+60% Increase in revenue
+75% Increase in bookings
-35%Reduction in manual intervention
About The Client
The client, a leading hotel, wanted to move away from manual, reactive pricing and toward a dynamic pricing system that automatically pushed optimized rates to Online Travel Agencies (OTAs) and its own booking engine, driven by market trends, seasonality, demand, and competitor analysis. BigOhTech designed, built, and launched the system end to end. The Challenge
The client was losing revenue and competitive positioning to manual, slow-moving pricing in a market that changes by the day:
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Our Approach
A market-responsive pricing algorithm BigOhTech built a machine learning model that analyzes market trends, seasonal patterns, and competitor rates, then recommends price adjustments so the hotel's rates track real market conditions instead of lagging behind them.
OTA automation via channel managers The system integrates directly with the hotel's channel managers, pushing updated rates to every connected OTA automatically, removing the manual, one-by-one rate updates that were the direct cause of the 35% intervention overhead the client was carrying before.
Real-time market monitoring A dedicated data layer continuously tracks market movement, competitor rates, and seasonal demand shifts, so the pricing model is always working from current conditions rather than a stale snapshot.
A rules engine for strategic control Rather than a black-box algorithm, the hotel got a configurable rules engine, letting them set boundaries and business-specific logic so automated pricing stayed aligned with their own strategy, not just the model's raw output.
CASE STUDY AI/ML
AI-powered Sentiment Analysis for a Luxury Hotel Chain
How BigOhTech helped an 11-property, 5-star hotel chain centralize scattered guest feedback into one AI-driven dashboard, turning previously unactionable reviews into a 12% RevPAR increase and measurable gains in guest loyalty.
The Impact
60% increase in revenue, driven by prices that tracked demand and competitor movement instead of lagging behind it.
75% increase in bookings, consistent with a pricing strategy that stayed competitive in real time rather than periodically.
35% reduction in manual intervention, freeing the revenue team from manually updating rates across every connected OTA.
Faster response to market shifts than manual pricing allowed, strengthening the hotel's competitive position during high-demand periods.
