The AI platform Airlines and Aviation use to get recommended on
Travellers ask a model where to fly, what the bag costs and whether you are reliable, and the answer is assembled from aggregators and complaint threads. LBOX measures what the engines say about you, finds who 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 Airlines and Aviation different
Not general marketing advice. These are the constraints your category actually operates under.
Aggregators answer the booking question and take the margin.
Ask how to get from one city to another and the engines surface Google Flights, Expedia and Skyscanner. Those channels already cost you a distribution fee, and they are now also the source that decides whether your own booking page is mentioned at all.
Fare rules change faster than any answer.
Bag allowance, change fees, seat selection, carry-on sizing. These move by route and by fare class, and an engine quoting last season policy creates a dispute at the gate that your staff has to absorb.
One disruption week defines the summary.
Ask whether an airline is reliable and a model reads delay statistics and complaint threads. A bad fortnight in a storm season becomes the standing description of your operation long after the operation recovered.
Route and schedule answers go stale and quietly cost bookings.
Engines read third-party timetables. A route you added is invisible and a route you dropped is still being recommended, and the traveller never learns which of those happened.
Every answer that books direct keeps the fee you would have paid someone else
Most industries measure AI visibility as incremental demand. In aviation the bigger prize is channel. A seat sold through an aggregator carries a distribution cost that a seat sold on your own site does not, and that difference repeats on every ticket, every day, across every route. An answer that names you and links you rather than sending the traveller to a comparison site is not just a booking won, it is a margin recovered on a booking you would probably have got anyway.
What you get back
The console, measuring a company in Airlines and Aviation 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 airlines the engines name
Visibility and position on the unbranded who-should-I-fly-with questions your travellers ask, measured per engine.
- Ranked against the airlines the engines actually named
- See where a model reads your pages without naming you
You against the field, engine by engine
unbranded questionsTurn 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 revenue or operations team.
- Scored against your routes and fare types, not a generic SEO checklist
- Nothing publishes without your sign off
The worklist
Where you disappear as the traveller gets closer to booking
Presence falls away as intent rises. The how-do-I-book questions are the ones that convert, and the ones the aggregators win.
- Visibility split by where the question sits in the journey
- Names the stage that costs you the booking
Visibility by buying stage
where you show up in the journeyThe sources the engines trust about airlines
Aggregators and review platforms decide what the engines repeat about your reliability and your fares. Several of them also charge you for the booking.
- 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
693 citationsThe program for Airlines and Aviation
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 airline today, through the engines own APIs
- The traveller questions you are actually asked, mapped by route, fare type and disruption
- Where an aggregator or review platform is answering in your place
- Whether the engines state your routes, baggage rules and change policies correctly
- Which sources the engines cite for your routes, and which of those you control
- Route, fare and policy pages built so the engines can read and quote them accurately
- 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.