Graph and download economic data for Producer Price Index by Industry: Hotels and Motels, Except Casino Hotels (PCU721110721110) from Dec 2003 to Sep 2025 about casino, hotel, PPI, industry, inflation, price index, indexes, price, and USA.

This statistic shows annual growth in average global hotel rates from 2010 to 2018. Global hotel rates were forecasted to increase by 3.7 percent in 2018.

The average daily rate of the hotel industry in the Americas reached around 123.37 U.S. dollars in 2016.

The average daily rate (ADR) of the United States hotel industry was ****** U.S. dollars in 2022, reflecting an increase over the previous year. The decline in ADR in both 2020 and 2021 can be attributed to the disruptions in travel and stay-at-home restrictions implemented due to the coronavirus (COVID-19) pandemic. What is average daily rate (ADR)? Average daily rate is a key performance indicator of the hospitality industry. It shows the average room rental price per day in either a specific hotel (independent/chain), or in this case the average room rental price per day of many hotels within the U.S. Other useful KPI’s that are used in the lodging industry are the occupancy rate and revenue per available room (RevPAR).

The average daily rate (ADR) of hotels in the United States was ***** U.S. dollars as of November 2020. Due to the impact of the coronavirus pandemic in the hotel industry, this figure dropped to about **** percent when compared to last year's figure.

What is average daily rate?

Average daily rate is a key performance indicator of the hospitality industry. It shows the average room rental price per day in either a specific hotel (independent/chain), or in this case the average room rental price per day of many hotels within the U.S. Other useful KPI’s in the lodging industry are the  occupancy rate and revenue per available room (RevPAR).

Monthly ADR trends

Patterns are quite easy to discern in the monthly ADR of U.S. hotels. It often peaks annually in October and shows a dip in January. This dip could be due to lower spending from consumers after the expensive winter holiday season. Additionally, U.S. hotel ADR rates have shown annual growth month-to-month since 2011.

The hospitality industry is booming in the last 10 years of India. It is due to growing business opportunities and IT presence in the cities of India, especially metro cities. Here the data is scrapped from MakeMyTrip booking site, which includes price and other information of hotels in different cities of the country. Data was scrapped on 19th August 2023. Only nearly 100 hotels have been added for each city. Other cities will be updated soon.

Available cities🏙️: - Bangalore - Chennai - Hyderabad - Mumbai - Delhi - Kolkata

Data Source: MakeMyTrip🔗

Data Scraping code: GitHub🔗

Columns in dataset: - Hotel Name - Rating - Rating Description - Reviews - Star rating - Location - Nearest Landmark - Distance to the Landmark - Price - Tax

Please Note: 1. Price given here is for one night (base room). 2. Tax given here is slapped on top of the price payable. Therefore, total amount = Price + Tax

View monthly updates and historical trends for US Inflation Rate: Hotels and Restaurants. from United States. Source: Eurostat. Track economic data with Y…

The USA Hotels Dataset from Booking.com is a rich collection of data related to hotels across the United States, extracted from Booking.com. This dataset includes essential information about hotel listings, such as hotel names, locations, prices, star ratings, customer reviews, and amenities offered. It's an ideal resource for researchers, data analysts, and businesses looking to explore the hospitality industry, analyze customer preferences, and understand pricing patterns in the U.S. hotel market.

Access 3 million+ US hotel reviews — submit your request today.

Key Features:

• Hotel Information: Includes hotel names, addresses, star ratings, and descriptions.
• Pricing Data: Nightly rates, discounts, and price variations by room type and season.
• Customer Reviews: Aggregated ratings and detailed user feedback from verified guests.
• Amenities: Detailed list of amenities provided by each hotel (e.g., Wi-Fi, parking, spa, swimming pool).
• Geographical Information: Hotel locations including city, state, and proximity to major landmarks.

