This statistic shows the revenue of the United States hotel industry from 2001 to 2018. In 2018, the revenue of the hotel industry in the U.S. reached *** billion U.S. dollars.

U.S. hotel industry key performance indicators

To measure the performance of the hotel industry sector three basic benchmark figures are commonly used:

• Occupancy rate

• Average daily rate (ADR)

• Revenue per available room (RevPAR)

The occupancy rate denotes the percentage of hotel rooms that are rented out at a given time of all the hotel rooms that are available. In 2018, the average occupancy rate of the U.S. hospitality industry was at **** percent, this was the highest seen since 2001.

The average daily rate (ADR) shows the average rate at which hotel rooms were paid. It is calculated by dividing total rooms revenue by the number of rooms that were occupied. In 2018, the average ADR of hotel rooms in the U.S. reached ****** U.S. dollars. In the Americas region, the average daily rate was relatively stable throughout the year.

Revenue per available room (RevPAR) is a measure of utilization in the hotel industry and can be calculated by multiplying the average daily rate of a property (market) by its occupancy rate. The average RevPAR of hotels in the United States was ***** U.S. dollars in 2018.

his dataset provides comprehensive insights into the operational and revenue performance of a hotel throughout the year 2024. It includes detailed records of daily operations, revenue figures, guest demographics, booking sources, economic indicators, and more. Key features encompass:

Date: The date of the recorded data. Month: Numeric representation of the month. Day of the Week: Numeric representation of the day in a week. Season: Categorical representation of the season (e.g., Winter, Spring, Summer, Fall). Public Holiday: Binary indicator (0 or 1) denoting whether it's a public holiday. Previous Month Revenue: Revenue generated in the previous month. Year-over-Year Revenue: Revenue compared to the same month the previous year. Monthly Trend: Trend in revenue or occupancy for the month. Occupancy Rate: Percentage of rooms occupied. Average Daily Rate (ADR): Average rate charged per occupied room. Revenue per Available Room (RevPAR): Revenue generated per available room. Booking Lead Time: Average lead time between booking and stay. Booking Cancellations: Percentage of bookings cancelled. Booking Source: Source of the booking (e.g., Direct, OTA). Guest Type: Type of guest (e.g., Leisure, Business). Repeat Guests: Percentage of guests who are repeat visitors. Nationality: Nationality of guests. Group Bookings: Binary indicator denoting group bookings. Discounts and Promotions: Use of discounts or promotions. Room Rate: Average rate charged for rooms. Local Events: Presence of local events influencing occupancy. Hotel Events: Events hosted by the hotel affecting operations. Competitor Rates: Rates offered by competitors. Weather Conditions: Local weather conditions influencing guest behavior. Economic Indicators: Economic factors influencing hotel performance. Staff Levels: Staffing levels affecting service quality. Guest Satisfaction: Guest satisfaction ratings. Maintenance Issues: Issues related to maintenance affecting operations. Marketing Spend: Expenditure on marketing activities. Online Reviews: Ratings and reviews provided online. Social Media Engagement: Engagement metrics on social media platforms. Seasonal Adjustments: Adjustments made for seasonal variations. Trend Adjustments: Adjustments made for trending factors. Room Revenue: Total revenue from room bookings. Food and Beverage Revenue: Revenue from food and beverage services. Other Services Revenue: Revenue from other hotel services. Total Revenue for the Month: Overall revenue generated for the month.

Direct state and local tax revenue generated from hotels increased to ***** billion U.S. dollars in 2023. This was well over twenty billion U.S. dollars more than in 2020, when the hotel industry was hit hard by the coronavirus (COVID-19) pandemic. Tax revenue from hotels was forecast to increase again in 2024 to around ***** billion U.S. dollars.

Taiwan Tourist Hotel: Revenue: Room data was reported at 2,124,543.299 NTD th in Mar 2018. This records an increase from the previous number of 1,963,212.105 NTD th for Feb 2018. Taiwan Tourist Hotel: Revenue: Room data is updated monthly, averaging 1,694,873.123 NTD th from Jan 2005 (Median) to Mar 2018, with 159 observations. The data reached an all-time high of 2,466,057.111 NTD th in Dec 2017 and a record low of 1,031,726.870 NTD th in Feb 2009. Taiwan Tourist Hotel: Revenue: Room data remains active status in CEIC and is reported by Tourism Bureau, Ministry of Transportation and Communications. The data is categorized under Global Database’s Taiwan – Table TW.Q010: Hotel Statistics: Tourist Hotel: Revenue.

Data includes occupancy rates, average daily rates, and revenue per available room.

Hotel Revenue Management System Market Outlook

The global hotel revenue management system market size is projected to experience significant growth over the years, with estimations indicating a climb from USD 2.4 billion in 2023 to approximately USD 5.6 billion by 2032, reflecting a compound annual growth rate (CAGR) of 9.8%. This remarkable growth can be attributed to several factors, including the increasing adoption of technology-driven solutions in the hospitality industry, a growing emphasis on optimizing operational efficiency, and the rising need for data-driven decision-making processes. As the hospitality sector continues to evolve, the role of hotel revenue management systems becomes increasingly critical in ensuring competitive advantage and profitability.

