The Local AI Visibility Playbook.

Contents

1. 01 · The shift that already happened
2. 02 · How AI assistants decide who to cite
3. 03 · The four engines, briefly
4. 04 · The Visibility Loop
5. 05 · The fixes that actually move the needle
6. 06 · What to skip (it won't help)
7. 07 · How to know it's working
8. 08 · What to do this week

Twenty years ago, when someone needed a plumber, they opened the phone book. Then for fifteen years, they Googled it and scrolled a list of ten blue links. Today, more and more of them open ChatGPT and ask “who’s the best plumber near me?” — and the AI gives them one answer. Maybe two.

That’s the whole shift. From a list of ten to a single name. It changes everything about how a local business needs to position itself online, and most local businesses haven’t noticed.

The numbers people quote about AI search adoption are still small-ish — somewhere between 10% and 30% of searches depending on who’s measuring and which category. But two things are true: (a) it’s growing fast, and (b) the people using AI search first are disproportionately younger, more affluent, and more decisive — exactly the customers most local service businesses want.

More importantly: the businesses that get cited by AI now build durable defaults. When ChatGPT consistently names you for “best HVAC tech in Marietta,” that becomes self-reinforcing — every conversation that produces your name trains future citations. The compounding works in your favor or in your competitor’s. Being early is structurally valuable.

Modern AI assistants build their answers from two sources: training data (what the model learned during training, essentially a snapshot of the public web at some past date) and retrieval (real-time fetching of pages, listings, and structured data when the user asks something current).

For local recommendations — “best [trade] in [town]” — retrieval matters most. The assistant queries its tools, pulls content from sites it can read, weighs authority signals, and picks one or two names to surface. The signals it weighs are different from traditional Google SEO ranking signals, but they overlap.

The signals that matter

• Structured data. Schema markup tells the AI exactly what your page means — that you’re a LocalBusiness, what services you offer, what your hours are, what reviews say. AI assistants prefer to cite sources where the meaning is unambiguous. Most local sites have no schema at all.
• Topical clarity. If your site says “we do everything,” the AI doesn’t know what to cite you for. If it says “we are the best at residential HVAC installation in greater Richmond,” the AI has something to extract.
• Authority and reputation signals. Reviews, citations in trusted directories (Google Business, BBB, Angi, industry associations), credentials, manufacturer certifications, press mentions. The AI doesn’t just count them — it weights their credibility.
• Q&A-shaped content. AI assistants prefer to quote content that already looks like an answer. A page with a clear question and a concise answer beats a page with a wall of marketing copy, even if the marketing copy is technically better-written.
• Freshness. Pages updated recently outweigh pages that haven’t changed in years, especially for local recommendations where the AI is wary of citing a business that might no longer exist.

None of these signals are secret or magical. They’re all things a local business can build. The reason most don’t is that the agencies they hire are still selling 2018 SEO and don’t know to do this work.

There are dozens of AI assistants, but four matter for local recommendations today:

• ChatGPT (OpenAI) — the largest by usage. Uses Bing for real-time browsing, plus its own training data. Tends to be conservative about local recommendations, favoring businesses with strong directory presence and review surface.
• Claude (Anthropic) — has web search and tends to cite sources prominently. Weights authoritative sources (industry press, professional associations, major directories) heavily. Particularly important for legal and medical categories.
• Gemini (Google)— the engine behind Google’s AI Overviews. Has direct access to Google’s entire search index plus Google Business Profile data. If your GBP is strong, you’re already ahead with Gemini.
• Perplexity — built around real-time web search with visible citations. Smaller user base but disproportionately power users. Citations are prominent and clickable, so showing up on Perplexity drives direct traffic faster than the others.

The good news: the work that gets you cited by one mostly gets you cited by all four. The signals overlap. You don’t need four different strategies — you need one strategy executed well.

This is the five-step process we run on every client engagement. We named it “The Visibility Loop” because step 5 feeds back into step 1, and the wins compound month over month. You can run this yourself if you have the time and the technical comfort. We do it for clients who don’t.

Step 01 · Audit

Score where you stand. The mechanical version: open ChatGPT, Claude, Gemini, and Perplexity. Run twenty queries a customer might ask — variations of “best [your trade] in [your town],” “[problem] near me,” “who does [specific service] in [neighborhood].” Note which ones name you, which name competitors, which name nobody.

Most local businesses score zero. That’s the baseline you’re working from. Don’t skip writing it down — you need a before number to know you’ve moved.

Step 02 · Map

Find the queries that matter — not the ones a keyword tool surfaces, but the ones your customers actually ask AI. The two sources we use:

• The People Also Ask box on Google for your trade and town. Those are real questions real people ask.
• Your sales calls. The first three questions every prospect asks you on the phone — those are also the first three things they tried to ask AI before calling.

Map each query to the page on your site that should be the answer. If no page exists, that’s a content gap. Write it down.

Step 03 · Fix

This is the work most agencies skip. We do it ourselves. The order of operations:

• Schema markup first. Add LocalBusiness, Service, and FAQPage schema to your top pages. This is the single highest-leverage technical move and most local sites have none of it.
• Rewrite service pages with Q&A blocks. Each service page should answer 4–6 of the questions from step 2, concisely, near the top of the page. Marketing copy below.
• Google Business Profile completeness. Categories, services, photos, hours, attributes, posts. GBP is one of the strongest signals AI assistants use to find local businesses.
• Listings consistency. NAP (name/address/phone) match across the directories AI pulls from — Google, Yelp, Apple Business Connect, BBB, your industry-specific directories. Inconsistencies hurt you.
• Service area pages. One page per major service area with locally relevant content. Not doorway pages — actual useful pages with the local context (neighborhoods served, local conditions, local examples).

