MakeMyTrip Hotel Rate Intelligence Report 2026 - How Brands Track Hotel Prices and Market Trends

Introduction

The Indian hospitality market has moved into a more data-driven phase, where hotel operators, travel companies, aggregators, investors, and hospitality analysts increasingly rely on structured pricing information to understand demand, competition, and market movements. The MakeMyTrip Hotel Rate Intelligence Report 2026 examines how hotel rate information can be transformed into actionable intelligence for businesses monitoring India's accommodation market.

Hotel rates can change frequently based on destination, booking window, room category, occupancy, seasonality, events, holidays, promotions, and demand conditions. For businesses operating across multiple destinations, manually checking these changes is difficult to scale. Structured travel datasets can help organizations compare room prices, discounts, availability, hotel attributes, and rate movements across locations and time periods.

The broader Indian hospitality industry also demonstrates why pricing intelligence has become increasingly relevant. Hotelivate reported 68.0% occupancy for its 2024/25 India survey base, with ADR increasing 4.7% and RevPAR increasing 5.7%. Its survey covered 2,008 hotels and 196,464 rooms, providing a broad view of India's branded hospitality landscape. (Hotelivate-Savills)

For businesses looking to systematically capture and analyze this information, Travel Data Scraping Services can support recurring collection, normalization, validation, and delivery of structured travel datasets.

This report explores six major dimensions of hotel-rate intelligence, covering historical changes from 2020 through 2026, data collection requirements, API-enabled workflows, pricing intelligence, real-time monitoring, and scalable extraction strategies.

Understanding Hotel Market Movements and Pricing Patterns

The first major area of analysis focuses on MakeMyTrip Hotel Rate Data Analysis and how historical and current rate observations can help businesses identify market patterns.

Hotel pricing is not static. A room listed at one rate during a low-demand weekday may appear at a substantially different price during a weekend, holiday, festival, conference, or high-tourism period. Consequently, a single rate snapshot provides limited intelligence. Repeated observations create a much stronger dataset for studying price movements.

A structured dataset can include hotel name, destination, room category, displayed rate, discounted rate, original rate, meal plan, occupancy information where available, check-in/check-out dates, hotel rating, review count, amenities, and availability status.

Key Industry Indicators

Hotelivate reported that Five-star Deluxe hotels exceeded the 70% occupancy threshold in 2024/25, while their average rate reached ₹16,797, up 7.7% year over year. (Hotelivate-Savills)

2020–2026 Market Evolution

The 2020–2026 period represents a significant transition for hotel pricing analytics. In 2020, travel restrictions and the disruption caused by the pandemic resulted in exceptionally weak travel demand. Hotels faced sharp occupancy pressure, cancellations, changing operating conditions, and considerable uncertainty around pricing.

During 2021, recovery began unevenly. Domestic travel gradually became an important demand driver, while hotel pricing varied significantly by destination and reopening conditions. Businesses tracking hotel rates increasingly needed date-specific information rather than relying on static market assumptions.

In 2022, travel demand strengthened considerably. Leisure destinations, business centers, and pilgrimage locations experienced different recovery trajectories. Pricing datasets became useful for comparing these regional differences and identifying destinations where rates were recovering faster.

By 2023, hotel demand had become substantially stronger. Pricing analysis increasingly incorporated competitive benchmarking, promotional monitoring, room-type comparisons, and seasonal patterns. In 2024, the Indian hospitality sector continued its expansion, while 2024/25 data showed occupancy and ADR growth. Hotelivate recorded 68.0% occupancy across its survey base in 2024/25. (Hotelivate-Savills)

In 2025 and into 2026, the market entered a phase characterized by continued demand, expanding hotel supply, and greater interest in data-led pricing. IBEF reports that India's hotel industry is expected to grow from an estimated US$32 billion in FY20 to US$52 billion by FY27. (India Brand Equity Foundation)

For brands, this evolution means historical rate data can help explain how hotel pricing responds to demand cycles, supply additions, seasonality, and destination-level changes.

