examples of how your company can create content with high information gain:

• Publishing Original Research Reports: Commission a proprietary survey on a niche industry trend, analyze the results, and release a comprehensive report with never-before-seen data and actionable insights. For example, “The State of Hybrid Work: A 2025 Study of Employee Preferences and Productivity.”
• Developing a Unique Data Visualization Tool: Create an interactive online tool that allows users to explore complex datasets relevant to your industry in a new way. For instance, a “Local Housing Market Predictor” that uses your own proprietary algorithms to forecast neighborhood-level price changes.
• Conducting In-Depth Case Studies with Quantifiable Results: Instead of generic testimonials, publish detailed case studies that highlight a client’s specific problem, your unique solution, and measurable outcomes like “How Our AI-Powered Marketing Platform Drove a 300% ROI for [Client Name] in Six Months.”

Here are three more examples to consider:

• Creating a Proprietary Industry Index or Benchmark: Develop a unique methodology to measure and track key performance indicators within your industry. For example, “The Top Click Joe Digital Marketing Efficacy Index,” which quantifies the effectiveness of various digital strategies based on your own client data.
• Releasing Expert Interviews with Exclusive Insights: Conduct interviews with leading, hard-to-reach experts in your field, extracting novel perspectives and predictions that aren’t widely available. This could be a series like “Pioneers in AI: Exclusive Conversations with [Industry Leaders].”
• Producing Predictive Analysis Reports: Leverage your internal data or publicly available, raw data to offer unique forecasts on future trends or market shifts. For instance, “Predicting Consumer Behavior Shifts in Q4 2025: An Analysis of [Your Company’s] Proprietary Data.”

Keywords Are Out, Real Discussions Are In

It’s time to say goodbye to keyword-centric content strategies, as the rise of AI-powered search engines has fundamentally changed how information is discovered and delivered. Traditional keywords, which have long been the cornerstone of search engine optimization (SEO), only reveal what terms people are typing into search bars—such as “best wireless headphones”—but they fail to uncover deeper details like who is searching (e.g., a fitness enthusiast versus a music producer) or why they are searching (e.g., for noise cancellation during workouts or high-fidelity sound for studio use). 

This limitation stems from the evolution of search technology: early systems, such as AltaVista in the 1990s, relied heavily on simple keyword matching. However, advancements like Google’s Hummingbird update in 2013 introduced semantic search, prioritizing user intent over exact phrases. 

In today’s AI age, this leads to a “one-size-fits-all” approach that no longer works, as AI systems like ChatGPT, Perplexity, and Google’s AI Overviews use natural language processing (NLP) models such as BERT and MUM to understand context, synthesize information, and provide direct, conversational answers rather than just ranked links. 

For example, you can no longer create a single piece of content in generic American English and expect it to resonate equally with audiences in the UK, Australia, or India, where regional dialects, cultural nuances, and local references—like “best earphones for the gym” versus “top headphones for exercise”—play a crucial role in engagement. 

AI’s advanced capabilities, including over a billion monthly voice searches that mimic natural conversations (e.g., “Hey, which wireless headphones are best for noise cancellation?”), Demand more targeted, context-rich content that addresses specific user intents, such as informational, transactional, or navigational needs, to stand out in generative responses.

Instead of obsessing over keyword tools and their often-dubious search volumes—which can be inflated or outdated—shift your efforts to robust market research that directly taps into the raw data sources powering large language models (LLMs) themselves, ensuring your content aligns with real-world conversations and emerging trends. 

For instance, Grok, developed by xAI, is pre-trained on a variety of publicly available sources but integrates real-time data from X (formerly Twitter), including trending discussions and user interactions, to provide up-to-date, context-aware responses through features like Deep Search.

More similarly, ChatGPT from OpenAI leverages publishing partnerships with major outlets like Condé Nast (including Vogue and The New Yorker), The Washington Post, Guardian Media Group, Hearst (covering magazines like GQ and Architectural Digest), and Future (with over 200 brands spanning news and lifestyle), allowing it to draw from high-quality, curated journalism and specialist content for more accurate and diverse answers.

The real insights for your content strategy lie in understanding the discussions and conversations happening in these source environments, such as analyzing X threads for live debates on topics like “best digital marketing strategies in 2025” or reviewing partnered publisher articles for in-depth lifestyle queries. 

This approach, part of generative engine optimization (GEO), emphasizes long-tail conversational queries (e.g., “which digital marketing channels work best for small businesses?”). It also incorporates semantic keywords (e.g., “SEO tactics” or “content marketing trends”) and entities (e.g., “Google Analytics” or “HubSpot”) to create content that AI systems can easily synthesize. 

