Introductory rate: full Core at $249/mo, or $199 paid annually. Through December 31, 2026

Research Visibility Analyzer

Are you named before buyers choose a dealership?

Enter your website. We check who AI names while buyers compare dealers in your market, show the sources, and identify which dealer facts could make your content more useful. Inventory readability is included. Free.

Run the check

Get the full report on screen. No email required to see it. AI answers change day to day, so if you’ve already run a check, just run another one for today’s read.

No card required. You can email yourself a PDF after.

ILLUSTRATIVE SAMPLE · BUILT FROM ILLUSTRATIVE DATA, NOT A REAL SCAN

Sample dealership is missing from AI answers shoppers trust.

We ran 4 real shopper queries across 1 AI engine: Gemini. Your dealership was cited in 1 of 4 answers, and absent from the rest.

Run it on your site →

Free to get published. No card, no call.

CITED IN 1 OF 4 ANSWERS
C62/100AI readiness
1 / 4
AI answers that cite Sample dealership
47
Vehicle pages invisible to AI crawlers

WHAT WE COULD NOT READ

Your pages need JavaScript to show their content.

The HTML returned on the first request carried no readable inventory content.

Roughly 69% of AI crawlers cannot execute JavaScript, so that is the version they read.

We could not read your vehicles.

Your inventory pages did not return vehicle detail we could parse.

Questions a shopper asks about specific cars are the ones we could not put to the engines.

We could not tell whether you run more than one location.

Your locations page was not reachable, or not linked where we could find it.

If you do have other stores, engines answering "dealership near me" in those cities have the same problem finding them.

The evidence

What the engines actually answered

WHAT WE ASKED · SAMPLE

These are the 4 questions we put to the engine.

Word for word, exactly as a shopper would type them. Every finding below comes from the answers to these, nothing else.

Research questions test documented policies before a dealer visit. Optional inventory questions use your scanned stock.

The questions
  • “Where should I buy a used car in Carleton Place, Ontario?”
    BEFORE THE DEALER VISITA saved buyer or supporting research question; its wording does not establish your inventory, services or search demand
  • “Where should I buy a used car in Ottawa, Ontario?”
    BEFORE THE DEALER VISITA saved buyer or supporting research question; its wording does not establish your inventory, services or search demand
  • “What's a good used SUV under $25,000 in Carleton Place, Ontario?”
    BEFORE THE DEALER VISITA saved buyer or supporting research question; its wording does not establish your inventory, services or search demand
  • “What's a good used SUV under $25,000 in Ottawa, Ontario?”
    BEFORE THE DEALER VISITA saved buyer or supporting research question; its wording does not establish your inventory, services or search demand
WHO THE ENGINES CITED INSTEAD · SAMPLE

2 other dealerships got cited in these answers. Sample dealership got cited zero times.

Every name below is a source an AI engine cited in the 4 answers we ran for you. Click any one of them to open the citation.

example-motors.example
example-motors.example
cited in 3 of 4 answers
maple-ridge.example
maple-ridge.example
cited in 1 of 4 answers
their own website was citednamed in Google’s answer panel
Sample dealership was cited in 0 of 4 answers, but named in 1 answer, with no link back.
WHERE THE CITATIONS SEND SHOPPERS · SAMPLE

4 citations across those 4 answers. None send the shopper to you.

Every source an AI answer cites is a door the shopper can walk through. Here's where each of those 4 doors actually leads:

4
0land on your site0land on aggregators (AutoTrader, CarGurus…)4land somewhere else (competitors, media)
THE TEST EVERY SHOPPER RUNS NOW · SAMPLE

We asked Gemini what buyers ask every day

“Where should I buy a used car in Carleton Place, Ontario?”
GEMINI · SAMPLE ANSWER
In this fictional example, Maple Ridge Auto is named as a used-car dealership in Carleton Place. Its documented buying process is linked as a source. This is an illustration, not a real recommendation.
maple-ridge.example
ENGINE BY ENGINE
Gemini
Mentioned you · 1 of 4
THE FULL TEST: EVERY QUERY, EVERY ENGINE
BEFORE THE DEALER VISIT · A saved buyer or supporting research question; its wording does not establish your inventory, services or search demand
“Where should I buy a used car in Carleton Place, Ontario?”
GeminiCited
BEFORE THE DEALER VISIT · A saved buyer or supporting research question; its wording does not establish your inventory, services or search demand
“Where should I buy a used car in Ottawa, Ontario?”
GeminiAbsent
BEFORE THE DEALER VISIT · A saved buyer or supporting research question; its wording does not establish your inventory, services or search demand
“What's a good used SUV under $25,000 in Carleton Place, Ontario?”
GeminiAbsent
BEFORE THE DEALER VISIT · A saved buyer or supporting research question; its wording does not establish your inventory, services or search demand
“What's a good used SUV under $25,000 in Ottawa, Ontario?”
GeminiAbsent
Sample dealership was missing from 3 of 4 answers. Every answer you're not in is a shopper sent somewhere else.
THE QUESTIONS YOU’RE NOT ANSWERING · SAMPLE