Building a Scalable Hotel Data Pipeline

Hotel Rate Data Collection from MakeMyTrip can provide businesses with a structured approach to gathering accommodation pricing information across destinations, properties, dates, and room categories.

The value of collection depends heavily on data structure. A useful hotel dataset should not simply contain a price. It should preserve the context surrounding that price.

For example, businesses may want to capture:

• Hotel name and property identifier
• Destination and location
• Check-in and check-out dates
• Room category
• Base room rate
• Discounted rate
• Discount percentage
• Meal-plan information
• Availability
• Hotel rating
• Review count
• Amenities
• Cancellation information
• Collection timestamp
• Property URL or reference
• Other publicly displayed attributes

Data Collection Framework

2020–2026 Collection Trends

In 2020, hotel-data collection was primarily affected by unstable travel patterns and rapidly changing availability. Traditional periodic research often became outdated quickly because hotel operating conditions changed frequently.

In 2021, businesses began placing greater emphasis on automated collection because manual research across destinations was difficult to maintain. Data workflows needed to accommodate changing hotel availability and uneven market recovery.

During 2022, broader travel recovery increased the number of properties and destinations requiring monitoring. Data collection therefore shifted toward larger property universes, recurring schedules, and standardized schemas.

In 2023, competitive pricing became more important as hotels and travel businesses sought to understand how their rates compared across properties and booking dates. Structured datasets enabled organizations to calculate price differences and identify recurring pricing patterns.

By 2024 and 2025, the expansion of India's hospitality supply created additional monitoring requirements. India added approximately 14,400 hotel rooms in 2024, with 67% of new rooms located beyond the top 10 markets, according to information reported by IBEF from Horwath HTL. (India Brand Equity Foundation)

In 2026, collection workflows increasingly need to support high-frequency monitoring, multiple destinations, historical storage, and automated validation. The objective is no longer simply to collect hotel prices but to create a dependable historical dataset that can support benchmarking, forecasting inputs, pricing research, and competitive analysis.

Connecting Hotel Data With Automated Systems

Businesses that require frequently refreshed information may incorporate Real-Time API Data from MakeMyTrip into broader data pipelines where technically and contractually appropriate.

API-oriented workflows can help organizations move collected information into databases, dashboards, analytical systems, or internal applications. Instead of relying exclusively on manually downloaded files, structured feeds can support automated processing and scheduled refreshes.

A typical architecture may include a collection layer, validation layer, normalization engine, database, analytics layer, and reporting interface.

Example Architecture

The availability and permissible use of any API depend on the provider's technical access, commercial terms, and applicable policies. Businesses should use authorized interfaces and data-access methods.

2020–2026 Technology Progression

In 2020, hotel analytics often relied heavily on manually compiled spreadsheets and periodic market research. The volatility of travel demand exposed the limitations of infrequent updates.

During 2021, automation became increasingly valuable because travel conditions could change rapidly. Organizations began looking for repeatable processes capable of updating hotel information without extensive manual intervention.

In 2022, cloud databases and automated pipelines became more common components of travel-data operations. Businesses could combine hotel data with destination, travel, and market datasets to build broader intelligence systems.

In 2023, API-driven architectures increasingly supported integration with dashboards and business applications. Instead of treating collected data as a standalone report, organizations could connect it to internal pricing, revenue, or competitive-analysis systems.

By 2024 and 2025, hotel businesses were operating in an environment where demand and pricing information needed to be interpreted alongside supply growth. Hotelivate reported that proposed branded-hotel supply was expected to cross 100,000 rooms over the following five years, highlighting the scale of future market expansion. (Hotelivate-Savills)

In 2026, automated delivery and system integration are increasingly relevant for businesses managing large hotel datasets. Properly structured feeds can reduce repetitive manual work and enable organizations to incorporate updated rate information into recurring analytical workflows.

Turning Rate Observations Into Commercial Intelligence

MakeMyTrip Hotel Pricing Data Intelligence involves transforming individual hotel-rate observations into broader competitive and market insights.