Step 04 · Monitor

Re-run your audit queries weekly. Track which engines name you, for which queries, and how that’s trending. We do this in a spreadsheet for clients and email a one-page summary monthly. No dashboard. The metric is binary per query: cited or not cited. Trends emerge.

Important: AI assistants give different answers to different people sometimes (personalization, location, model version), and the same person twice. Don’t panic on a single negative result. Look at the rolling average across multiple tests.

Step 05 · Iterate

AI search shifts. New models ship every few months. Ranking signals change. New schema types get supported. Your monitoring from step 4 tells you what’s working — double down. What isn’t — diagnose and adjust.

The compounding is the point. A business that does this work consistently for a year is essentially uncatchable by a competitor starting from zero. AI assistants tend to keep citing whoever they’ve cited before, because that’s what their training data and retrieval bias toward.

If you do nothing else from this playbook, do these five things, in this order. They’re ranked by impact-per-effort for a typical local service business.

1. Add schema markup to your service pages

JSON-LD format. LocalBusiness schema on the homepage, Service schema on each service page, FAQPage schema on any page with a Q&A block. There are free generators online. If you’re on WordPress, plugins do most of it. The work is making sure the schema is correct (it gets validated by Google’s Rich Results Test) and that it actually matches the visible content.

2. Add an FAQ block to every service page

Six questions a real customer asks before booking. Concise answers in the first sentence, more context underneath. Wrap each question in proper heading tags and FAQPage schema. AI assistants quote these blocks directly when they line up with a user’s question.

3. Make your Google Business Profile complete and active

Fill out every field. Add photos monthly. Respond to every review (good and bad) within 48 hours. Post weekly. GBP completeness is the single strongest local signal across all four AI assistants — it’s the first thing they check.

4. Build out service area pages

One page per major area you serve. The page needs to be actually useful, not a copy-paste template with the city name swapped. Local landmarks, local conditions, local examples, local testimonials. The AI can tell when a page is genuinely about a place and when it’s a doorway.

5. Get cited by adjacent authority sources

Local press, industry directories specific to your trade, the chamber of commerce, professional associations. One real citation in a place with editorial weight beats ten directory listings. AI assistants weight where you’re mentioned, not just how often.

A short list of things you’ll see other agencies and self-help blogs recommend. Most of it is recycled 2015 SEO advice that either doesn’t apply to AI search or actively hurts you.

• Buying backlinks from link farms. AI assistants detect link patterns and discount bought links. You can hurt your own visibility this way.
• Stuffing keywords. AI assistants understand language semantically. Repeating “best HVAC near me” thirty times on a page makes the page look spammy and lowers your authority signal.
• Generating thin content with AI. The irony — using ChatGPT to write five hundred service pages so you can rank in ChatGPT. AI can detect AI-generated content patterns and deprioritizes them. Use AI to draft, but a human needs to edit and add real local detail.
• Doorway pages with city names swapped. Google penalized this years ago. AI assistants are smarter about it than Google was — they read the page and notice when nothing meaningful changed except the city name.
• Promises of overnight results. Anyone telling you they can get you cited by ChatGPT “in a week” is selling you something. Realistic timeline: 30–90 days for the first citations to start appearing, 3–6 months for it to become a meaningful share of inbound.
• Ignoring Google. Some AEO content frames Google as dead. It isn’t. Google is still where the majority of search happens, and Google’s own AI Overviews use the same signals as classical SEO. Optimize for both. The work overlaps.

Two metrics matter. Everything else is noise.

Leading metric — citation count by query

Pick your top 20 customer queries. Run them weekly across all four AI assistants. Count how many name you. The number going up means the work is working. The number staying at zero after 90 days means something’s broken — usually schema, GBP, or a fundamental site issue.

Lagging metric — booked jobs from inbound

Track call volume and form submissions to your tracked phone number and forms. AI search inbound is hard to attribute cleanly (no UTM, no referrer in many cases) — what you’re looking for is rising inbound that doesn’t correlate with paid spend or new GBP posts. That residual lift is your AI visibility paying off.

What to ignore

• Impressions and CTR from Search Console. AI search traffic mostly doesn’t show up there. Don’t use Search Console as your AEO scorecard.
• Domain Rating (DR), Domain Authority (DA), other agency vanity metrics. They’re proprietary scores from SEO tool vendors and AI assistants don’t use them.
• Anyone claiming a positional rank on a single AI engine — “you’re #2 in ChatGPT for plumber queries.” That’s a meaningless claim because AI assistants don’t return ordered lists the way Google does. A single query is binary: cited or not. (A composite visibility scoreacross many queries and signals — citation rate, schema coverage, GBP completeness, listing consistency — is a different thing and a useful one. We use one. Don’t confuse the two.)

If you read this far, here’s the smallest set of steps that produces a real improvement, in roughly the time you have on a Friday afternoon.

• Open ChatGPT, Claude, Gemini, and Perplexity. Run five queries a customer might ask about your business. Write down who they name.
• If you’re not named in any of them, that’s your starting point. If you are, note which engines and which queries — that’s your foundation to build on.
• Open your Google Business Profile. Fill in every field that isn’t filled. Add five recent photos. Respond to every unanswered review.
• Pick your most important service page. Add an FAQ block of five real questions and concise answers. Add LocalBusiness and FAQPage schema (or pay someone to).
• Re-run your queries in 30 days. Compare.

That’s the whole foundation. The deeper work — the schema across every page, the listing consistency across twelve directories, the service area pages, the monitoring cadence, the iteration loop — is what we do for clients who want it done right and don’t want to manage it themselves.

Want this done for you?

We’ll audit your business this week, and fix it the next.

The free audit covers everything in this playbook — your visibility across all four AI engines, your schema gaps, your listings hygiene, your competitive position. Then we tell you what we’d fix first.