The Challenge: Flying Blind in a Hyper-Competitive Market
“Celestial Resorts” was the owner of 200+ luxury hotels in 40 countries worldwide, yet their market intelligence system was in the stone age. They managed a beautiful hotel chain, but their competition was entering their lunch with data intelligence.
♦ The secret extension of a competitor into their most fervent markets, which was uncovered after the signing of leases
♦ Changing traveler demand to bleisure – observed once occupancy fell 23%
♦ Emerging distribution channels that are going to takeover -achieved a loss of bookings since it realized a loss of $47M in direct bookings.
This would lead them to their breaking point as three huge market shifts caught them by surprise:
Their quarterly reports were not intelligence at all but autopsies. Competitive analysis equated to employing consultants that presented PowerPoints concerning yesterdays news. Market forecasting? Wishful thinking and an educated guess from last year.
The challenge of the CEO: I must understand what is going on in our market before the competitors. And I want to know about the future, not what the past is.”
The Approach: Building an AI-Powered Market Intelligence Command Center
We implemented our end-to-end AI platform so that it can transform Celestial, a follower in the market into a predictor.
Phase 1: Industry Research Deep Dive
Doing research in the whole, industry our AI system conducted a deep analysis of the industry:
♦ An examination of 73 rival chains in all market segments
♦ Monitoring of 450+ autonomous luxury properties
♦ Observe the influence of alternative places to stay (Airbnb, vacation rentals)
♦ Examination of 15 years of information in the industry in order to perceive cycles and trends
♦ Have a closer look at the new concepts in the hospitality sphere and assess their feasibility
♦ Observation of changes related to the demographics of travelers and the development of preference changes
The system was not only about data collection, but it could understand relations. ♦It discovered that as technology conferences were relocated to different cities, eight months later, there was an increase in bookings of smaller hotels (technology people returning to play). According to a report on a hotel marketing website, Instagram posts concerning the lobbies of hotels proved to better predict occupancy rates than other conventional marketing measures.
Phase 2: Ongoing Market and Competitive Intelligence
Static reports became living intelligence. Our AI monitored in real-time:
♦ Pricing strategies of competitors in every channel
♦ New property developments and new expansion plans (permits to job postings)
♦ Sale of partnership and distribution agreements
♦ Domestication of marketing campaigns and success
♦ The mood of the customers changes in favor of other brands
♦ Up-and-coming travel patterns prior to going mainstream
♦ Factors influencing economic indicators of travel trends
Signals that other people did not notice were detected by the intelligence system. Our AI forecast property sales when a competitor’s CFO used the term, operating streamlining, on an earnings call. Both of the properties were premium, and Celestial purchased them without other parties realizing that they were in the market.
Phase 3: Scenario Planning for Multiple Futures
We built sophisticated models for different market scenarios:
♦ Economic recession impact on luxury travel
♦ Climate change effects on destination popularity
♦ Political instability influence on regional bookings
♦ Technology disruption (virtual travel, new booking platforms)
♦ Demographic shifts (Gen Z travel patterns versus Baby Boomers)
♦ Post-pandemic travel behavior evolution
Any situation was followed by the triggers that were to be observed, response strategies, and investment ideas. By the time inflation began creeping up, Celestial was fully equipped to accommodate with modified pricing policies and schemes of cost controls formulated months previous.
Phase 4: AI-Powered Forecasting
Our forecasting went beyond simple projections:
♦ Demand prediction by property, season, and segment (87% accuracy)
♦ Revenue forecasting 18 months out (within 4% variance)
♦ Market share evolution modeling
♦ Optimal timing for renovations and expansions
♦ Pricing optimization based on competitive dynamics
♦ New market entry viability scoring
The Solution: From Market Follower to Market Maker
The transformation was profound and profitable.
The Bangkok Breakthrough Our ongoing competitive intelligence detected unusual activity: three luxury competitors were quietly reducing Bangkok inventory for Q3. The AI correlated this with:
♦ A large festival that is shifted to other days
♦ Building that would occur around the airport
♦ Two new hotels are being constructed as business hotels.