Raw pricing information becomes more valuable when analyzed across multiple dimensions. Businesses can compare properties within the same destination, evaluate room categories, identify discount patterns, monitor changes over booking windows, and segment hotels by rating or positioning.

For example, an analytics system can calculate:

• Average displayed rate by destination
• Median hotel rate
• Minimum and maximum observed rates
• Rate changes over time
• Discount frequency
• Destination-level price differences
• Weekend versus weekday rates
• Premium versus budget property pricing
• Seasonal price movements
• Competitive price gaps

Sample Analytical Metrics

2020–2026 Intelligence Development

The period beginning in 2020 demonstrates why context is essential when interpreting hotel rates. A low price during a disruption does not necessarily represent a sustainable competitive advantage; it may reflect temporary demand conditions.

In 2021, destination-level segmentation became important because different regions recovered at different speeds. Businesses needed to distinguish between market-wide changes and property-specific movements.

In 2022, growing demand made rate comparisons more meaningful. Competitive analysis could identify hotels that were increasing prices faster than their local market or properties that maintained promotional pricing despite rising demand.

In 2023, businesses increasingly combined pricing information with ratings, reviews, amenities, and hotel categories. This created more nuanced comparisons than simply ranking properties by price.

In 2024, continued hospitality growth increased the importance of understanding rate positioning. Hotelivate reported 68.0% national occupancy in its 2024/25 survey base, while ADR and RevPAR increased 4.7% and 5.7%, respectively. (Hotelivate-Savills)

In 2025 and 2026, hotel pricing intelligence can increasingly be used as one component of revenue and competitive analysis. However, rate observations should be interpreted alongside availability, booking dates, taxes or fees where displayed, cancellation conditions, room type, and other relevant attributes. This prevents businesses from treating different rate products as directly comparable when their underlying conditions differ.

Tracking Market Changes as They Happen

Real-Time MakeMyTrip Hotel Price Monitoring can help businesses identify significant pricing changes without waiting for a periodic manual review.

Frequent monitoring is particularly useful for destinations where rates can change quickly. Hotels may adjust prices around weekends, festivals, sporting events, conferences, school holidays, long weekends, or sudden changes in demand.

A monitoring workflow can establish predefined thresholds. For example, a business could flag a hotel whenever the displayed rate changes by more than a specified percentage, a property becomes unavailable, or a competitor introduces a significant discount.

Monitoring Indicators

2020–2026 Monitoring Evolution

In 2020, real-time monitoring was particularly challenging because hotel availability and travel restrictions could change rapidly. Periodic reports often struggled to capture these short-lived conditions.

In 2021, automated monitoring became more useful as travel demand returned unevenly. Businesses could track how individual destinations responded to changing demand.

During 2022, monitoring expanded from simple price collection toward event-driven analysis. Long weekends, holidays, and popular travel periods created noticeable rate movements.

In 2023, businesses increasingly looked at rate histories rather than isolated observations. This enabled them to distinguish temporary promotions from recurring pricing behavior.

By 2024, India's hospitality market had entered a stronger growth phase. Hotelivate's research recorded broad improvement in occupancy and rate performance, while its 2024/25 survey also showed significant differences between established hotels and the wider market. (Hotelivate-Savills)

In 2025 and 2026, real-time or high-frequency monitoring can support more responsive competitive research. Hotelivate reported that Q2 2025/26 recorded 7% ADR growth year over year, illustrating how quickly pricing indicators can move even within relatively short reporting periods. (Hotelivate-Savills)

For businesses, the main benefit of monitoring is not simply speed. It is the ability to create a continuous historical record that shows when pricing changed and how much it changed.

Scaling Extraction Across Properties and Destinations

MakeMyTrip hotels data extraction can be designed as a scalable process for businesses requiring information across multiple cities, property categories, room types, and travel dates.

Scalability is critical because a hotel intelligence project can quickly grow from hundreds of properties to thousands of property-date combinations. Each additional check-in date, room category, destination, or monitoring frequency increases the volume of observations.

