Key Takeaways
- 10.0% of all hospitality businesses reported using a revenue management system, according to a survey of US hotels and motels (2022).
- 18.0% of hotel revenue in the US is attributed to online travel agencies (OTAs), reflecting OTA share of industry bookings (2023).
- 48% of travelers used online booking platforms in 2023, demonstrating the importance of digital distribution sources executives monitor.
- 7.1% projected average annual growth rate for the global hospitality software market from 2024 to 2030 (industry forecast).
- $6.8 billion global market size for hotel revenue management software in 2023 (vendor market sizing).
- $1.9 billion global market size for hospitality cybersecurity services in 2024 (market research estimate).
- 12.2 million Americans were employed in accommodation and food services in 2023 (BLS annual average).
- $25.64 median hourly earnings for accommodation and food services workers in May 2023 (BLS OEWS).
- 2.5x increase in use of labor-management software among hospitality operators from 2020 to 2023 (vendor survey).
- 70% of hotel chains have integrated digital guest messaging with at least one other system (2023 industry study).
- 60% of hotels use online reputation management tools (2021 survey).
- 67% of hotels report using data analytics platforms for marketing performance measurement (2022 survey).
- 34% of breach incidents in 2023 were attributed to external actors (reporting year 2023).
- 62% of US consumers say they trust brands that use personalization responsibly (US consumer survey, 2023).
- 73% of travelers used a mobile device to research travel in 2023 (traveler behavior share).
Hospitality leaders rely on digital distribution, revenue systems, and trusted data to stay competitive.
Related reading
Industry Trends
Industry Trends Interpretation
More related reading
Market Size
Market Size Interpretation
More related reading
Labor & Skills
Labor & Skills Interpretation
User Adoption
User Adoption Interpretation
More related reading
Cybersecurity Risk
Cybersecurity Risk Interpretation
More related reading
Customer Behavior
Customer Behavior Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Kevin O'Brien. (2026, February 13). Where Do Hospitality Executives Get Industry Statistics. Gitnux. https://gitnux.org/where-do-hospitality-executives-get-industry-statistics
Kevin O'Brien. "Where Do Hospitality Executives Get Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/where-do-hospitality-executives-get-industry-statistics.
Kevin O'Brien. 2026. "Where Do Hospitality Executives Get Industry Statistics." Gitnux. https://gitnux.org/where-do-hospitality-executives-get-industry-statistics.
References
- 1strategyanalytics.com/access-content/reports/hospitality-revenue-management-market-2022
- 8strategyanalytics.com/access-content/reports/hospitality-crm-market-2023
- 29strategyanalytics.com/strategy-analytics-blog/2024/06/online-travel-platform-usage
- 2phocuswright.com/Webinars/2023-OTA-Share-of-US-Lodging
- 24phocuswright.com/Research/Marketing-Analytics-Data-Platforms-2022
- 27phocuswright.com/white-papers/mobile-booking-report-2024
- 3iea.org/reports/global-travel-and-tourism-statistics-2023/online-booking-platform-use
- 4str.com/research/direct-channel-share-2023
- 5fortunebusinessinsights.com/hospitality-management-system-market-104789
- 16fortunebusinessinsights.com/hotel-revenue-management-software-market-103576
- 6researchandmarkets.com/reports/5401232/hotel-revenue-management-market-size
- 7bccresearch.com/market-research/information-technology/hospitality-cybersecurity-market-533637
- 9reportlinker.com/p06429542-Restaurant-Online-Ordering-Market.html
- 10alliedmarketresearch.com/online-travel-agency-market
- 15alliedmarketresearch.com/hospitality-cybersecurity-market
- 11wttc.org/research/economic-impact
- 12hospitalitynet.org/news/4101000.html
- 30hospitalitynet.org/news/4101650.html
- 13data.census.gov/table/AB0101?g=0100000US&y=2022
- 14bls.gov/oes/current/naics_721100.htm
- 18bls.gov/oes/current/naics.htm
- 19bls.gov/oes/current/naics3_722.htm
- 17gartner.com/en/information-technology/it-spending-by-industry
- 20g2.com/categories/waitlist-and-reservation-management?stats=labour
- 21hotelmanagement.net/operations/2021-hotel-executive-survey-revenue-management-training
- 22jdpower.com/business/press-releases/2023-hotel-digital-messaging-adoption
- 23tripadvisor.com/press/industry-reputation-management-2021
- 28tripadvisor.com/PressCenter-c2-?something
- 25verizon.com/business/resources/reports/dbir/
- 26cdt.org/insights/consumer-trust-and-privacy-2023-study