Predictions: The demand would decline in luxury by 20 percent during that quarter.
Celestial response: Diverted the inventory to corporate long-term, teamed up with film productions requiring lodgings, developed workation deals. Outcome: 95% occupancy rate as compared to 60% by the competitors.
Industry study revealed a new trend: the number of wellness travel searches is growing 3 percent each month; however, only in particular demographics and areas. We had forecasted 18 months for this to go mainstream on our AI.
Celestial moved first:
♦ Converted underperforming spaces to wellness centers
♦ Partnered with health brands before prices spiked
♦ Trained staff while labor was available
♦ Marketed to early adopters
When wellness travel exploded, Celestial owned the category. Revenue from wellness packages: $73 million in year one.
The Distribution Channel Revolution. In our market intelligence, we have identified a bad trend of a new booking platform achieving tremendous market share in Asia. It was shrugged off as a local racket by the majority. Our AI disagreed; it found similar growth patterns with Airbnb in its early days.
The three probable futures were identified in scenario planning:
♦ Platform is still regional (25% chances)
♦ Platform grows internationally (60 percent probability)
♦ Bigger player buys the platform (15 per cent chance)
Celestial negotiated exclusive partnership terms while the platform was hungry for inventory. When it went global 14 months later, Celestial had preferred status worth $34 million annually in incremental bookings.
The Results: Intelligence-Driven Dominance
The numbers validate the transformation:
♦ Revenue increase: 34% over 18 months
♦ Market share gain: 4.7 points in luxury segment
♦ Forecasting accuracy: 87% (versus 41% previously)
♦ Competitive response time: 3 days (from 3 months)
♦ New opportunity identification: 23 initiatives launched successfully
♦ Failed initiatives: decreased 71% due to better prediction
♦ Strategic planning confidence: 91% (executive survey)
Positioning, however, was the true triumph. Celestial no longer responded, but anticipated. They never entered a market when it was saturated; they never left a segment until it was declining, and certainly did not put their properties where the demand existed but rather where it would be.
Advanced Implementation: The Network Effect
The intelligence system created unexpected benefits:
♦ Cross-Property Learning: When the AI identified successful strategies at one property, it immediately tested applicability elsewhere. A food concept that worked in Dubai was successfully replicated in 12 other locations within months.
♦ Supplier Intelligence: The system tracked supplier health and predicted potential disruptions. When it flagged financial distress at a major linen supplier, Celestial secured alternative sources before prices spiked 40%.
♦ Talent Market Forecasting: By analyzing job postings, LinkedIn activity, and industry movements, the AI predicted talent shortages. Celestial recruited aggressively before the labor crisis, saving millions in emergency staffing costs.
♦ Investment Optimization: The forecasting system didn’t just predict revenue—it optimized capital allocation. Instead of renovating based on age, properties were updated based on ROI predictions. Investment efficiency improved 43%.
Key Lessons Learned
✔️ Cross-Property Learning: The AI learned valuable strategies that worked well at one property, and applied them somewhere new instantly. An example is a food concept that was successful in Dubai but in a few months, copied in 12 other places.
✔️ Supplier intelligence, Supplier health, and disruption forecasting was tracked. Celestial was able to find alternative suppliers before prices increased by 40 percent when it had issued a warning of financial distress in one of its major linen suppliers.
✔️ LinkedIn was able to predict shortages of talent using job postings and industry movements, as well as LinkedIn activity. Celestial had done aggressive recruiting ahead of the labor crisis saving millions of dollars in emergency staffing.
✔️ Optimization of Investment. The forecasting system was not merely the forecast of revenue; it was the optimization of capitalization. Rather than renovating by age, properties were renovated by forecasting of ROI. The efficiency of investment increased by 43 percent.
Note: While this story is based on real strategies we’ve employed, specific client details have been tweaked to respect confidentiality.