Use Cases:

• Sentiment Analysis: Analyze customer reviews to gauge hotel service quality and guest satisfaction.
• Price Analysis: Compare pricing across different hotels, locations, and time periods to identify trends.
• Recommendation Systems: Build recommendation engines based on customer ratings, reviews, and preferences.
• Tourism and Hospitality Research: Understand patterns in hotel demand and services across various U.S. cities.

In 2024, the Hotel Price Index (HPI) in Spain reached a peak in May at over *** points, which was the highest HPI recorded since at least January 2020 and was above by *** percent versus the same month of the previous year.

We will create a customized hotels dataset tailored to your specific requirements. Data points may include hotel names, location details, pricing information, amenity lists, guest ratings, occupancy rates, and other relevant metrics.

Utilize our hotels datasets for a variety of applications to boost strategic planning and market analysis. Analyzing these datasets can help organizations understand guest preferences and market trends within the hospitality industry, allowing for more precise operational adjustments and marketing strategies. You can choose to access the complete dataset or a customized subset based on your business needs.

Popular use cases include: optimizing booking strategies, enhancing guest experience, and competitive benchmarking.

Hotel Rate Shopping Market Outlook

According to our latest research, the global hotel rate shopping market size reached USD 1.43 billion in 2024, reflecting robust growth driven by the hospitality sector’s increasing reliance on dynamic pricing strategies and advanced analytics. The market is expected to expand at a CAGR of 8.7% from 2025 to 2033, reaching a projected value of USD 2.99 billion by 2033. This upward trajectory is propelled by the growing adoption of cloud-based solutions, the integration of AI-powered rate intelligence, and the escalating competition among hotels and online travel agencies (OTAs) to optimize pricing and maximize revenue.

One of the primary growth factors for the hotel rate shopping market is the hospitality industry’s accelerated digital transformation. As hotels seek to stay competitive in a rapidly evolving landscape, they are increasingly investing in sophisticated rate shopping tools that provide real-time insights into competitor pricing, market demand, and consumer trends. The proliferation of metasearch engines and OTAs has made pricing transparency a critical success factor, prompting hotels to leverage advanced software solutions for continuous price monitoring and optimization. Furthermore, the integration of machine learning and AI technologies within rate shopping platforms enables hotels to predict demand fluctuations more accurately, automate pricing decisions, and respond swiftly to market changes, thereby driving higher occupancy rates and revenue per available room (RevPAR).

Another significant driver is the rising importance of revenue management in the post-pandemic era. The hospitality sector has witnessed a paradigm shift, with hoteliers placing greater emphasis on data-driven decision-making to recover from revenue losses and adapt to changing guest preferences. Rate shopping tools have become indispensable for revenue managers, enabling them to benchmark their rates against competitors, identify pricing gaps, and implement dynamic pricing strategies. Additionally, the growing trend of personalized guest experiences and tailored pricing models is fueling the demand for granular market intelligence, further boosting the adoption of hotel rate shopping solutions. The evolution of cloud-based platforms has also democratized access to these tools, making them affordable and scalable for both independent hotels and large chains.

The expansion of online travel agencies and the increasing complexity of distribution channels represent another pivotal growth factor. OTAs and metasearch platforms have transformed the way consumers compare hotel prices, compelling hotels to maintain rate parity and competitive pricing across multiple channels. This has created a pressing need for automated rate shopping solutions that can track rates across hundreds of websites in real time, providing actionable insights for both hotels and OTAs. The growing collaboration between technology providers and hospitality brands is also fostering innovation, with new features such as predictive analytics, competitor benchmarking, and market segmentation analysis becoming standard offerings in modern rate shopping platforms.

