Competitor Hotel Pricing Analysis on Expedia & Booking.com

Introduction

The hospitality sector has undergone a significant digital transformation. Online Travel Agencies (OTAs) like Expedia and Booking.com have become the primary channel for hotel bookings globally. As these platforms dominate the market, hotels are increasingly challenged to maintain competitive pricing while maximizing occupancy and revenue.

In this scenario, Competitor Hotel Pricing Analysis becomes crucial. Hotels cannot rely solely on historical or static pricing; they must continuously track OTA rates, in-app pricing, and market trends to remain competitive. By leveraging tools to Extract Expedia Hotel API Data and Extract Booking.com Hotel API Data, hoteliers can collect comprehensive datasets that include nightly rates, room types, discounts, availability, and OTA-specific surcharges.

Additionally, comparing OTA rates to direct in-app hotel pricing via methods to Scrape market hotel rates vs in-app prices provides actionable insights for revenue managers, enabling strategic adjustments that can drive higher direct bookings and reduce commission dependency.

Research Objectives

This research aims to:

• Conduct a detailed comparison of hotel room rates across Expedia and Booking.com.

• Evaluate discrepancies between OTA-listed rates and in-app hotel prices.

• Identify pricing patterns across different room types, hotel star ratings, and seasonal trends.

• Analyze surge periods, promotions, and discounts for informed pricing strategy.

• Provide actionable recommendations using Hotel Data Scraping Services to optimize revenue.

• Build a comprehensive historical Hotel Room Price Trends Dataset for predictive analytics.

Methodology

Step 1: Platform Selection

• Expedia and Booking.com were selected due to their global reach, popularity among travelers, and extensive hotel listings.

Step 2: Data Extraction

• Automated extraction was performed using APIs and scraping scripts, ensuring accurate collection of price, availability, discounts, and cancellation policies.

• Daily rate updates were captured to reflect market fluctuations.

Step 3: Data Cleaning and Normalization

• All room types were standardized: Standard, Deluxe, Suite, Executive.

• Prices were converted to INR, including taxes and fees, to allow fair comparison across platforms.

• Discounted rates, promotional offers, and last-minute deals were separately flagged.

Step 4: Analysis

• Differences between OTA and in-app rates were calculated.

• Monthly, weekly, and daily trends were examined.

• Seasonal variations and festival-period surges were tracked.

Step 5: Reporting

• Tables, charts, and visualizations were prepared for actionable insights.

• Key metrics like price gaps, surge percentages, and room-type trends were highlighted.

Data Collection Parameters

• Sourcing Platforms: Data was aggregated from Expedia and Booking.com, the primary drivers of OTA (Online Travel Agency) bookings in the region.

• Geographic Scope: The study covered six key Indian metros and leisure hubs: Delhi, Mumbai, Bengaluru, Jaipur, Goa, and Hyderabad.

• Inventory Categories: Monitoring was conducted across four distinct room types: Standard, Deluxe, Suite, and Executive.

• Booking Conditions: To account for flexibility premiums, the data tracked both Non-refundable and Free Cancellation rate types.

• Core Metrics: Captured variables included the base price per night, applied discounts, statutory taxes, and real-time inventory availability.

• Temporal Window: The collection period spanned three months, from September 1, 2025, to November 30, 2025.

• Observation Frequency: Data points were logged on a daily basis, ensuring a granular view of the dynamic pricing shifts typical of the Indian festival season.

OTA vs In-App Price Comparison

Hotel Rate Comparison (INR per night)

• The Grand Palace (Delhi)

• Rates: ₹8,500 (Expedia) | ₹8,200 (Booking.com) | ₹7,900 (In-App)

• Variance: Expedia is ₹300 more expensive than Booking.com.

• Royal Orchid (Mumbai)

• Rates: ₹7,200 (Expedia) | ₹7,500 (Booking.com) | ₹7,000 (In-App)

• Variance: Booking.com is ₹300 more expensive than Expedia.

• Leela Heights (Bengaluru)

• Rates: ₹9,800 (Expedia) | ₹9,500 (Booking.com) | ₹9,300 (In-App)

• Variance: Expedia is ₹300 more expensive than Booking.com.

• Taj Residency (Jaipur)

• Rates: ₹6,500 (Expedia) | ₹6,400 (Booking.com) | ₹6,200 (In-App)

• Variance: Expedia is ₹100 more expensive than Booking.com.

• Goa Beach Resort (Goa)

• Rates: ₹10,200 (Expedia) | ₹9,900 (Booking.com) | ₹9,700 (In-App)

• Variance: Expedia is ₹300 more expensive than Booking.com.

Analysis:

• Expedia rates are typically higher than Booking.com rates by 2–5%, providing opportunities for hotels to adjust direct in-app pricing competitively.

• The in-app rate is consistently lower than both OTA rates, demonstrating the value of promoting direct bookings.

• Regional variations indicate that business-heavy cities (Delhi, Mumbai) have higher surges, while leisure destinations (Goa, Jaipur) have more pronounced seasonal fluctuations.

