Intro (above the fold)
AI visibility is not owned by one role.
A hotel CMO cares about brand framing and citation share. A revenue manager cares about OTA capture and demand routing. An owner or GM cares about reputation, accuracy and direct bookings. An asset manager cares about portfolio risk and reporting cadence.
Same data, four different reading angles. Four different decisions.
This hub gathers the four stakeholder-specific pages of Capston Core. Each page is written for one role, with the prompts, score dimensions, escalations and sign-off lines that matter for that role. Use this hub to route the right page to the right stakeholder.
Run a baselineView the hospitality scorecard
Why stakeholder framing matters
Most AI visibility reports are written for a generic reader. That is part of why they get filed and forgotten.
A board does not care which model named which competitor on which date. An owner does not care about citation share if the brand fact is wrong. A revenue manager does not care about sentiment if OTA capture is bleeding direct demand.
Stakeholder framing fixes three problems:
- Ownership. Each finding is assigned to the role that can decide on it.
- Escalation. When something needs to move up, the path is already drawn.
- Sign-off. When something is done, the right person signs off.
Capston Core treats the four hotel commercial stakeholders as first-class readers of the score. The methodology is shared. The views are not.
Four roles around the commercial table
The same baseline, read four ways.
Hotel CMOs
The CMO owns brand framing, demand generation and partner positioning. AI visibility lands on this desk first: which prompts surface the brand, which competitors are named ahead, which descriptors AI engines reuse, and which experiences are being missed entirely.
The CMO view focuses on citation share, answer position, sentiment, descriptor accuracy and the gap between brand intent and AI summary.
→ Read the dedicated page: AI visibility for hotel CMOs.
Revenue Managers
The revenue manager owns rate, mix, channel and demand routing. The questions that matter here are different: are AI answers sending demand to OTAs, to aggregators, to comparison sites, or to the brand’s own booking path? Which prompts produce a direct citation versus an intermediary citation?
The revenue manager view focuses on OTA capture risk, channel substitution, market-by-market variance and the commercial cost of being missing on conversion prompts.
→ Read the dedicated page: AI visibility for revenue managers.
Owners and GMs
The owner or GM owns the property’s reputation, the guest experience promise and the local relationships that protect them. AI answers can describe the hotel inaccurately, miss a renovation, repeat an old controversy or quietly favour a neighbour.
The owner and GM view focuses on factual accuracy, experience visibility, review-driven sentiment and the local sources AI engines are reusing about the property.
→ Read the dedicated page: AI visibility for hotel owners and GMs.
Asset Managers
The asset manager owns portfolio value, performance variance across properties and the reporting that flows up to investors. AI visibility becomes a portfolio signal: which properties are losing share of AI answers, which are exposed to OTA capture, which need brand or content investment.
The asset manager view focuses on cross-property comparison, score variance, commercial risk concentration and a quarterly cadence that fits the asset reporting calendar.
→ Read the dedicated page: AI visibility for asset managers.
How to sequence stakeholder engagement in a Capston Core program
A common mistake is to open the conversation with every stakeholder at once. The findings overlap, the language drifts, and no one signs off.
The sequence that works:
- Start with the CMO. They own brand framing and are usually the first to feel AI visibility as a category. They can authorise the baseline.
- Bring in the revenue manager early. The OTA capture and channel substitution findings need their sign-off and their distribution context.
- Loop in owners and GMs property by property. Factual accuracy and experience visibility are personal at the property level. The conversation has to happen one property at a time.
- Close the loop with the asset manager. Once the property-level work is moving, the portfolio view becomes the reporting backbone for the board.
Each stakeholder page mirrors this sequence. The hub gives the map. The pages give the conversation script.
How this fits into Capston Core
Stakeholders is one of the three navigation hubs inside Capston Core, alongside research and playbooks.
- Research explains the method.
- Playbooks explains the operations.
- Stakeholders explains who decides what.
All three rely on the same backbone: the AI visibility scoring system, the AI answer evidence layer, the Capston Core methodology and the Capston QA standards.
→ Back to Capston Core.
FAQ
Why split AI visibility by stakeholder instead of one shared report?
Because decision rights are split. A CMO cannot sign off on OTA channel mix. A revenue manager cannot sign off on brand framing. A single report forces everyone to read material they do not own. Stakeholder views route the right findings to the role that can act.
Which stakeholder should commission the first baseline?
Usually the CMO. They own brand framing and are typically the first to feel AI visibility as a strategic category. The revenue manager and asset manager often join at the readout, once findings are concrete.
Do the four pages share the same data?
Yes. The underlying baseline, prompt set, competitor set and evidence layer are shared. Only the reading lens, the priority dimensions and the escalation paths change per role.
Final CTA block
Route AI visibility to the right stakeholder.
Pick the page that matches the role on the call. Use the same baseline. Run the conversation with the language and the decisions that role actually owns.
Run a baseline
View the hospitality scorecard