Your stock earns 5 research questions. Your site answers 1.

Shoppers put these questions to AI assistants before they know a year, make or model to search for. Engines retrieve pages; a site with no page shaped like the question has nothing to be retrieved for. Every question below is earned by cars we read on your own site, and every “answered” links the page of yours that proves it.

  • “best used SUV under $20,000 near Ottawa”no page — needs a used-SUVs page
  • “best used sedan under $15,000 near Ottawa”no page — needs a used-sedans page
  • “used Honda near Ottawa: which models hold up?”no page — needs a used-Honda page
  • “good used cars under $15,000 near Ottawa”no page — needs an under-$15k page
  • “can I get a car loan with bad credit near Ottawa?”ANSWERED — YOUR PAGE ↗

These 5 are the tip: counted across every category, budget band and payment combination your feed actually covers, your stock qualifies you for 118 distinct research questions — a computed count of pages your inventory could back, not an estimate.

The fix

What we would do about it

THE FIX: HOW VIN INDEX WORKS

We make Sample dealership the answer, and the click lands on you.

Aggregators win those queries because they publish thousands of structured, machine-readable pages. So do we, for your inventory. Here's the same question the aggregator just took from you, answered by a page you own:

mapleridgeauto.vinindex.ai/answers
mapleridgeauto.vinindex.ai/answers
VIN INDEX ANSWER · mapleridgeauto.vinindex.ai
“Where should I buy a used car in Carleton Place, Ontario?”

Sample dealership has matching vehicles in your market, including a 2020 Honda Civic LX, each on its own page built for AI to read, quote, and route the shopper to you.

2020 Honda Civic LX
On your VIN Index page
YOUR LOT
The rest of your matching inventory
Every unit its own citable page
YOUR LOT
Every row is yours

PREVIEW: BUILT FROM YOUR REAL INVENTORY ONCE YOUR FEED IS CONNECTED

THE SYSTEM BEHIND IT

Not a one-time cleanup, but a system that keeps Sample dealership in the answers as your inventory, and the questions shoppers ask, keep changing.

TRACKwhat shoppers ask
OPTIMIZEevery VIN
BUILDthe answer pages
DISTRIBUTEfeeds + agent tools
MEASUREwho got cited
…and repeat.
1We track the real questions, and who gets named

You just saw the first turn: we ran 4 live queries on Sample dealership across the AI engines and watched whether you were named. Every gap becomes the next page we build: track, build, measure, build more, a loop that compounds your coverage.

CHATGPT · AI MODE · PERPLEXITY · GEMINI
2A page for every question they ask

For every question shoppers actually ask (“best used truck under $40k ”, “AWD SUV for winter”, “SUV that seats seven”, “financing with bad credit”), we build the page that answers it, stocked with your matching vehicles, real payment math, and eligibility rules. The generic searches no single listing can answer, answered by a page you own.

A PAGE PER SHOPPER QUESTION
3Every VIN published, not a sample

Your whole feed is rebuilt for AI: a fast page per vehicle that a crawler reads without running a line of JavaScript, carrying the full specs, market position, financing scenarios and an answer-first summary an engine can quote, refreshed within an hour of every inventory change.

EVERY VIN · ~1H FRESH
4We hand AI assistants a direct line to your inventory

Beyond pages, your live inventory is something AI assistants and shopping agents can query directly. When one goes looking for matching cars it checks your stock in real time and routes the shopper straight back to you, current and attributed to you.

A LIVE LINE TO YOUR STOCK
5We publish where shoppers already are

Syndication feeds push your vehicles into the ChatGPT, Microsoft Copilot and Google shopping tools on a rolling refresh, so you show up inside the assistants shoppers already use, not only when they happen to land on your site.