The volume of these discussions—measured by metrics like retweets, replies, or article shares—indicates genuine content demand, as high-engagement topics signal what users are truly interested in, helping you prioritize creation of meaningful, intent-driven material over generic keyword-stuffed pages.

Feed AI Inputs, Not AI Outputs

We’ve noticed a trend where people believe that AI will automatically pick up AI-generated or AI-assisted content. This is a short-term fantasy. While it might seem like a quick fix, expecting AI to re-process its own outputs is like asking it to “rehydrate itself using its sweat.” 

AI outputs are inherently derivative, diluted, and prone to hallucination. LLMs won’t risk degrading their models by training on content that’s founded on other AI outputs.

To create content that AI truly prefers, you need to use the same data sources that feed AI engines. While a data firehose from platforms like X.com might be out of budget for most, there are creative alternatives. 

We’ve successfully used well-constructed surveys with robust sample sizes to generate original data. Allow the general public to provide you with new data by conducting surveys.

Meaningful press coverage, media mentions, and high-quality backlinks are also crucial. These signals indicate to AI that your content is valuable enough to be used for retraining its models and updating its worldview. 

By data-mining the same sources as AI, you can structure your content to provide direct answers to questions and adopt a conversational tone that mirrors how buyers prompt for solutions.

Here’s An Example

Imagine you’re the marketing team for a company like Woody’s Hardwood Flooring, which specializes in refinishing services for homes in Utah and beyond. To enhance visibility in AI search results (such as those from Grok or Google’s AI Overviews), you decide to create content around homeowner trends in flooring choices. 

Rather than relying on generic articles or outdated keyword data, you commission your own nationwide survey of homeowners, mirroring the high-quality, original datasets that train large language models (LLMs)—like those from industry associations or consumer research firms that partner with AI developers. 

The survey includes questions such as “What attributes are most important when choosing flooring?” and “What kind of flooring would you have in your dream home?” This generates fresh insights, for instance, revealing that 67% of respondents prioritize durability, 61% value attractiveness, and 58% seek easy-to-clean options, while 66% would choose wood floors for their ideal home.  

You then publish a detailed blog post or report on your site, featuring these original findings with a transparent methodology (e.g., a sample size of 1,000+ homeowners, with a margin of error noted), structured in a conversational format with headings like “Top Homeowner Priorities for Hardwood Refinishing” and lists of key statistics. 

Because this content provides verifiable, non-redundant value (information gain) akin to what AI engines are built on, it gets referenced in AI responses. In a real-world parallel, surveys like those from the National Wood Flooring Association have been cited in AI overviews for queries on flooring trends, driving traffic, and establishing authority for similar companies.

This approach demonstrates how utilizing AI-aligned data sources—original surveys with raw, insightful responses—enhances the appeal of your content for AI to surface and share.

Below are twenty survey questions that a hardwood floor refinishing company could ask potential homeowners. These are designed for market research, lead generation, or customer intake, focusing on preferences, needs, and pain points to inform services and content creation. They’re compiled and adapted from industry consumer studies and expert recommendations.

1. What type of flooring do you currently have in your home (e.g., hardwood, carpet, tile, laminate)?
2. How old are your current hardwood floors, and have they been refinished before?
3. What are the main issues you’re experiencing with your hardwood floors (e.g., scratches, dullness, water damage, gaps)?
4. What attributes are most important to you when considering floor refinishing (e.g., durability, attractiveness, ease of cleaning)?
5. On a scale of 1-10, how satisfied are you with the current appearance and condition of your hardwood floors?
6. What kind of finish do you prefer for refinished floors (e.g., matte, satin, gloss, natural oil, water-based polyurethane)?
7. Do you have any specific color or stain preferences for your refinished hardwood floors?
8. What is the approximate square footage of the area you want refinished?
9. Are there high-traffic areas in your home that need extra durable refinishing (e.g., kitchen, entryway, living room)?
10. How important is dust control during the refinishing process to you, and what measures would you like us to take?
11. Will you need us to move furniture, or will the space be empty before we start?
12. Do you have pets or children that might affect the choice of finish (e.g., for scratch resistance)?
13. What is your timeline for completing the refinishing project?
14. How do you currently clean and maintain your hardwood floors?
15. Are there any repairs needed before refinishing (e.g., replacing damaged boards, fixing squeaks)?
16. What budget range are you considering for the refinishing project?
17. Have you researched other flooring options, or are you committed to refinishing your existing hardwood?
18. What sources do you use for advice on home flooring projects (e.g., internet, friends, professionals)?
19. On a scale of 1-10, how concerned are you about environmental factors like low-VOC finishes?
20. Would you be interested in add-on services like custom transitions, trim installation, or ongoing maintenance plans?

