The AI platform Retail Motor Vehicles use to get recommended on
Buyers ask an AI where to buy, what it should cost and who to trust, before they visit a lot or a website. LBOX measures what the engines say about your store, finds where a listing site is answering in your place, and builds the evidence that changes it.
Measured across
Perplexity
Gemini
Google AI
Claude
Copilot
Meta
DeepSeekGrok... and moreEvery one of them is competing for the same answer. One name comes back when a buyer asks.
What makes Retail Motor Vehicles different
Not general marketing advice. These are the constraints your category actually operates under.
Your inventory changes daily. The answer does not.
Engines quote stock, trim and price from listing feeds and cached pages that lag by days or weeks. A buyer is told you have a vehicle you sold on Tuesday, or quoted a price you no longer honour, and you find out when they arrive.
Listing sites outrank the store that holds the car.
Cars.com, Autotrader, CarGurus and KBB are what the engines cite when someone asks where to buy. You pay those platforms for leads on your own inventory, and now they also own the sentence that describes you.
You are one of several stores selling the identical vehicle.
Inside a franchise footprint the product is not the differentiator, the store is. Which store an engine names is decided by review counts, directory data and local pages, not by who has the better deal.
Financing and trade-in questions get answered without you.
Rate, term, trade value and availability are the questions that used to bring someone in to talk. They are now answered upstream, and whoever the engine names is the store that gets the visit.
What you get back
The console, measuring a company in Retail Motor Vehicles against the questions its buyers ask. Every brand named, every domain cited, every engine separately.
A worked example on an illustrative company, shown to display the console. Your own numbers come from measuring your questions through the engines’ own APIs.
See which store the engines send buyers to
Visibility and position on the unbranded buying questions shoppers ask in your market, measured per engine.
- Ranked against the stores the engines actually named
- See where a model reads your inventory without naming you
You against the field, engine by engine
unbranded questions| Brand | Gemini | AI Overviews | OpenAI | Perplexity | Claude | ChatGPT |
|---|---|---|---|---|---|---|
| Rivermont Auto Group | 30% | 27% | 25% | 22% | 13% | 28% |
| Halloway Motors | 24% | 21% | 19% | 17% | 11% | 22% |
| Kestrel Motorsyou | 19% | 11% | 16% | 13% | 7% | 1% |
| Brookvale Autos | 13% | 10% | 9% | 11% | 5% | 10% |
Turn what the answers get wrong into work that ships
Findings arrive as a worklist sorted by who can act: what LBOX writes, what needs your decision, what needs your feed provider.
- Scored against your market, not a generic SEO checklist
- Nothing publishes without your sign off
The worklist
Prove the change, month after month
Every measurement is stored, so the line lengthens each cycle and the movement is on the record rather than asserted.
- The same questions, asked again and checked
- Sources broken out per model, per page
Visibility over time
every measured runKnow when the models come to read your inventory
Crawler activity captured at the edge, so you can see which models fetch your listing and store pages, and how often they return.
- Every model, every page, logged over time
- Robots and content signals kept current
Crawler activity
hits by model, last 30 daysWhere you disappear as the buyer gets closer to the lot
Presence falls away as intent rises. The where-should-I-buy questions are the ones that convert, and the ones listing sites win.
- Visibility split by where the question sits in the journey
- Names the stage that costs you the visit
Visibility by buying stage
where you show up in the journeyThe sources the engines trust when someone is buying a car
Listing sites, valuation tools and review platforms decide what the engines repeat about your store. You pay several of them for leads already.
- Owned versus earned, so you know what to build and what to earn
- Every citation traced to the answer it supported
Which domains the engines cite
584 citationsThe program for Retail Motor Vehicles
Everything below is included. Measured through the engines’ own APIs, so the same questions can be asked again and the result checked.
- Measure what every major AI engine says about your store today, through the engines own APIs
- The buying questions shoppers actually ask, mapped by model, condition, finance and location
- Where a listing site or directory is answering in your place
- Whether the engines describe your inventory, hours and location correctly
- Which sources the engines cite for your market, and which of those you control
- Inventory and store pages built so the engines read them accurately and currently
- Re-measurement on the same questions, so the change is provable rather than asserted
What this does not show: what any individual user saw. LBOX measures what the engines answer through their own APIs, which is repeatable and checkable. It is not a record of any one person’s session, and it does not predict revenue.