AI Platform to Reconcile Guest Data Across a Luxury Hotel Chain's Channels

A luxury hotel chain has data that conflicts from one part of the business to another. Using AI, what platform would you build to resolve those discrepancies and improve the guest experience across channels? ```hint Follow one returning guest Trace a single repeat guest from booking, through a phone call, to arrival at a different property, and note every point where one system knows something the next one does not. ``` ### Clarifying Questions - Which discrepancies hurt most today: duplicate or conflicting guest profiles, reservations and rates that differ between channels, or loyalty records that disagree? - Which channels are in scope: the brand website and app, the reservation call center, front desk and concierge, messaging, and bookings made through online travel agencies? - Do individual properties run their own systems, and does the chain have the authority to change them? - Is the platform for staff, for guests directly, or both? ### What a Strong Answer Covers - A diagnosis of where the data conflicts come from and which ones damage a luxury guest's experience most. - The people the platform serves, guests and the staff roles who serve them, and the cross-channel moments that matter. - A platform design that shows how data is unified, where AI is used for matching, reconciliation and personalization, and where people stay in the loop. - An MVP and later phases, with success metrics and guardrails. - Risks such as wrongly merged guest records, privacy and consent, and staff adoption. ### Follow-up Questions - The platform merges two different guests who share a name, and one is greeted with the other's preferences. How do you prevent this, and how do you recover when it happens? - A property's general manager refuses to give up a local system that staff like. How do you get adoption? - How would you show the chain's leadership that the platform is paying off within its first year?