From a regional perspective, North America continues to lead the global hotel rate shopping market, accounting for the largest revenue share in 2024. The region’s dominance is attributed to the high concentration of international hotel chains, advanced IT infrastructure, and early adoption of cloud-based revenue management systems. Europe follows closely, with a strong focus on digitalization in the hospitality sector and stringent regulatory requirements for pricing transparency. The Asia Pacific region is emerging as the fastest-growing market, driven by rapid urbanization, a booming travel industry, and increasing investments in hospitality technology. Latin America and the Middle East & Africa are also witnessing steady growth, supported by the rise of tourism and government initiatives to modernize the hospitality sector.

Component Analysis

The hotel rate shopping market is

Hotel Price Index: 2001=100: Weekend data was reported at 110.200 2001=100 in Dec 2007. This records a decrease from the previous number of 111.800 2001=100 for Nov 2007. Hotel Price Index: 2001=100: Weekend data is updated monthly, averaging 107.900 2001=100 from Jan 2000 (Median) to Dec 2007, with 96 observations. The data reached an all-time high of 121.000 2001=100 in Aug 2001 and a record low of 90.170 2001=100 in Apr 2000. Hotel Price Index: 2001=100: Weekend data remains active status in CEIC and is reported by National Statistics Institute. The data is categorized under Global Database’s Spain – Table ES.Q026: Hotel Price Index.

India Consumer Price Index (CPI): Miscellaneous: Hotel Lodging Charges data was reported at 125.300 2012=100 in Oct 2018. This records an increase from the previous number of 123.000 2012=100 for Sep 2018. India Consumer Price Index (CPI): Miscellaneous: Hotel Lodging Charges data is updated monthly, averaging 116.700 2012=100 from Jan 2014 (Median) to Oct 2018, with 58 observations. The data reached an all-time high of 140.700 2012=100 in Aug 2017 and a record low of 108.000 2012=100 in Feb 2014. India Consumer Price Index (CPI): Miscellaneous: Hotel Lodging Charges data remains active status in CEIC and is reported by Central Statistics Office. The data is categorized under India Premium Database’s Inflation – Table IN.IA017: Consumer Price Index: 2012=100: Miscellaneous.

Hotel Rate Shopping Market Outlook

According to our latest research, the global hotel rate shopping market size in 2024 stands at USD 1.62 billion, with a robust CAGR of 10.7% projected during the forecast period from 2025 to 2033. By 2033, the market is forecasted to reach USD 4.06 billion. This impressive growth is primarily driven by the hospitality industry's increasing reliance on advanced pricing intelligence and dynamic rate management to stay competitive in a rapidly evolving digital landscape. The adoption of AI-powered solutions, real-time analytics, and seamless integration with property management systems are pivotal factors propelling this market forward, as per our comprehensive market analysis.

One of the key growth drivers in the hotel rate shopping market is the intensifying competition among hotels, resorts, and online travel agencies (OTAs) to capture price-sensitive customers. The proliferation of digital booking platforms and meta-search engines has made rate transparency a necessity, compelling hoteliers to monitor and adjust their pricing strategies in real-time. Hotels and travel companies are leveraging rate shopping tools to gain actionable insights into competitors’ pricing, promotional tactics, and inventory availability. This enables them to optimize their own rates, enhance occupancy levels, and maximize revenue per available room (RevPAR). The adoption of sophisticated rate shopping software is further fueled by the growing demand for personalized guest experiences, which require agile and data-driven pricing mechanisms.

Another significant factor contributing to the expansion of the hotel rate shopping market is the integration of cloud-based solutions and artificial intelligence. Cloud deployment offers unparalleled scalability, real-time data access, and cost-effectiveness, making it the preferred choice for both large hotel chains and independent properties. AI-powered rate intelligence platforms can process vast volumes of market data, identify pricing trends, and recommend optimal rate adjustments instantaneously. This automation reduces manual effort, minimizes pricing errors, and enables hoteliers to respond swiftly to market fluctuations. Additionally, the rise of mobile bookings and the need for omnichannel rate consistency are pushing the adoption of advanced rate shopping tools across the hospitality sector.