Room Type Price AnalysisRoom Category Price Analysis (INR per night)

• The Grand Palace | Standard Room

• Rates: ₹8,500 (Expedia) | ₹8,200 (Booking.com) | ₹7,900 (In-App)

• Price Gap: ₹600 (Difference between highest and lowest rate)

• The Grand Palace | Deluxe Room

• Rates: ₹10,500 (Expedia) | ₹10,200 (Booking.com) | ₹10,000 (In-App)

• Price Gap: ₹500

• Royal Orchid | Suite

• Rates: ₹12,000 (Expedia) | ₹11,800 (Booking.com) | ₹11,500 (In-App)

• Price Gap: ₹500

• Leela Heights | Standard Room

• Rates: ₹9,800 (Expedia) | ₹9,500 (Booking.com) | ₹9,300 (In-App)

• Price Gap: ₹500

• Taj Residency | Deluxe Room

• Rates: ₹7,800 (Expedia) | ₹7,700 (Booking.com) | ₹7,500 (In-App)

• Price Gap: ₹300

Insights:

• Deluxe and Suite rooms exhibit larger OTA-in-app price gaps, suggesting opportunities for premium segment pricing strategies.

• Standard rooms have smaller gaps, indicating stable pricing patterns.

• Hotels can use this data for targeted upselling and promotional offers on higher-value room categories.

Monthly Price TrendsAverage Monthly Rate Comparison (INR per night)

• September

• Rates: ₹8,700 (Expedia) | ₹8,500 (Booking.com) | ₹8,200 (In-App)

• Average Gap: ₹400

• October

• Rates: ₹9,000 (Expedia) | ₹8,800 (Booking.com) | ₹8,500 (In-App)

• Average Gap: ₹500

• November

• Rates: ₹9,200 (Expedia) | ₹9,000 (Booking.com) | ₹8,700 (In-App)

• Average Gap: ₹500

Insights:

• Price surges are evident in October–November due to festival travel and holiday bookings.

• Hotel Room Price Trends Dataset reveals predictable patterns for peak seasons, enabling proactive dynamic pricing adjustments.

Surge & Discount Analysis

• Expedia Surges: Peaks of 5–12% above Booking.com during festivals, weekends, and business conferences.

• Booking.com Discounts: Last-minute deals often 3–7% lower than Expedia, influencing price-sensitive travelers.

• In-App Pricing:Hotels can attract more direct bookings by offering slightly lower in-app rates than OTAs.

• Recommendation: Use competitive OTA hotel rate scraping to monitor these fluctuations in real-time and adjust pricing dynamically.

Regional Price Analysis

• Delhi & Mumbai: Business-centric cities show weekday rate surges; OTA prices 5–10% higher than in-app rates.

• Bengaluru & Hyderabad: Consistent tech-tourism demand; smaller surges; in-app rates 3–5% lower.

• Goa & Jaipur:Seasonal tourist destinations; OTA rates spike during holidays and festivals.

• Observation: Regional variations must guide localized pricing strategies for optimal revenue.

Star Rating & Hotel Category Analysis

• 5-Star Hotels: Largest discrepancies between OTA and in-app rates; potential for higher-margin promotions.

• 4-Star Hotels: Moderate gaps; weekend pricing adjustments can improve occupancy.

• 3-Star Hotels:Smaller gaps; consistent baseline pricing maintains stable occupancy levels.

• Actionable Insight: Segment pricing strategies based on star ratings to maximize ROI.

Promotional Strategy Analysis

• OTAs frequently bundle discounts, cashback, or perks, creating discrepancies with direct in-app rates.

• Hotels can leverage Expedia & Booking.com price comparison to align promotions strategically.

• Direct bookings can be incentivized via loyalty programs, seasonal packages, or exclusive offers, reducing dependency on OTA commissions.

Revenue Optimization Recommendations

• Dynamic In-App Pricing: Adjust rates based on OTA price trends and seasonal surges.

• Targeted Premium Room Promotions: Focus on Deluxe and Suite rooms for high-margin gains.

• Daily Rate Monitoring: Use Hotel Data Scraping Services to capture real-time changes.

• Predictive Pricing: Leverage historical Hotel Room Price Trends Dataset for forecasting surges.

• Direct Booking Incentives: Encourage guests to book via hotel apps through discounts, loyalty points, and exclusive offers.

Conclusion

Hotels that perform detailed hotel market rates vs app prices analysis can gain a clear understanding of pricing dynamics, seasonal trends, and competitor strategies. By leveraging Scrape Expedia hotel prices Data, they can track fluctuations in real-time, enabling quick adjustments to maintain competitiveness. Similarly, using a Booking.com hotel rate scraper provides insights into promotional offers, last-minute discounts, and room availability, ensuring comprehensive market coverage. Integrating Hotel Data Intelligence into pricing strategy allows hotels to optimize in-app rates, target premium room categories, and implement data-driven revenue management. Continuous monitoring, frequent analysis, and strategic price adjustments based on OTA and in-app data are essential for maximizing profitability, improving occupancy, and enhancing direct booking performance.

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Source : https://www.travelscrape.com/competitor-hotel-pricing-analysis-expedia-booking-com.php

Originally published at https://www.travelscrape.com.

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