# AgentFaro > AgentFaro is an AI-search marketing service for residential real estate agents across the United States. We build the websites, profiles, and digital signals that get an agent recommended by AI assistants (ChatGPT, Perplexity, Gemini, Google AI Overviews) and by Google search and the map pack, keep the agent’s presence consistent across every platform that lists them, and report the results with hard numbers every month. Pricing: solo agents $75 per month; teams $400 per month plus $30 per agent seat. No setup fee. - Category: Generative Engine Optimization (GEO) - Tagline: Be the agent AI recommends. - Audience: Residential real estate agents and small teams, typically 10 to 40 transactions per year - Service area: United States - Pricing (set 2026-07-24): solo agent $75/month; team $400/month plus $30 per agent seat; no setup fee - Contact: https://agentfaro.com/contact/ (form; we do not publish an email address) - Last updated: 2026-07-31 ## Answers (full text) ### How do I get my real estate business recommended by ChatGPT? Make yourself the best-documented agent in your market. AI assistants recommend agents whose identity, service area, reviews, and track record are consistent and machine-readable across their website, Google Business Profile, and the sources assistants cite. There is no submission form and no shortcut: you earn the recommendation with signals. ChatGPT does not keep a directory of realtors. When someone asks it who to hire in your market, it draws on two things: what its underlying model learned from the open web, and what its search tools retrieve at the moment of the question. You influence both the same way, by being clearly and consistently documented everywhere a machine might look. That means a website that states who you are, where you work, and what you have done in structured data a model can parse. It means a complete, active Google Business Profile, because local review signals carry heavy weight in who gets named. It means your name, brokerage, and contact details matching exactly across every listing, directory, and profile that mentions you. Inconsistency reads as uncertainty, and models do not recommend what they are uncertain about. #### What actually moves the needle Entity clarity comes first: one unambiguous answer to "who is this agent" across the web. Then content that answers real home buyer and seller questions for your specific neighborhoods, written so an assistant can quote a sentence of it. Then reviews, recent and specific, on profiles the assistants actually read. None of this is a trick, which is why it holds up. Assistants are built to name the agent the evidence supports. The work is making sure the evidence about you is complete, current, and readable. That is the work we do, and we measure it monthly with a fixed set of real questions so you can see your mention rate move. Canonical: https://agentfaro.com/answers/how-do-i-get-recommended-by-chatgpt/ ### How do AI assistants decide which realtor to recommend? Assistants weigh evidence, not advertising. They favor agents with a clear, consistent identity across the web, strong and current review signals, a documented service area and specialty, and content that directly answers the question asked. The agent with the cleanest, most complete evidence usually gets named. When a home buyer asks an assistant for an agent recommendation, the assistant assembles an answer from sources it can retrieve and trust: the agent’s own site, their Google Business Profile, review platforms, local directories, and coverage that mentions them. It is not choosing who spent the most on ads. It is choosing who the record supports. Three patterns show up consistently. First, specificity beats breadth: an agent clearly documented as working a particular set of neighborhoods, at particular price points, gets named for questions about that territory. Second, corroboration matters: the same facts appearing identically in several independent places reads as reliability. Third, recency counts: a profile that has been active this month outweighs one that went quiet last year. #### Why most agents are invisible to assistants Most agent websites are built for people who already found them, not for machines deciding whom to surface. Brokerage profile pages bury individual agents under the brokerage’s own entity. Review counts sit on platforms assistants weigh lightly. The raw material is often there; it just is not legible. Making it legible is an engineering job: structured data, entity consistency, answer-shaped content, and an active profile. That is the substance of what we run for clients, and the reason the work is checkable: either the assistants start naming you or they do not, and we report which. Canonical: https://agentfaro.com/answers/how-do-ai-assistants-choose-a-realtor/ ### What is generative engine optimization (GEO)? Generative engine optimization is the practice of making a person or business the answer AI assistants give, rather than one of the links a search engine lists. It covers the structure, content, and consistency signals that determine whom ChatGPT, Perplexity, Gemini, and Google AI Overviews name when asked for a recommendation. Classic SEO competes for position on a results page a human will scan. GEO competes for a different surface: the single answer an assistant