The growing emphasis on revenue management and competitive benchmarking is also fueling market growth. Revenue managers are increasingly relying on comprehensive rate intelligence to make informed decisions about pricing, distribution channels, and promotional strategies. By benchmarking their rates against competitors and monitoring market demand, hotels can identify opportunities to increase direct bookings and reduce dependency on OTAs, thereby improving profitability. The integration of rate shopping solutions with channel management systems further streamlines the distribution process, reduces the risk of rate parity issues, and enhances overall operational efficiency.

Regionally, North America continues to dominate the hotel rate shopping market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The high concentration of global hotel chains, tech-savvy consumers, and advanced digital infrastructure in North America has accelerated the adoption of rate shopping solutions. Asia Pacific is expected to witness the highest CAGR of 12.4% during the forecast period, driven by the rapid growth of the travel and tourism industry, increasing internet penetration, and the emergence of new hospitality players in countries like China, India, and Southeast Asia. Europe, with its mature hospitality sector and focus on digital transformation, also represents a significant growth opportunity for market players.

Component Analysis

The hotel rate shopping market is segmented by component into software and services, each playing a critical role in the overall value proposition for hoteliers. The software segment comprises advanced rate intelligence platforms, dynamic pricing engines, and integrated analytics dashboards that provide real-time competitor pricing data, market trends, and actionable insights. These platforms are increasingly leveraging artificial intelligence and machine learning to automate data collection, analysis, and rate recommendations, enabling hotels to respond proactively to market changes. The software seg

Graph and download economic data for Consumer Price Index for All Urban Consumers: Lodging Away from Home in U.S. City Average (CUUR0000SEHB) from Dec 1997 to Sep 2025 about lodging, urban, consumer, CPI, housing, inflation, price index, indexes, price, and USA.

How much does a city trip with your sweetheart cost in Valentine's Day(2025)? Which popular tourist destinations are more budget friendly in Europe? I gathered a dataset which consists of search results from more than 15 cities and 600 hotels in Europe.

I searched booking.com, filtered the results for 2 adults, 5-star hotel, private bathroom, more than 7.0 points in reviews. I preferred to present the prices in USD for enabling future comparisons.

Happy Valentines.

Hotel Rate Shopper Software Market size was valued at USD 632.79 Million in 2023 and is projected to reach USD 3,250 Million by 2030, growing at a CAGR of 14.7 % during the forecast period 2024-2030.

Global Hotel Rate Shopper Software Market Drivers

The market drivers for the Hotel Rate Shopper Software Market can be influenced by various factors. These may include:

The hospitality industry: The hospitality industry is becoming more competitive as more hotels and lodging options enter the market. As a result, hoteliers must adapt their pricing tactics to remain competitive. Rate shopper software can assist them in tracking and evaluating the prices of rival companies.

Trends in Dynamic Pricing: The hotel sector has been using dynamic pricing techniques more and more, modifying rates according to demand, seasonality, and events, among other variables. Tools for rate shoppers help hotels price their rooms dynamically to maximise profits.

Growing Online Travel Agencies (OTAs): As online booking sites and OTAs have become more common, hotel competition has increased. Hotels can monitor these firms' pricing tactics and modify their rates by using rate shopper software.

Demand for Real-Time Data: In order to quickly and intelligently make decisions, hoteliers are looking for real-time data into rival pricing and market trends. Tools for rate shoppers that offer precise and fast data are needed to support pricing decisions.

Dataset

This dataset was created by ShreyasBagwe1015

Released under Apache 2.0

Contents

Hotel Price Intelligence Market Outlook

According to our latest research, the global Hotel Price Intelligence market size reached USD 1.84 billion in 2024, reflecting robust industry growth supported by the increasing adoption of dynamic pricing strategies and advanced analytics within the hospitality sector. The market is projected to grow at a CAGR of 10.7% from 2025 to 2033, ultimately reaching a forecasted value of USD 4.16 billion by 2033. This remarkable expansion is primarily driven by the escalating demand for data-driven decision-making tools, the proliferation of online travel agencies, and the intensifying competition among hotels to optimize occupancy and maximize revenue.

