Client Background: A leading luxury hotel chain with 45 properties across major U.S. metropolitan areas including New York, San Francisco, and Miami, managing over $2.8 billion in annual revenue. The chain specialized in business and premium leisure travel segments with average daily rates exceeding $350.

Challenge: The client struggled with dynamic pricing across multiple OTAs, losing approximately 18% potential revenue due to delayed competitor rate adjustments and seasonal demand fluctuations. Manual rate monitoring across 200+ booking platforms proved ineffective for real-time pricing decisions.

Solution: Hir Infotech implemented comprehensive hotel data scraping services covering Booking.com, Expedia, Hotels.com, and regional platforms. Our AI-powered system monitored competitor rates, availability patterns, and promotional strategies across all properties with 15-minute refresh intervals.

Results: Within 8 months, the client achieved 31% growth in revenue per available room, 38% boost in pricing optimization accuracy, and 28% faster response to competitor pricing changes. Automated intelligence reduced manual research efforts by 24% while improving market positioning significantly.

Client Testimonial: “Hir Infotech’s hotel data scraping transformed our pricing strategy completely. Real-time competitor intelligence helped us optimize rates across all properties, resulting in our highest RevPAR growth in five years.”