composes. The two overlap heavily in their inputs, and good GEO work usually improves classic rankings too, but the target is different. A results page has ten winners. An answer usually has one, sometimes three. In practice GEO means writing content that answers questions directly enough to be quoted, marking up every page with structured data so a machine can extract the facts, keeping the subject’s identity consistent everywhere it appears, and maintaining the profile and review signals assistants lean on for local questions. See our full explainer for the mechanics. #### Why it matters for real estate specifically Choosing an agent is exactly the kind of high-stakes, low-information decision people now hand to assistants. The question "who is a good realtor near me" has moved from a search box, where an agent could buy their way onto the page, to a chat window, where they cannot. The agents who adapt to that shift early hold an advantage that compounds, because the signals GEO builds accrue over time. For the terms used in this field, see the glossary. For whether the work is paying off, the test is simple and measurable: ask the assistants and count. That count, run against a fixed question set each cycle, is exactly what our monthly report shows. Canonical: https://agentfaro.com/answers/what-is-generative-engine-optimization/ ### Does my Google Business Profile affect AI search results? Yes, heavily. For local questions, AI assistants lean on the same signals that drive the Google map pack: profile completeness, review volume and recency, category accuracy, and activity. A complete, active Google Business Profile is the single highest-leverage input for getting named in both places. Local recommendation questions get local evidence. When an assistant is asked about agents in a specific place, profile data is among the most structured, most trustworthy evidence available to it: verified location, service area, categories, hours, reviews with dates and text. Assistants and the map pack drink from the same well. That makes the profile unusually efficient to invest in. The same work that moves your map pack position, complete fields, accurate categories, steady posts and photos, prompt review responses, also feeds the evidence an assistant weighs. One input, two surfaces. #### What a well-run profile looks like Every field filled and accurate. Categories chosen deliberately rather than defaulted. New photos and posts on a steady cadence, review responses within days, and questions answered before a stranger answers them for you. Name, address, and phone matching every other listing of your business to the character, because consistency is itself a ranking signal. Most agents have a profile; few run one. Running it is a weekly discipline, which is why it is one of the core things we take over for clients. Canonical: https://agentfaro.com/answers/does-google-business-profile-affect-ai-search/ ### How do I know if AI assistants are recommending me? Ask them and count. Put a fixed set of realistic home buyer and seller questions to ChatGPT, Perplexity, Gemini, and Google AI Overviews, and record how often you are named. Repeat the same set on a schedule and the trend tells you whether your visibility work is paying off. There is no dashboard inside the assistants that shows this, so you measure from the outside. The method is a prompt battery: a fixed list of questions a real home buyer or seller in your market would ask, phrased the way people actually phrase them. Run every question across the major assistants, note who gets named, and compute your mention rate. Two details make the measurement honest. The question set must stay fixed, because changing the questions between runs makes the trend meaningless. And the questions must be realistic, not engineered to flatter you. "Who is the best realtor for a first home in Plano" is a real question. A question written so that only you could be the answer is not. #### What to do with the number A single run tells you where you stand today. The value compounds when you rerun the same battery every cycle: now you can connect the work done, a rebuilt website, a revived profile, new neighborhood content, to movement in the number. That connection between work and result is what most marketing never shows you. This measurement is the spine of our monthly report, alongside your Google rankings and the leads delivered. If you want to see where you stand before committing to anything, request a free audit and we will run a battery for your market. Canonical: https://agentfaro.com/answers/how-do-i-know-if-ai-recommends-me/ ### Do real estate agents still need SEO in 2026? Yes, but the target has widened. Google search and the map pack still deliver real home buyers and sellers, and the same underlying signals now also decide who AI assistants recommend. The right strategy treats classic SEO and AI visibility as one body of work, because for a local agent they mostly are. People have not stopped using Google. They have added assistants alongside it, and Google itself now answers many searches with an AI Overview before the first link. So the honest answer is not "SEO is dead" or "nothing changed." Both surfaces matter, and they reward substantially the same fundamentals: clear identity, real local content, strong reviews, technical soundness. What has