SYNDICATED · CHATGPT · COPILOT · GOOGLE
6Your lead, and the proof it's working

The shopper routes to your page and the lead lands in your inbox or CRM, never brokered, never shared with another dealer. And you get first-party proof: which engines named you, which agents pulled your inventory, which pages earned the visit.

FIRST-PARTY ATTRIBUTION
Fix this →Free to start, no card. You pick your plan at the last step.
Under the hood

Why it happens, and how to check us

WHY THIS HAPPENS

What shoppers see vs. what AI can read

Vehicle page as shoppers see it
SHOPPERS SEE THIS
<!doctype html>
<html lang="en">
  <head>
    <title>Inventory | Maple Ridge Auto</title>
    <meta name="viewport" content="width=device-width">
    <link rel="stylesheet" href="/static/app.4f1c.css">
  </head>
  <body>
    <noscript>You need to enable JavaScript to run this app.</noscript>

    <div id="cookie-banner">We use cookies. Accept all?</div>

    <header class="site-nav">
      <a href="/">Home</a> <a href="/inventory">Inventory</a>
      <a href="/financing">Financing</a> <a href="/about">About</a>
    </header>

    <!-- inventory renders here, client-side, after this point -->
    <div id="root"></div>

    <script src="/static/runtime.8a2.js"></script>
    <script src="/stati
AI READS THIS
STEP BY STEP

4 things standing between your inventory and AI answers

1Agentic capabilityAT RISK

There is no endpoint an assistant can query. An agent that wants to search your stock, pull a VIN, or check availability has no machine interface to call, only a webpage built for human eyes.

2llms.txt / discoveryAT RISK

No llms.txt or agent discovery files were found, so AI agents have no machine-readable map of your inventory. Your sitemap exists, which is how the detail pages get read at all, but the modern discovery layer is missing. This is the cheapest gap to fix.

3Page renderingNEEDS WORK

Your inventory browse page is JavaScript-rendered: a crawler that lands on it gets 12,800 characters of HTML with zero vehicles in it. But your individual vehicle pages return static HTML, so an AI that follows your sitemap can still read each car. The gap is discovery on the listing pages, not the detail pages.

4Content qualityNEEDS WORK

The vehicle copy we could read is mostly a stock spec dump repeated across listings. Assistants prefer specific, factual descriptions. This is the most improvable area, and the easiest to lift.

WHAT AN ASSISTANT CAN DO TODAY VS ON VIN INDEX
What an assistant can doYour siteVIN Index
Found
Search your inventory by criteria
Get a single vehicle by VIN
Real-time availability
Convert
Financing scenarios
Trade-in appraisal
Structured lead with attribution
Be discovered
Zero-setup discovery files
ChatGPT Shopping feed
Copilot / UCP feed
VIN Index adds every missing capability automatically.
DON'T TAKE OUR WORD FOR IT
C+
AI Readiness: C+ · 62/100
Your site grades C+. AI engines cited you in 1 of 4 answers.

Paste the prompt into ChatGPT, Claude, or Gemini and it will independently check the findings above against your live site.

For your website person

The six checks behind the grade, with the evidence for each. Hand this to whoever manages your website. Every finding is a provable fact about what an AI crawler received.

Agentic capability

Can AI do anything with your inventory?

Failing

There is no endpoint an assistant can query. An agent that wants to search your stock, pull a VIN, or check availability has no machine interface to call, only a webpage built for human eyes.

The fixVIN Index does this

VIN Index gives assistants a direct line to your stock, so one can search your inventory, pull a specific car and start a lead, not just read a page.

See the detail

What we checked

Whether an assistant has a machine interface to act, search your stock, pull a VIN, request financing, or submit a lead.

How we tested

We look for an agent endpoint (MCP / WebMCP) or structured action declarations exposed by your site.

What it means

Without one, an assistant can describe your cars but can’t do anything, so every buyer action dead-ends at a human form.

Agent endpoint (MCP / HTTP)
None detected
Inventory feed an agent can read
None detected
Per-VIN machine record
None detected
Real-time availability signal
None detected

llms.txt / discovery

Can AI discover you the modern way?

Failing

No llms.txt or agent discovery files were found, so AI agents have no machine-readable map of your inventory. Your sitemap exists, which is how the detail pages get read at all, but the modern discovery layer is missing. This is the cheapest gap to fix.

The fixVIN Index does this

VIN Index hands agents a map straight to every vehicle you have, so they find the whole lot rather than whatever they stumble onto.

See the detail

What we checked

Whether you publish the discovery files agents look for, llms.txt, an agent card, and a sitemap that actually lists your vehicle pages.