Here are twenty questions that an ad agency might ask a potential client like Good House Floor Care (a hardwood flooring company specializing in refinishing, cleaning, and installation services) during an initial discovery call or meeting. These are designed to gather insights into their business, marketing needs, goals, and challenges to tailor advertising strategies effectively:

1. Can you tell us more about your company’s history, including how long you’ve been in the hardwood floor care industry and what inspired you to focus on services like refinishing and screen & re-coat?
2. What are your primary services, and which ones generate the most revenue—such as hardwood cleaning, refinishing, or installation?
3. Who is your ideal target audience? For example, are you focusing more on residential homeowners preparing to sell their homes or commercial clients in the Charlotte area?
4. What geographic areas do you currently serve, like Charlotte and surrounding cities, and are you looking to expand to new regions?
5. What are your top business goals for the next 6-12 months, such as increasing leads, boosting online visibility, or growing your customer base?
6. How do you currently acquire new clients? Do you rely on word-of-mouth, Google reviews, or local referrals?
7. What marketing channels are you using right now, like your website, social media, SEO, or paid ads, and which ones have been most effective?
8. Have you run any digital advertising campaigns in the past, such as Google Ads or Facebook Ads targeting local homeowners, and what were the results?
9. What unique selling points set your company apart, like your 35+ years of experience, state-of-the-art equipment, or quick turnaround times for services?
10. How do you measure success in your marketing efforts, such as through lead volume, conversion rates, or return on investment?
11. What challenges are you facing in attracting new clients, like competition from other floor care companies or reaching clients outside your immediate service areas?
12. Do you have any customer testimonials, before-and-after photos, or case studies that we could leverage in advertising campaigns?
13. What is your current marketing budget, and how much are you willing to allocate toward new ad strategies like PPC or content marketing?
14. Are there specific seasons or times of year when demand for your services peaks, such as spring home sales, that we should focus on for targeted ads?
15. How important is online reputation management to you, given your high number of five-star reviews, and do you need help amplifying that?
16. What kind of content do you create or share, like blog posts on hardwood maintenance, and how could we enhance that for better engagement?
17. Have you explored video marketing, such as demos of your refinishing process, and would you be open to producing more visual content?
18. What key performance indicators (KPIs) would you want to track in an ad campaign, like website traffic, quote requests, or service bookings?
19. Are there any specific competitors in the Charlotte area that you’re aware of, and how do you differentiate your services from theirs?
20. What outcomes are you hoping to achieve from partnering with an ad agency, such as a certain percentage increase in leads or improved brand awareness in your target market?

The Enduring Importance of SEO Basics

While GEO is a distinct approach, it overlaps significantly with foundational SEO practices that remain more critical than ever. In the world of AI, there’s no “rank” as we knew it; there are only winners and losers.

However, content efficiency is paramount for AI. Given the constraints of energy costs and chip shortages, AI needs content that is even more streamlined and parseable. So, keep these “hygiene factors” in mind:

• Optimize pages for fast loading and quick processing.
• Implement schema markup to add context to your content.
• Build a conversational, answer-first content architecture.
• Utilize HTML anchor jump links for easy navigation.
• Provide programmatic access to content, such as RSS feeds.
• Allow LLM crawling by using an llms.txt file. llms.txt typically refers to a text file named “llms,” which stands for “Large Language Models.”

In various contexts—especially related to AI, software development, or prompt engineering—llms.txt might contain:

• A list of large language models (e.g., GPT-4, Claude, LLaMA, Mistral).
• Configurations or parameters associated with using these models.
• Prompts or instructions tailored to specific models.
• API keys or endpoints if used in an internal or developer context (less common but possible).

If you’ve encountered a file named llms.txt, it’s likely used to manage, organize, or configure aspects related to large language models, particularly if you’re dealing with applications or scripts interacting with generative AI systems.

While these practices might not be the sole game-changer for AI citation, they make your content more discoverable. If you master GEO, you’ll naturally excel at SEO.

Keep It Human

AI engines aren’t interested in citing boring rehashes – they’re busy doing that job themselves by citing original sources. We firmly believe that LLMs will not want to be retrained on content generated by other AI.

While generative outputs might not be explicitly tagged, it’s often statistically clear to AI engines (and humans) when content is AI-written. AI-generated content often contains common tropes and lacks the nuanced human experience, personal anecdotes, or spontaneous humor that sets truly original content apart.

So, our advice is simple: keep your content written by humans by optimizing your content.

The Future: Targeted, Substantial Value

Getting your content and business brand recommended by AI means providing genuinely new information. Focus on information gain derived from substantive, non-LLM-generated research. Couple this with strong SEO fundamentals and a commitment to human-written content.

The next challenge for businesses like yours is to produce this kind of high-effort, AI-worthy content efficiently and cost-effectively. At Top Click Joe, we’re ready to help you navigate this exciting new landscape.