changed is the cost of being mediocre. A results page has room for you at position six. An AI answer does not. As more discovery moves into single-answer surfaces, the gap between the recommended agent and everyone else widens. #### Where the effort goes now For a local agent, the priorities are concrete: a technically clean site with structured data, hyperlocal content for the neighborhoods you actually work, a managed Google Business Profile, and consistent listings everywhere your name appears. That set serves the map pack, organic rankings, and assistant recommendations at once. What is worth less than it used to be: thin content written for keyword volume, link schemes, and anything else built to game a ranking rather than document a reality. Assistants are harder to fool than a 2015 results page, and the penalty for getting caught is applied by machines that do not send appeal forms. Canonical: https://agentfaro.com/answers/do-agents-still-need-seo/ ### What should a real estate agent’s website actually do? Two jobs: convince the humans who look you up, and document you for the machines that decide who gets recommended. Most agent sites attempt only the first. A site doing both is fast, states your market and track record plainly, carries structured data on every page, and answers the questions your home buyers ask. Almost no one finds an agent by browsing websites. They find a name through a referral, a listing, a search, or increasingly an assistant, and then they look the name up. Your site is where a lead confirms or abandons a decision that is already in motion, and it is a primary source machines read when deciding whether to surface you at all. The confirmation job takes clarity: who you are, where you work, what you have sold, what clients say, and how to reach you, all reachable in seconds on a phone. The documentation job takes engineering: structured data that states your identity and service area in machine-readable form, pages for each neighborhood you work, and content shaped to answer real questions rather than to fill space. #### What it does not need It does not need an IDX search portal better than Zillow’s, because it will not beat Zillow at that and does not have to. It does not need animation-heavy design that costs three seconds of load time. And it should not be a page inside your brokerage’s site, where your identity is subordinate to theirs and disappears when you move. The site should be an asset you own, on a domain you keep. That is how we build them: the agent owns the domain, full stop. It stays yours if you leave. Canonical: https://agentfaro.com/answers/what-should-an-agent-website-do/ ### How much does marketing cost for a real estate agent? Typical ranges run from a few hundred to several thousand dollars a month across agencies, coaching programs, and portal lead products. AgentFaro is priced flat and published openly: $75 per month for a solo agent, $400 per month plus $30 per seat for teams, no setup fee. One closed transaction covers years of it. The market is opaque on purpose. Agencies quote after a sales call, portal lead programs price by zip code and competition, and the number an agent actually pays is usually a negotiation artifact. That opacity favors the seller, which is reason enough to distrust it. We publish our pricing because the economics survive daylight. Seventy-five dollars a month for a solo agent buys the website, the managed profile, the visibility work, and the monthly measurement, run for you rather than handed to you as homework. Full detail is on the pricing page. #### How to evaluate any marketing spend Ask one question of every vendor: what number will you show me each month, and what happens when it does not move. Impressions and reach are not answers; they are what gets reported when nothing countable happened. Mention rate, rankings, and delivered leads are answers. That standard is the one we hold ourselves to. The monthly report exists so that continuing to pay us is a decision you make looking at numbers, not a subscription you forgot to cancel. Canonical: https://agentfaro.com/answers/how-much-does-real-estate-marketing-cost/ ## Glossary (full text) ### Generative engine optimization (GEO) The practice of making a person or business the answer AI assistants give. GEO covers the content, structure, and consistency signals that determine whom ChatGPT, Perplexity, Gemini, and Google AI Overviews name when asked for a recommendation. Where classic SEO competes for position on a results page, GEO competes for the answer itself. The inputs overlap: clean technical foundations, real content, strong reviews. The difference is the shape of the goal. A page of results rewards being present; an answer rewards being the best-supported choice. For a local real estate agent, GEO work concentrates on entity clarity, answer-shaped local content, an active Google Business Profile, and consistent citations. It is the core of our AI search visibility service. Canonical: https://agentfaro.com/glossary/generative-engine-optimization/ ### Answer engine optimization (AEO) Structuring content so an answer engine can quote it directly: the question stated plainly, the answer given first in a complete and self-contained form, and supporting detail after. AEO is the writing discipline inside the broader practice of GEO. Assistants compose