Find Your AI Revenue Gap

One traveller loves the experience. The next asks AI, and gets your competitor.

Find out exactly where that is happening to you.

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Prathish Cherian, Founder GMK
“Cited gave us a baseline, the evidence gaps behind it.”
Prathish Cherian · Founder, GMK
What your guest said last week
The family pool was incredible. Kids club staff knew our children names by day two. Best family holiday we have ever had.
TripAdvisor
+846 similar reviews this year
What a family asked AI this morning
Best family resort in Dubai?
1 Competitor A
2 Competitor B
– Your property: not in this answer
Two conversations. Zero connection. Cited finds the gap between them.
The market shift

Your website tells one version of the story. Your customers tell thousands.

Travel brands have spent years optimising what they say. Routes. Rooms. Destinations. Service promises.

Every stay, flight, cruise, tour and booking produces evidence after the experience. Reviews. Advocacy. Complaints. Independent proof. As AI becomes part of travel discovery, that wider evidence environment can increasingly influence how brands are understood and recommended.

Word of mouth is becoming machine readable.

When they do not align, AI notices
Brand says
Customers say
AI says
“Best in class customer service.”
“Great crew, but baggage handling was poor and refunds slow.”
“Strong onboard service. Mixed reliability feedback.”
BRAND CLAIM  ≠  CUSTOMER EXPERIENCE  ≠  AI PERCEPTION
Google, TripAdvisor, Booking, airline review sites
Reddit, travel forums, social advocacy, creator content
Awards, associations, editorial media, partner citations

Every team sees a signal. Nobody sees the whole story. That is the problem.

What a Recommendation Gap looks like

The evidence exists. AI is not associating it with you.

Traveller asks AI
“Best family resort in Dubai?”
UK families. High intent. Planning summer holiday.
AI recommends
Competitor A and Competitor B are recommended. Your resort is not mentioned.
Your guests mention family experience in 847 reviews. Competitor A has 312.
The Recommendation Gap
Strong family evidence. Weak AI recommendation association.
Cited investigates why. Strengthens the evidence. Reruns the same journey.
If the agreed recommendation shows no measurable movement at the 90 day rerun, Cited continues at no additional professional fee.
See your gap · free
How Cited is different

AI visibility tells you where you appear. Cited explains why you get recommended.

AI visibility tools
Track mentions
Measure visibility
Monitor competitors
Report movement
They tell you the score. Not why you are losing.
Cited
Analyse recommendation
Trace the evidence
Explain why competitors win
Strengthen evidence. Rerun. Measure.
We strengthen the existing evidence. Then measure whether recommendation moves.
The Cited thesis

Word of mouth is becoming machine readable.

Travel has always run on word of mouth. AI changes the scale at which that word of mouth can participate in discovery. What your customers say after a flight, stay, tour or booking is increasingly relevant to what AI says before the next traveller chooses.

Travel is unusually suited to this. The product is experienced before it can be fully described. Rooms, flights, cruises, tours, meals, transfers. Millions of those experiences produce public evidence, historically scattered across review platforms, editorial sites, directories, social and forums.

The Cited hypothesis: as conversational AI takes a larger role in travel discovery, that distributed reputation becomes increasingly relevant to the recommendation layer. The travel brands that understand this will compound recommendation share while others optimise yesterday’s channels.

How Cited works

Define. Baseline. Trace. Strengthen. Rerun.

Five steps. One defined buying situation at a time. Analyst led and never automated.

01
Define
Agree the specific buying situation: the recommendation to compete for, the traveller type and the competitor set.
02
Baseline
Establish where the brand stands today across five AI channels. Document current AI recommendation gaps and associated evidence.
03
Trace
Identify the customer, market and authority evidence driving AI recommendation gaps.
04
Strengthen
Improve genuine customer, brand and authority evidence where legitimate gaps exist.
05
Rerun
Run the same defined journeys again and measure what changed against the baseline.
For every part of the travel decision

Where to stay. How to get there.
What to do. Who helps plan.

What happens inside a Cited Sprint

An analyst document. Not a dashboard.

Every Sprint produces a documented baseline, executed evidence work, and a rerun against the same buyer journeys. Here is what that looks like.

Cited Sprint document
Analyst-delivered · Confidential
Buyer journey Baseline position Evidence finding Action 90-day rerun
Best family resort Dubai Absent across 5 channels 847 family reviews. Not structured for family queries Evidence activation + profile updates Present: 3 of 5 channels
Best luxury spa hotel UAE Present: 2 of 5 channels Strong spa evidence. Wellness association weak Wellness hub page + editorial outreach Present: 4 of 5 channels
Best business hotel Dubai DIFC Present: 3 of 5 channels Present on 3 channels. Meeting room evidence thin Meeting facilities content + review activation In progress
184 prompts tested · 27 evidence gaps identified · 11 interventions · 90 day rerun
See Sprint pricing
From completed engagements

The gap found. The gap closed.

Three properties. What guests were saying. What AI was missing. What changed at 90 days.

Hotel Group UAE
Family travel evidence not reaching AI recommendation.
Baseline
Absent from family travel queries across all 5 AI channels
Gap found
847 family guest reviews. Not structured for family queries
Action
Evidence activation, profile updates, structured content
90-day rerun
Present on 3 of 5 AI channels for family queries
Tour Operator UK
Japan specialist expertise invisible to AI recommendation.
Baseline
Absent from Japan specialist queries on all 5 channels
Gap found
15 years of specialist expertise. No indexed destination content
Action
Destination authority pages, editorial placements, profiles
90-day rerun
Appeared on 4 of 5 channels for Japan specialist queries
TMC UK
Strong service record absent from AI procurement shortlists.
Baseline
Absent from mid-market TMC queries on all tested channels
Gap found
92% client renewal. Zero public case studies or references
Action
3 case studies published, GBTA profile expanded, trade press
90-day rerun
Shortlisted on 2 of 3 target buyer journey territories
Cited Research

Building the evidence base for a new category.

Cited publishes research on how traveller experience, word of mouth and public evidence influence AI recommendation. All research is transparent about what is published, in fieldwork or planned.

US Hotel AI Recommendation Report Public Teardowns
In Fieldwork
US Hotel AI Recommendation Report 2026
Planned Q4 2026
Public Teardowns
Methodology
How Cited measures
How to start

Start by seeing where you're invisible.

Before any engagement, Cited surfaces one specific AI recommendation you're losing — and roughly what it's costing you in bookings. That's your starting point.

Step 1
AI Revenue Gap
One specific finding. What AI says when someone searches for you. What it's costing you. Free.
Step 2
AI Recommendation Report
Full gap analysis across five AI channels. Evidence gaps ranked by revenue impact. Actionable, not theoretical.
Step 3
Recommendation Sprint
We close the gap. Strengthen the evidence. Rerun the same AI journeys and measure what moved.
Find my AI Revenue Gap · free See engagement pricing

One traveller loves the experience.
The next asks AI, and gets your competitor.

Word of mouth is becoming machine readable.

Get a free gap check to see where the signal is breaking down, or a full AI Recommendation Report to see exactly what it is costing you.

Find my AI Revenue Gap · free See the full report
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