Case Study · Predictive Analytics
How AI Turns a 10-Room Lakefront Resort into a Revenue Engine
A direct-booking website with six AI/ML modules: a 24/7 bilingual concierge, dynamic pricing, personalisation, pre-arrival upselling, review intelligence and demand forecasting.
The client
The client is a 10-room luxury lakefront retreat close to a national park. Most guests book from abroad, mainly from Europe, and pay in several currencies. They expect the service of an international hotel brand, delivered by a small local team.
The challenge
- OTA dependency: most bookings came through online travel agencies taking 15–25% commission, and the agencies kept the guest relationship.
- Time-zone gap: European guests enquire in their evening, which is late night at the resort, so enquiries went unanswered for hours.
- Static pricing: rates changed a few times a year, without reflecting park seasons, school holidays, festivals or competitor prices.
- Missed ancillary revenue: safaris, jetty dinners and spa treatments were sold on arrival, if at all.
- No time for marketing: reviews, bilingual content and social media competed for the same few staff hours.
The solution: six AI modules
AI Concierge
A 24/7 bilingual assistant on the website and WhatsApp. It uses retrieval-augmented generation (RAG) over the resort's content, checks live availability, quotes in the guest's currency and hands over to staff when needed.
Dynamic pricing
Gradient-boosted demand forecasting that recommends nightly rates and minimum stays, based on booking pace, park seasons, European school holidays, local festivals and competitor rates. The owner approves prices in one click, within set limits.
Personalised booking website
Language, currency and offers tailored to each visitor, room recommendations ranked by likelihood to book, and abandoned-booking recovery.
Pre-arrival upsell engine
Propensity scoring predicts which experiences each guest is most likely to buy and offers them before arrival.
Reputation intelligence
Multilingual sentiment analysis across TripAdvisor, Google and Booking.com, with drafted replies for staff to approve.
Demand forecasting
Restaurant, staffing and content forecasts that reduce food waste and plan shifts, plus an AI content studio for bilingual SEO copy.
People stay in control
Every AI decision that affects price, guests or public content can be reviewed by a person. The owner stays in control, and the system does the repetitive work.
Projected impact after 12 months
Modelled on the resort's size and market, using hospitality industry benchmarks.
Technology
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