answers from fragments they can lift with confidence. A page that buries its answer under six paragraphs of preamble gives them nothing to lift. A page that opens with a direct, accurate, fifty-word answer gives them exactly what they need, with your name attached. This page, and every page in our answers section, is written that way on purpose. The same structure goes into the neighborhood and specialty content we build for clients. Canonical: https://agentfaro.com/glossary/answer-engine-optimization/ ### Prompt battery A fixed set of realistic questions used to measure AI search visibility. The same questions are put to the major assistants on a schedule, and the share of answers naming a given agent is their mention rate. Keeping the set fixed is what makes the trend meaningful. A useful battery is built from questions real home buyers and sellers ask, phrased the way people phrase them: "who is a good realtor for a first condo in Arlington," not keyword strings. It spans the agent’s actual neighborhoods and specialties, and it does not change between runs, because a moving measure measures nothing. The battery is our core measurement instrument. It runs against ChatGPT, Perplexity, Gemini, and Google AI Overviews, and the resulting mention rate leads the monthly report. Canonical: https://agentfaro.com/glossary/prompt-battery/ ### Mention rate The percentage of prompt battery questions for which an agent is named in the assistant’s answer. Measured per assistant and in aggregate, on a fixed question set, so movement over time reflects real change in visibility rather than a change in the questions. Mention rate is the closest thing AI search has to a ranking. It is honest in a way most marketing metrics are not: either the assistant named you or it did not, and anyone can rerun the question and check. A single reading matters less than the trend. The number moving from two mentions in twenty to seven in twenty across a quarter is evidence the underlying work is landing. Canonical: https://agentfaro.com/glossary/mention-rate/ ### Map pack The block of usually three local business results, with a map, that Google shows for searches with local intent. Placement is driven largely by Google Business Profile signals: proximity, relevance, review strength, and activity. For an agent, the map pack is prime placement for searches like "realtor near me" or a neighborhood search with local intent. It is governed by different mechanics than the ordinary results below it, which is why a well-ranked website and an absent map presence often coexist. The inputs that win the map pack, a complete and active profile with strong recent reviews, are largely the same inputs AI assistants weigh for local recommendations. Work invested here pays on two surfaces. Canonical: https://agentfaro.com/glossary/map-pack/ ### Google Business Profile (GBP) Google’s listing for a local business: identity, service area, categories, hours, photos, posts, reviews, and Q&A. Formerly called Google My Business. For local search and AI recommendations alike, it is the highest-leverage single asset an agent controls. The profile feeds the map pack directly and supplies much of the structured local evidence AI assistants rely on. Completeness, category accuracy, review volume and recency, response behavior, and posting activity all count. The difference between having a profile and running one is the difference between existing and competing. Running one is a weekly discipline of posts, photos, review responses, and Q&A, which is exactly the work our GBP management service takes over. Canonical: https://agentfaro.com/glossary/google-business-profile/ ### Entity A distinct thing a machine can identify and reason about: a person, a business, a neighborhood. Search engines and AI models organize knowledge around entities, so an agent whose identity is clear and consistent everywhere is an entity a machine can confidently recommend. Entity clarity fails in mundane ways: a name spelled three ways across directories, an old brokerage still attached to half your listings, two half-maintained profiles splitting your reviews. Each inconsistency makes the machine less certain you are one findable thing, and uncertainty suppresses recommendation. Building entity clarity means one canonical statement of who you are, propagated identically everywhere, and marked up in structured data so nothing is left to inference. Canonical: https://agentfaro.com/glossary/entity/ ### Structured data Machine-readable annotations, usually schema.org JSON-LD, embedded in a web page to state its facts explicitly: this page is about a real estate agent, with this name, this service area, this brokerage. It removes the guesswork from how machines read you. A human infers from layout and prose. A machine parsing your site does better with declarations: a RealEstateAgent node with a name, an areaServed, and reviews, connected to the same identifiers used elsewhere on the web. Pages with clean structured data are eligible for richer treatment in search and are easier for assistants to cite accurately. Every page we ship carries a structured data graph, including this one. View source on this site and the annotations are there to read. Canonical: https://agentfaro.com/glossary/structured-data/ ### NAP consistency Name, address, phone: the practice of keeping