One of the primary growth factors for the hotel revenue management system market is the continuous technological advancements in the hospitality sector. The adoption of artificial intelligence, machine learning algorithms, and big data analytics has revolutionized how hotels manage their revenue streams. These technologies enable hoteliers to predict demand patterns more accurately, optimize pricing strategies, and enhance guest experiences, thereby driving revenue growth. Moreover, the integration of these advanced technologies into revenue management systems allows hotels to tailor their services to meet the ever-changing needs of their guests, ensuring personalized experiences and higher customer satisfaction, which in turn enhances brand loyalty and repeat business.

Another critical driver for the market is the growing competition in the hospitality industry, which necessitates the adoption of sophisticated revenue management systems. With an increasing number of hotels entering the market, hoteliers are under pressure to maximize their revenue and maintain profitability. Revenue management systems provide a strategic approach to revenue optimization by analyzing various factors such as market demand, competitor pricing, and booking patterns. By leveraging these insights, hotels can implement dynamic pricing strategies, optimize room inventory, and improve their sales and marketing efforts. This results in increased occupancy rates, higher average daily rates, and ultimately, enhanced revenue performance.

Furthermore, the rising importance of data-driven decision-making processes in the hospitality sector is also propelling the growth of the hotel revenue management system market. In an era where data is considered the new oil, hotels are increasingly relying on data analytics to gain valuable insights into their operations and customer preferences. Revenue management systems equipped with powerful analytics tools enable hoteliers to make informed decisions based on real-time data, allowing them to identify trends, assess market conditions, and adjust their strategies accordingly. This data-driven approach not only helps hotels stay ahead of the competition but also ensures efficient resource allocation and improved financial performance.

From a regional perspective, North America currently dominates the hotel revenue management system market, owing to the high concentration of luxury and high-end hotel chains in the region. The increasing prevalence of advanced technologies and the presence of key market players contribute to the region's strong market position. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, driven by the rapid expansion of the hospitality sector in countries such as China, India, and Southeast Asian nations. This growth is further fueled by the rising disposable incomes of the middle-class population and the increasing demand for travel and tourism in the region.

Component Analysis

The hotel revenue management system market is primarily segmented by component into software and services. Within this segment, the software component is anticipated to hold a significant share, driven by the increasing demand for sophisticated and efficient management solutions that can optimize hotel operations and boost revenue. Advanced software solutions offer features such as dynamic pricing, demand forecasting, and real-time analytics, which are essential for the effective management of hotel revenues. These software solutions are continuously being enhanced with new capabilities, such as AI-driven insights and automation features, which are attracting more hotel operators to invest in such systems.

On the other hand, the services component within the hotel revenue management system market also plays a crucial role in supporting

The revenue in the 'Hotels' segment of the travel & tourism market worldwide was modeled to be ************** U.S. dollars in 2024. Between 2017 and 2024, the revenue rose by ************* U.S. dollars, though the increase followed an uneven trajectory rather than a consistent upward trend. The revenue will steadily rise by ************** U.S. dollars over the period from 2024 to 2030, reflecting a clear upward trend.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on Hotels.

Taiwan Tourist Hotel: Revenue: Food & Beverage: Taipei data was reported at 1,300,374.125 NTD th in Mar 2018. This records a decrease from the previous number of 1,442,771.702 NTD th for Feb 2018. Taiwan Tourist Hotel: Revenue: Food & Beverage: Taipei data is updated monthly, averaging 983,631.521 NTD th from Jan 2005 (Median) to Mar 2018, with 159 observations. The data reached an all-time high of 1,782,216.972 NTD th in Jan 2017 and a record low of 624,627.216 NTD th in Aug 2005. Taiwan Tourist Hotel: Revenue: Food & Beverage: Taipei data remains active status in CEIC and is reported by Tourism Bureau, Ministry of Transportation and Communications. The data is categorized under Global Database’s Taiwan – Table TW.Q010: Hotel Statistics: Tourist Hotel: Revenue.

Graph and download economic data for Revenue for Hotels (Except Casino Hotels) and Motels, Establishments Subject To Federal Income Tax, Employer Firms (HCHAMRESTF272111) from 2013 to 2022 about casino, hotel, employer firms, revenue, establishments, tax, federal, income, and USA.

Taiwan General Hotel: Revenue data was reported at 7,650,864.734 NTD th in Dec 2017. This records an increase from the previous number of 6,695,094.549 NTD th for Nov 2017. Taiwan General Hotel: Revenue data is updated monthly, averaging 4,666,592.345 NTD th from Jul 2008 (Median) to Dec 2017, with 114 observations. The data reached an all-time high of 7,650,864.734 NTD th in Dec 2017 and a record low of 1,522,672.751 NTD th in Sep 2008. Taiwan General Hotel: Revenue data remains active status in CEIC and is reported by Tourism Bureau, Ministry of Transportation and Communications. The data is categorized under Global Database’s Taiwan – Table TW.Q016: Hotel Statistics: General Hotel: Revenue.