A scalable framework should therefore include structured schemas, duplicate handling, validation, timestamping, error management, and historical storage.

Scalable Extraction Framework

2020–2026 Scaling Journey

In 2020, the primary challenge was maintaining reliable hotel information during a highly disrupted market. Smaller datasets and manual processes were common, but their limitations became increasingly visible.

In 2021, automated extraction helped organizations expand beyond individual properties and destinations. Recurring collection schedules became more practical for monitoring recovery.

In 2022, larger hotel universes increased the importance of standardized data schemas. Businesses needed consistent fields across thousands of records to perform meaningful comparisons.

In 2023, data engineering became increasingly important because rate information needed to be integrated with analytics platforms. Historical databases allowed businesses to compare current rates with previous observations.

In 2024 and 2025, expanding hotel supply increased the potential scale of monitoring. IBEF reported that India's organized hotel industry was expected to add more than 100,000 rooms and surpass 300,000 rooms by 2029. (India Brand Equity Foundation)

By 2026, scalable extraction can support multi-destination hotel intelligence programs involving thousands of properties and repeated date-level observations. For businesses, the objective is to create a consistent, validated, analytics-ready dataset rather than simply collect a large volume of unstructured information.

Building a Stronger Pricing Intelligence Strategy

The MakeMyTrip Hotel Rate Intelligence Report 2026 demonstrates how hotel pricing information can support a broader competitive-intelligence framework.

The most useful datasets combine multiple observations over time instead of relying on isolated prices. Historical rate records can reveal seasonal patterns, destination-level differences, competitive gaps, discount behavior, and changes in visible availability.

The wider market supports the importance of this approach. Hotelivate's 2025 research showed India's 2024/25 hotel occupancy at 68.0%, while premium hotel categories recorded strong ADR and RevPAR performance. (Hotelivate-Savills)

For businesses, the practical value comes from connecting collection with analysis. A well-designed pipeline can turn raw hotel observations into dashboards, historical benchmarks, alerts, and structured research outputs.

Actowiz Solutions focuses on building structured web-data workflows designed around specific business intelligence requirements. For hospitality and travel businesses, this can include property-level data collection, price monitoring, historical datasets, normalization, validation, and recurring delivery.

The MakeMyTrip Data Scraping workflow can be designed around the fields, destinations, property universe, frequency, and analytical requirements defined by the client.

Key capabilities can include:

• Scalable hotel data collection
• Structured property and room-level datasets
• Price and discount tracking
• Destination-level benchmarking
• Historical data storage
• Automated data validation
• Recurring monitoring
• API-ready or database-ready delivery
• Custom analytical fields
• Data normalization and deduplication

Actowiz Solutions can also help businesses integrate collected information into broader market-intelligence workflows, enabling hotel data to be compared with other travel, pricing, or competitive datasets.

The focus is on creating reliable, reusable data pipelines rather than one-time extraction. This makes the resulting datasets more useful for organizations that need ongoing market visibility.

Conclusion

The MakeMyTrip Hotel Rate Intelligence Report 2026 highlights the growing importance of structured hotel-rate information in India's evolving hospitality market. From the disruption of 2020 to the stronger demand environment seen through 2024/25 and continuing into 2026, hotel pricing has become increasingly dynamic and data dependent.

Businesses can use recurring hotel data collection to understand rate movements, compare destinations, identify promotional patterns, monitor competitors, and develop historical benchmarks. As India's hotel supply expands and demand continues to evolve, timely and structured data can become an important input for hospitality analytics.

For companies seeking scalable collection and analysis, Web Crawling service capabilities can support recurring acquisition of publicly available web information, while Web Data Mining can help transform collected records into structured datasets for deeper market analysis.

The objective is clear: convert continuously changing hotel-market information into organized, validated, and actionable intelligence.

Ready to build a scalable hotel pricing intelligence solution? Contact Actowiz Solutions to discuss your custom hotel data collection, monitoring, and analytics requirements!