business identity details exactly identical across every listing, directory, and profile. Character-level consistency is a trust signal; variation reads as uncertainty about who and where you are. Machines cross-reference. When your profile says one suite number, an old directory says another, and your site omits the address entirely, the mismatch costs more than any single listing is worth. The fix is unglamorous: an audit of everywhere your identity appears, corrections, and a canonical record that every future listing copies. NAP work is part of the identity cleanup in every AgentFaro engagement, because it is a prerequisite for the rest of the signals to be believed. Canonical: https://agentfaro.com/glossary/nap-consistency/ ### llms.txt A proposed convention for a plain-text file at the root of a website that orients AI systems: what the site is, what it offers, and where its key pages are. An emerging standard with growing adoption, not yet universally read. The idea parallels robots.txt: a stable, predictable place for machine guidance. An llms.txt file gives a language model a clean summary and a map of canonical URLs, which beats forcing it to infer both from navigation menus. We publish one at agentfaro.com/llms.txt, along with an expanded companion file and per-assistant documents, and we are plain about which of these are established conventions and which are forward bets. Details on our For AI page. Canonical: https://agentfaro.com/glossary/llms-txt/ ### AI crawler An automated agent that fetches web content for an AI system: for training corpora, for search and answer indexes, or live at a user’s request. Examples include GPTBot, ClaudeBot, PerplexityBot, and Google-Extended. Each can be allowed or refused in robots.txt. Many sites block AI crawlers by default, sometimes deliberately, often by accident of a template. A blocked crawler cannot read the evidence that would get you recommended: blocking Google-Extended, for instance, withholds your content from Gemini grounding. For anyone whose business depends on being recommended, the calculus favors access. We allow the major AI crawlers explicitly and deliberately, and checking a client’s site for accidental blocks is one of the first things our audit looks at. Canonical: https://agentfaro.com/glossary/ai-crawler/ ### Citation In AI search, a source an assistant links or references in support of its answer. Being cited puts your page in front of the user at the moment of decision. In local SEO the word also means any listing of a business’s name, address, and phone; both senses matter here. Assistants that show their sources, Perplexity most visibly, turn every answer into a short reading list. Content gets cited when it is specific, verifiable, and shaped so a fragment of it answers the question outright. Vague content does not get cited; it gets summarized anonymously, which earns you nothing. The local-SEO sense of citation, a directory listing of your business details, feeds NAP consistency. The two senses meet in the same place: machines deciding how much to trust the record about you. Canonical: https://agentfaro.com/glossary/citation/ ### Knowledge graph A machine’s map of entities and the relationships between them: this agent, works in these neighborhoods, at this brokerage, with these reviews. Search engines and assistants consult knowledge graphs to ground who is who before composing an answer. When the graph’s picture of you is rich and consistent, machines can answer questions about you confidently and connect you to relevant queries. When it is sparse or contradictory, you are functionally invisible for recommendation purposes, whatever your actual track record. You feed the graph through structured data, consistent citations, and authoritative profiles. That feeding is deliberate work, and it is the quiet majority of what effective GEO consists of. Canonical: https://agentfaro.com/glossary/knowledge-graph/ ### E-E-A-T Experience, Expertise, Authoritativeness, Trustworthiness: the qualities Google’s systems are designed to reward in content and its authors. Not a direct ranking factor but a description of what the ranking systems try to detect, and a useful standard for AI answers too. For an agent, E-E-A-T translates concretely: content grounded in transactions you actually closed and streets you actually know, an identifiable author with a documented track record, and claims that check out against public records and reviews. Machine evaluators are imperfect at detecting these qualities, but they improve every year, and they are already good enough to punish fabrication. The practical rule: publish what you can stand behind, under your own name, with the evidence attached. It is also simply the right way to operate. Canonical: https://agentfaro.com/glossary/e-e-a-t/ ### Local SEO Search optimization for businesses that serve a geographic area: winning the map pack, ranking for "near me" and neighborhood searches, and maintaining the profile and citation signals local algorithms weigh. For agents, the foundation that AI visibility builds on. Local SEO differs from general SEO in its inputs: proximity, Google Business Profile strength, review signals, and locally relevant content count for more; sitewide domain authority counts for less. An agent can outrank national portals for neighborhood queries by being