Overview
How visible we are in AI → what's wrong → what to do
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Visibility Healthi
Visibility Health

One score, 0–100. We start at 100 and subtract a penalty per factor — each is weight × shortfall — so the “What's lowering it” list adds up exactly to this number.

100 − core-invisibility×35 − low-SoV×15 − weak-rank×20 − engine-gaps×20 − OTA-destination×10. Targets: full core visibility · 50%+ SoV · rank ≤#3 · all engines · ≤20% OTA.

/ 100

What's lowering it

Share of Voice · monthlyi
Share of Voice / € at risk

SoV — of all hotel recommendations across your query set, the share that is you vs competitors.

€ at risk — a discovery-funnel estimate with two non-overlapping channels: lost bookings (cold AI shortlists where you're absent — the guest never learns you exist) + OTA commission on bookings the AI does send, via its measured booking path. Full math: Settings → How Visibility Works.

Core visibility
Avg rank when shown
lower is better
Engine coverage
Not shown
Top actionsranked by impact — what to fix firstView activity →

Visibility over time

Core-query visibility · rolling avg

Who outranks you

Top competitors by appearances
Appears instead of youAppears alongside

Visibility by engine

% of checks where a hotel is shown

AI citations & destination

What AI cites vs where it sends the guest
What AI cites
Where AI sendsi
Where AI sends

Direct = the hotel's own site · OTA = Booking / Expedia / etc. · Other = something that isn't your site or an OTA (Google Search/Travel grounding, reviews, DMO). A Google-Maps hotel card counts as direct — its website button is the official site.

Hotels

Top 10 by impact · click a row for detail
View Hotels →
HotelShown %ChecksCore visAvg rankSoVBest / worst30-dayTop competitorStatus
Best engine
Weakest engine
Engine coverage
engines where shown
Biggest gap
best vs weakest

Engines

Click an engine for detail

Visibility by engine × theme

Where you're invisible — % of checks shown
Active competitors
appearing in your queries
We lead vs
of top rivals — higher SoV than them
Top rival
most frequent
Push you out
rivals recommended where you're absent

Competitors

Who shows up in your queries
CompetitorAppearsModeInsteadEnginesSoV taken
Core visibility
high-intent queries
Competitive
broader plausible
Baseline
generic top-of-funnel
High-intent lost
core checks you missed

Coverage funnel

Visibility by query tier — the 70 / 20 / 10 mix

Queries

Click a query for per-engine detail
Markets monitored
countries of search
Best market
Weakest market
Biggest geo gap
best vs weakest

Markets

Click a market for detail

Hotels

Click a hotel for detail & value at risk
HotelShown %CoreRankSoVBestStatus

Activity

Recent notable checks — confirmed change-detection lights up as history accrues

What lights up here

event types that fire once ~2 weeks of history accrue
Note
Right now this feed lists notable RAW checks — not visible / ranked low / sent to an OTA — so you can watch what the cadence finds day by day. Confirmed change-detection (dropped / reappeared / overtaken, verified over consecutive checks and deduped) replaces it once ~2 weeks of history accrue; push delivery (email / Telegram) is a later step.
Profile

Your name as it appears across the dashboard.

Password

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Team

People with access to this account. Owners can edit; viewers are read-only.

What “how visible you are in AI” actually measures

When a traveller asks an AI assistant for a hotel — “best spa hotel in Riga”, “family hotel near the Old Town” — that answer is the new shortlist. This page shows exactly how every number on the dashboard is built, so each figure is defensible to a revenue manager. We query the engines the way a fresh prospect in your market would: neutral context, no personalisation, incognito / temporary sessions — so the result is what a real guest sees, not your own history.

Visibility Health — one score, 0–100

Start at 100 and subtract a penalty per factor — each is weight × shortfall (shortfall 0 = at target, 1 = worst). So the “What’s lowering it” panel on Overview adds up exactly to this score.

100 − core-invisibility×35 − low-SoV×15 − weak-rank×20 − engine-gaps×20 − OTA-destination×10

Targets

100% core visibility · 50%+ Share of Voice · average rank ≤ #3 · all 4 engines · ≤ 20% of answers sending the guest to an OTA. Weights and targets get calibrated on real data.

Share of Voice & the engines

Share of Voice — of all the hotel recommendations the AI makes across your query set, the share that is you vs every competitor it names.

We track four engines — ChatGPT, Gemini, Perplexity, Claude — and weight the money model by where discovery actually happens (ChatGPT 60 / Gemini 25 / Perplexity 10 / Claude 5). Queries split into three tiers, roughly 70 / 20 / 10: core (high-intent, you should win), competitive (broader, plausible), baseline (generic top-of-funnel).

How “€ at risk” works

A discovery-funnel model — an order-of-magnitude estimate, not an invoice. Two loss channels that never overlap:

A · Lost bookings — you’re absent

Bookings (rooms × occupancy × 30 ÷ 2-night stay) × 75% booked online × 10% with an AI assistant in the discovery path × 30–45% a cold shortlist — where the AI answer is the consideration set. Inside a cold shortlist, absence = the whole booking lost: the guest never learns you exist. Depth matters — top-3 counts as fully seen, #4–6 half, #7+ a quarter. That engine-weighted shortfall is your exposure gap, priced at ADR × 2 nights.

B · OTA commission — on kept bookings

The visible share of the same pool: the booking happens, but when the engine’s measured click-destination is an OTA and the guest follows it (40–60%), you pay the ~16% commission.

Worked example — a sample hotel
150 rooms
× 70% occupancy
× 30 days
÷ 2-night average stay
1,575 bookings / month
1,575 bookings
× 75% booked online
× 10% via an AI assistant
× 30–45% cold shortlist
35–53 AI-decided bookings
Exposure gap ~60%
35–53 × 60%
21–32 lost bookings
ADR €100
× 2 nights
€200 per booking
21–32 lost bookings × €200
+ the OTA-commission channel
€4.2k – €6.4k lost / month

A flat “every AI-touched booking is lost” would claim ≈ 3× more — that’s why the cold-shortlist share sits in the funnel. The live tile shows each hotel’s real figure on its current window.

Citations, destination & recommendations

Citations vs destination. We record both what the AI cites (TripAdvisor / OTA / your own site / DMO) and where it sends the guest (direct vs OTA), per engine — measured from our own timestamped screenshots.

Evidence-graded fixes. Every recommendation is tagged proven / likely / marginal — we never ship debunked tactics. AI ranking and phrasing stay outside anyone’s control; we improve your odds of being cited, not guarantee a position.

Every assumption is a calibration knob: the 10% AI-discovery share is reviewed semi-annually (it will grow); rooms/ADR estimates refresh quarterly via the LLM pass. Your manual overrides in each hotel panel always win and are never auto-touched — and per-hotel figures always reconcile to the portfolio headline.