A significant growth factor for the Hotel Price Intelligence market is the surging reliance on sophisticated pricing analytics to enhance revenue management strategies. As hotels face increasing pressure to remain competitive in a rapidly evolving digital landscape, the integration of real-time price intelligence solutions enables them to monitor competitor pricing, analyze market trends, and dynamically adjust their own rates. The growing complexity of distribution channels, coupled with fluctuating demand patterns, has made it essential for hoteliers to leverage advanced software and services that provide actionable insights. This trend is further amplified by the proliferation of online booking platforms and meta-search engines, which have heightened price transparency and intensified the need for competitive benchmarking.

Another key driver propelling the Hotel Price Intelligence market is the widespread adoption of cloud-based deployment models. Cloud technology offers unparalleled scalability, flexibility, and cost-effectiveness, enabling hotels of all sizes to access powerful price intelligence tools without significant upfront investment in IT infrastructure. The shift towards cloud-based solutions has democratized access to advanced analytics, allowing even small and boutique hotels to implement sophisticated revenue management strategies. Moreover, cloud platforms facilitate seamless integration with property management systems, channel managers, and other hospitality software, streamlining operations and enhancing the accuracy of pricing decisions.

Additionally, the growing focus on personalized guest experiences and the need for granular demand forecasting have spurred innovation within the Hotel Price Intelligence market. Hoteliers are increasingly utilizing artificial intelligence (AI) and machine learning algorithms to anticipate booking patterns, segment customer profiles, and optimize rates in real time. These technologies enable hotels to respond swiftly to market shifts, capture incremental revenue opportunities, and build more resilient pricing strategies. The emergence of new data sources, such as social media sentiment and online reviews, is further enriching the analytics landscape, empowering hotels to make more informed pricing decisions and deliver greater value to guests.

From a regional perspective, North America currently dominates the Hotel Price Intelligence market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The region's leadership can be attributed to the high concentration of international hotel chains, advanced technological infrastructure, and a mature online travel ecosystem. However, Asia Pacific is expected to witness the highest growth rate over the forecast period, driven by rapid urbanization, expanding tourism sectors, and increasing digitalization across emerging economies. The competitive landscape is also evolving, with local players and global technology providers vying for market share by offering innovative, region-specific solutions tailored to diverse hotel segments.

Component Analysis

The Component segment of the Hotel Price Intelligence market is bifurcated into Software and Services, each playing a pivotal role in shaping the industry’s growth trajectory. The software segment encompasses a wide arr

United States - Producer Price Index by Industry: Hotels and Motels, Except Casino Hotels: Hotel and Motel Food and Beverage and Related Services was 165.94100 Index Dec 2003=100 in August of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Industry: Hotels and Motels, Except Casino Hotels: Hotel and Motel Food and Beverage and Related Services reached a record high of 165.94100 in August of 2025 and a record low of 100.00000 in January of 2004. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Industry: Hotels and Motels, Except Casino Hotels: Hotel and Motel Food and Beverage and Related Services - last updated from the United States Federal Reserve on November of 2025.

Colombia Hotel Rates: Real Index data was reported at 11.631 2005=100 in May 2020. This records an increase from the previous number of 10.021 2005=100 for Apr 2020. Colombia Hotel Rates: Real Index data is updated monthly, averaging 127.868 2005=100 from Jul 2004 (Median) to May 2020, with 191 observations. The data reached an all-time high of 221.798 2005=100 in Dec 2019 and a record low of 10.021 2005=100 in Apr 2020. Colombia Hotel Rates: Real Index data remains active status in CEIC and is reported by National Administrative Department of Statistics. The data is categorized under Global Database’s Colombia – Table CO.Q002: Hotel Rates and Average Room Rate Index: 2005=100.