genuinely, documentably local. The same local evidence now feeds AI assistants answering local questions, which is why we treat local SEO and GEO as one program rather than two line items. Canonical: https://agentfaro.com/glossary/local-seo/ ### Schema.org The shared vocabulary of types and properties (RealEstateAgent, Review, Service, Place) that Google, Bing, and AI systems all agree to read. It is the dictionary structured data is written in: a common language for stating facts machines can trust. Schema.org exists because every search engine inventing its own markup would have doomed the idea. The major engines maintain it jointly, which is why one correctly marked page is legible to all of them, and increasingly to the assistants grounding their answers in the same web. For an agent, the types that matter are RealEstateAgent, the review and rating types, and the place types that document a service area. We write them in JSON-LD on every page we build. Canonical: https://agentfaro.com/glossary/schema-org/ ### JSON-LD The format Google recommends for structured data: a small block of JSON inside a script tag in the page, describing the entities on it and their relationships without changing anything a visitor sees. Its virtue is separation: the markup lives in one clean block rather than being woven through the visible HTML, which makes it easy to generate correctly, easy to validate, and easy for a crawler to extract. Every page on this site carries one; view source and it is the script block near the top. The alternative formats, microdata and RDFa, still parse, but JSON-LD is where the tooling and the recommendations have settled. There is no reason to choose anything else for a new build. Canonical: https://agentfaro.com/glossary/json-ld/ ### RealEstateAgent (schema type) The schema.org type purpose-built for describing an agent or agency: name, service area, brokerage affiliation, contact details, reviews. Using it, rather than a generic type, tells machines exactly what kind of business they are reading about. Specificity pays. A machine that knows a page describes a RealEstateAgent, with a service area of particular places, can connect that entity to realtor questions with a confidence a generic Organization node never earns. The type also anchors the rest of the graph: reviews attach to it, the brokerage links from it, and sameAs ties it to the agent’s profiles across the web. It is the center of the structured identity we build for every client. Canonical: https://agentfaro.com/glossary/real-estate-agent-schema/ ### sameAs A schema.org property listing the authoritative URLs that describe the same entity: your Zillow profile, LinkedIn, Google Business Profile, brokerage page. It is the main lever for telling machines that all those scattered profiles are one person. Machines meet you in fragments: a portal profile here, a directory listing there, a website somewhere else. sameAs is the explicit declaration that stitches the fragments into one entity, which is precisely the consolidation a knowledge graph needs before it can recommend you confidently. It only works if the profiles it points to agree with each other, which is why sameAs markup and presence sync are two halves of the same job. Canonical: https://agentfaro.com/glossary/sameas/ ### Rich result A search listing enhanced beyond the standard blue link: star ratings, breadcrumbs, FAQ dropdowns, images. Valid structured data makes a page eligible; Google still decides case by case whether to show the enhancement. Rich results earn more attention and more clicks from the same ranking position, which makes them one of the few ways to outperform a competitor who technically outranks you. Eligibility is mechanical: the right schema types, validly expressed. Display is not guaranteed, and anyone promising specific rich results is promising Google’s behavior, which is not theirs to promise. We build eligibility everywhere it applies and report what actually shows. Canonical: https://agentfaro.com/glossary/rich-result/ ### Featured snippet The answer box at the top of Google search results, lifted directly from the visible content of a page rather than from schema. Pages win it by answering a question plainly, early, and in the shape Google wants to display. The snippet is a preview of the AI era that arrived years ahead of it: one answer, extracted, above every ranked result. The writing that wins snippets, the question stated and the answer given whole in the first sentences, is the same writing that gets quoted by assistants. That is why our content is answer-first as a rule. The answers section of this site is the pattern, applied to ourselves. Canonical: https://agentfaro.com/glossary/featured-snippet/ ### People Also Ask The expandable list of related questions on a Google results page, each answered with a passage lifted from a web page. A page that answers a specific question directly can appear here even when it ranks far below the front page for the broad term. People Also Ask is a side door. An agent who will not outrank the portals for a broad homes-for-sale term can still own the answer to a specific home buyer question, because the box rewards the best direct answer rather than the biggest site. Each question it shows is also market research in plain sight: these are the literal questions home buyers and sellers