How we tested

We fetch /llms.txt and agent-discovery files, and walk your sitemap to see whether it enumerates individual VDP URLs.

What it means

These conventions are emerging with no proven citation lift yet, but a sitemap that lists every VDP is how index crawlers find your whole lot.

/llms.txt
Not found
/.well-known/mcp.json
Not found
sitemap.xml
Found
IndexNow key file
Not found

Page rendering

Can AI read your vehicle pages?

Needs work

Your inventory browse page is JavaScript-rendered: a crawler that lands on it gets 12,800 characters of HTML with zero vehicles in it. But your individual vehicle pages return static HTML, so an AI that follows your sitemap can still read each car. The gap is discovery on the listing pages, not the detail pages.

The fixVIN Index does this

VIN Index republishes every car as a page a crawler reads start to finish, without running a line of JavaScript.

See the detail

What we checked

Whether your vehicles are present in the raw HTML an AI crawler receives, and whether the named AI crawlers are allowed in.

How we tested

We fetch your page with no JavaScript (the way ChatGPT’s and Claude’s crawlers read), count the readable vehicles, and probe whether each engine’s crawler gets through.

What it means

If your cars only appear after JavaScript runs, most AI crawlers see an empty page and have nothing to cite when a buyer asks.

Bytes returned to ChatGPT’s crawler (browse)
12,800 chars of HTML
Vehicles readable on the browse page
None
Individual vehicle page (via sitemap)
Static HTML + schema
Browse-page content container
<div id="root"></div> (empty)

Content quality

Is your vehicle text worth citing?

Needs work

The vehicle copy we could read is mostly a stock spec dump repeated across listings. Assistants prefer specific, factual descriptions. This is the most improvable area, and the easiest to lift.

The fixVIN Index does this

VIN Index gives each listing the condition detail and market context an assistant can lift straight into an answer.

See the detail

What we checked

Whether your visible vehicle descriptions are fact-dense and self-contained enough for an engine to quote.

How we tested

We score the visible inventory text for specific, complete, citable detail, real specs and no mid-sentence truncation.

What it means

Thin or truncated descriptions give an engine nothing quotable, so it summarizes a competitor’s listing instead of yours.

Unique description per VIN
Low (templated)
Condition narrative
Not present
Market context (price vs median)
Not present
Photos with alt text
Present

Structured data

Can AI trust your vehicle facts?

Passing

Validated Vehicle data is present on your detail pages, with price and currency. Engines have something machine-readable to trust and cite, not just numbers painted on the screen.

See the detail

What we checked

Whether your pages carry machine-readable structured data (schema.org Vehicle and Offer) an engine can quote with confidence.

How we tested

We parse a real vehicle detail page for JSON-LD Vehicle/Offer markup, including price and currency.

What it means

Without structured data an engine can read your prose but can’t reliably extract price, mileage, or specs, so it hedges or skips you.

Vehicle (schema.org)
Found
Offer / price
Found
AutoDealer / Organization
Found
Valid JSON-LD blocks
3

Robots / crawler access

Is AI even allowed in?

Passing

Your robots.txt allows the AI crawlers that matter: ChatGPT, Claude, Perplexity, and Google. Nothing here is turning assistants away at the door.

See the detail

What we checked

Whether your robots.txt permits the crawlers that feed AI search (and doesn’t quietly wall them out).

How we tested

We read your robots.txt and check the rules that apply to AI and search engine user-agents.

What it means

A disallow here removes you from the indexes AI assistants pull from, no matter how good the rest of your site is.

Google’s search crawler (Googlebot)
Allowed (200)
ChatGPT’s training crawler (GPTBot)
Allowed (200)
Perplexity’s search crawler (PerplexityBot)
Allowed (200)
Claude’s training crawler (ClaudeBot)
Allowed (200)

Per-engine crawler probe (each bot’s real user-agent)

Search index crawlers

Build the indexes ChatGPT, Gemini and Copilot answer from. A block here is the serious one: it keeps you out of AI search.

ChatGPTGoogleBing

On-demand fetchers

Fetch your page when a shopper asks an assistant to “check this dealer.” A block breaks that.

ChatGPTClaude

Training crawlers

Crawl to train models. Blocking these only opts you out of free training; you stay citeable in search.

ChatGPTClaudePerplexity

Get your inventory in the answers. Start free.

The free plan gets every car listed and readable by AI, at no cost. No card, no call, live in about an hour.

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