Global hotel company Choice Hotels International Inc. generated a revenue amounting to **** billion U.S. dollars during the 2024 financial year. This shows an increase over the previous year's total of around **** billion U.S. dollars.

Graph and download economic data for Total Revenue for Accommodation, Establishments Subject to Federal Income Tax (REV721TAXABL144QNSA) from Q3 2012 to Q2 2025 about accommodation, revenue, establishments, tax, federal, income, services, and USA.

These data sets contain the information on 6050 hotel bookings between in the year of 2024. Each observation represents a hotel booking. The dataset contains 6,050 hotel transactions with 36 columns, covering various aspects of hotel bookings, customer details, sales performance, and financial metrics.

The Key Features included: Hotel Information: Hotel Name, Region, State, Hotel Type Customer Details: Customer Name, Phone Number, Email, Repeated Guest, Previous Cancellations Booking Information: Reservation Status, Check-in & Check-out Dates, Number of Guests (Adults/Children), Room Type, Duration (Nights) Financial Data: Price Per Room, Gross Sales, Discounts, Net Sales, Payment Method, Deposit Amount & Status, Commission Customer Feedback: Customer Rating, Customer Review Sales Performance: Sales Person, Position

This dataset presents aggregated transformational (non-operational) revenues for Qatar’s hotels and restaurants sector. It includes interest income, insurance claims, asset and raw material sale profits, and dividend earnings. Data is broken down by revenue item and main activity type. Values are reported in thousands of Qatari Riyals (QR).

Tourist Hotel: International: Revenue: Taichung data was reported at 149,239.939 NTD th in Jun 2018. This records an increase from the previous number of 137,459.370 NTD th for May 2018. Tourist Hotel: International: Revenue: Taichung data is updated monthly, averaging 183,928.856 NTD th from Jan 2005 (Median) to Jun 2018, with 162 observations. The data reached an all-time high of 270,734.606 NTD th in Dec 2012 and a record low of 117,480.035 NTD th in Feb 2009. Tourist Hotel: International: Revenue: Taichung data remains active status in CEIC and is reported by Tourism Bureau, Ministry of Transportation and Communications. The data is categorized under Global Database’s Taiwan – Table TW.Q010: Hotel Statistics: Tourist Hotel: Revenue.

In 2023, all hotel enterprises above designated size in China generated a revenue of approximately *** billion yuan, around *** billion yuan more than in the previous year. In the laste decade, the revenue numbers were the lowest in 2020, the first year of the COVID-19 pandemic.

The summary statistics by North American Industry Classification System (NAICS), which include: operating revenue (dollars x 1,000,000), operating expenses (dollars x 1,000,000), salaries wages and benefits (dollars x 1,000,000), and operating profit margin (by percent), of all NAICS under accommodation services (721), annual, for five years of data.

Revenue team in the hospitality domain Domain: Hospitality
Function: Revenue

AtliQ Grands owns multiple five-star hotels across India. They have been in the hospitality industry for the past 20 years. Due to strategic moves from other competitors and ineffective decision-making in management, AtliQ Grands are losing its market share and revenue in the luxury/business hotels category. As a strategic move, the managing director of AtliQ Grands wanted to incorporate “Business and Data Intelligence” to regain their market share and revenue. However, they do not have an in-house data analytics team to provide them with these insights.

Their revenue management team had decided to hire a 3rd party service provider to provide them with insights from their historical data.

Here is the reference of Data Visualization :

https://github.com/SanthoshSivakumar/Hospatility-Domain

In 2024, the largest share of revenue per occupied room for all hotel segments in the United Kingdom was **** revenue, except for regional golf hotels, where **** revenue was exceeded by ***************** revenue. Overall, sales of food and beverages tended to be the second largest source of revenue.

Local Hotel Occupancy Tax (HOT) data has been compiled by municipalities complying with Tax Code Section 351.009 since 2018. In January 2021, counties began reporting their HOT data in accordance with Tax Code Section 352.009.

If local HOT data related to a specific municipality or county is not available in this dataset, it may be because that entity does not levy such a tax or that the local government failed to submit their information to the Comptroller's office within the specified reporting period.

The data reported through the Comptroller's Local HOT Submission Form and available in this dataset is self-reported by submitting municipalities, counties, or third parties on their behalf and has not been independently verified by the Texas Comptroller of Public Accounts. Specific questions or concerns regarding a local government's HOT rate, revenue, allocations and/or submitted webpage links should be directed to that entity.

General questions regarding this spreadsheet, Tax Code Sections 351.009 or 352.009 may be directed to the Comptroller’s Transparency Team, either by email (transparency@cpa.texas.gov) or by phone (844-519-5676).