ask, and every one is a candidate page in a content program. Canonical: https://agentfaro.com/glossary/people-also-ask/ ### AI Overview Google’s AI-generated answer at the top of the results page, synthesized from sources it cites. It reads content passage by passage and favors direct answers, clear structure, and named facts it can attribute. AI Overviews matter because of where they sit: above every ranked result, on the default search engine of the world. When one appears for a question in your market, whoever it cites has effectively been moved to position zero, and everyone below has been moved down. Because Overviews ground heavily in the regular index and local signals, the inputs are familiar: liftable answers, clean structured data, a strong profile, consistent identity. It is one of the four assistants our prompt battery measures. Canonical: https://agentfaro.com/glossary/ai-overview/ ### Knowledge panel The information box Google shows beside results for an entity it recognizes: photo, description, profiles, facts. It is generated from the Knowledge Graph rather than from any single page, and it is earned by being consistently documented, not requested. A panel appearing for your name is the visible symptom of the invisible thing this whole practice builds: Google holding a confident, consolidated record of who you are. There is no application form; there is only evidence, accumulated and reconciled. The inputs are the usual suspects working together: strong structured data with sameAs links, agreeing profiles across the web, and authoritative references to your name. Local agents most often surface first through their Google Business Profile panel. Canonical: https://agentfaro.com/glossary/knowledge-panel/ ### Canonical URL The single preferred address for a piece of content when it is reachable at more than one. The canonical tag tells search engines which version to index and credit, so duplicates consolidate instead of competing with each other. Duplication happens innocently: with and without the www prefix, tracking parameters, a listing syndicated to three portals. Left unresolved, each copy splits the credit the content earns. The canonical tag resolves it by declaring one address the real one. Every page we build declares its canonical, and every citation surface we manage points at it, so anything earned anywhere accrues to one place. Canonical: https://agentfaro.com/glossary/canonical-url/ ### Indexing A search engine storing a crawled page so it can appear in results. Crawled does not mean indexed, and only indexed pages can rank or be cited; a page the index skipped is invisible regardless of its quality. Indexing is where quiet failures live. A site can look finished and be largely absent from the index because of blocked crawlers, broken canonicals, thin duplicated pages, or never being submitted at all. The owner rarely knows, because the site works fine when they visit it. The check is direct: search engines report what they hold, and a scoped site search approximates it in seconds. It is among the first things our audit verifies, along with whether the crawlers feeding AI assistants can get in at all. Canonical: https://agentfaro.com/glossary/indexing/ ### Core Web Vitals Google’s page-experience metrics: how fast the main content loads, how quickly the page responds to interaction, and how much the layout shifts while loading. Measured from real visits, and a factor in rankings. The metrics formalize what visitors already punish: slow, unstable pages lose people before the content gets a chance. For agent sites the common offenders are oversized photos, third-party widgets, and page builders that ship a small application to render a paragraph. Static pages with restrained scripts pass comfortably, which is one reason we build that way. This site ships no JavaScript at all, and that is not a stunt; it is the discipline, applied. Canonical: https://agentfaro.com/glossary/core-web-vitals/ ## Services ### Websites that AI can read A fast, static website built so search engines and AI assistants can read every fact on it: structured data on every page, clean entity signals, and hyperlocal pages for the neighborhoods you work. You do not manage it. We do. Canonical: https://agentfaro.com/services/agent-websites/ ### Profile and GBP authority Full management of your Google Business Profile: posts, photos, review responses, questions and answers, categories and attributes, kept consistent with every other place your name appears. The single highest-leverage input for both the map pack and AI answers. Canonical: https://agentfaro.com/services/google-business-profile/ ### Digital presence sync Your name appears on dozens of platforms whether you maintain them or not: Zillow, Realtor.com, Google, Yelp, Facebook, LinkedIn, and the rest. Machines cross-reference all of them. We audit the full matrix, fix the mismatches, claim the strays, and keep every listing telling the same story. Canonical: https://agentfaro.com/services/digital-presence/ ### AI search visibility The flagship: getting you named when a home buyer or seller asks ChatGPT, Perplexity, Gemini, or Google who to work with. We engineer the signals models read, then measure your mention rate against a fixed set of real questions, every cycle. Canonical: https://agentfaro.com/services/ai-search-visibility/