

What are hospitality data analytics?
In hospitality, data analytics involves gathering and
analyzing information on customer behavior, booking trends, revenue streams,
and more to make smarter, data-driven decisions for managing your hotel.
By monitoring key metrics, you gain deeper insights into
your guests—understanding their preferences and identifying which offerings
provide the most value. This not only helps increase revenue but also improves
the overall guest experience.
With advancements in AI, these analytics are becoming
more precise and powerful, delivering detailed insights without adding to the
workload for hoteliers.
What data does my hotel have?
Types of Data Your Hotel Tech Collects
Hotel operations are largely digital, meaning data is always being collected. It’s just a matter of understanding what you have and how to use it.
For example, your property management system collects operational data points about the efficiency of your staff, and your revenue management system provides insights into booking trends. If you’re using a guest management system, you’ll know which upsells are the most popular, how satisfied guests are with their stay, and insights into what conversations your staff is having with guests.
A quick guide to the types of hotel data analytics
Data Analytics Terms to Note
- Descriptive
Analytics – Analyzing historical data to
understand trends.
- Diagnostic
Analytics – Explaining why certain trends
happened.
- Predictive
Analytics – Forecasting future trends based on
past data.
- Prescriptive
Analytics – Recommending actions based on
predicted outcomes.
- Real-Time
Analytics – Monitoring live data for immediate
decision-making.
Types of hotel data analytics
Analytics Type |
What It Does |
Hospitality Example |
Descriptive Analytics |
Looks at past data to identify trends. |
A hotel reviews last summer’s occupancy rates to plan
for the upcoming season. |
Diagnostic Analytics |
Explains why something happened. |
A resort discovers a booking spike was caused by a
nearby music festival. |
Predictive Analytics |
Forecasts future trends based on past data. |
A city hotel predicts a post-holiday dip and offers
business traveler discounts. |
Prescriptive Analytics |
Recommends actions based on predicted outcomes. |
A family resort launches a kids-stay-free promo before
spring break to boost bookings. |
Real-Time Analytics |
Monitors live data for instant decision-making. |
A mobile checkout system alerts housekeeping to
prioritize room turnovers. |
Key KPIs for hotel data analytics
Now that you know what data you have, you can focus on
the key performance indicators (KPIs) that will guide your decision-making.
These KPIs provide insights into financial performance, guest satisfaction, and
operational efficiency:
Financial performance KPIs
- Average
Daily Rate (ADR): Measures revenue earned per room
per day.
- Revenue
per Available Room (RevPAR): Assesses a hotel’s
ability to fill rooms at the best rates.
- Total
Revenue per Available Room (TRevPAR): Looks at total
revenue against the number of rooms.
- Gross
Operating Profit per Available Room (GOPPAR):
Examines a hotel’s profit compared to its room count.
Guest satisfaction KPIs
- Online
Reviews: Tracks reviews from sites like
Tripadvisor and Google.
- Net
Promoter Score (NPS): Measures how likely guests are to
recommend your hotel.
- Internal
Ratings: Evaluates guest ratings at different
stages of their stay.
Operational efficiency KPIs
- Front
Desk Revenue Generated: Indicates the
performance of upsell offers.
- Tickets
Cleared/Tasks Completed: Measures department
efficiency.
- Guest
Message Response Time: Tracks how quickly guests’ service
requests are handled.
10 ways hospitality analytics data helps hotels
Once you understand the data and KPIs, you can start
utilizing the insights to optimize operations. Here are ten ways to leverage
analytics in your hotel:
- Optimize
staff scheduling – Use occupancy and booking data to
predict peak periods.
- Enhance
housekeeping efficiency – Streamline schedules
based on guest check-in and check-out times.
- Improve
inventory management – Track supplies and forecast
demand.
- Refine
pricing strategies – Adjust room rates dynamically
using revenue insights.
- Streamline
maintenance operations – Implement predictive maintenance
using equipment performance data.
- Increase
marketing effectiveness – Personalize
campaigns using guest insights.
- Forecast
demand outlook – Use historical booking data to
predict guest volume.
- Drive
sustainable initiatives – Implement
eco-friendly strategies based on energy consumption data.
- Improve
guest experiences – Personalize services based on
guest behavior and booking patterns.
- Create custom upsells – Develop targeted upsell offerings based on guest insights.
Enhance the Guest Experience
- Anticipate
guest preferences: Use a guest management system to
track behaviors and preferences, such as early check-in requests or
special occasions, to provide personalized experiences.
- Customize
add-on offers: Leverage dynamic upselling tools to
personalize offers, such as beach rentals for families or champagne for
couples.
- Resolve
issues with ease: Use real-time analytics to monitor
service response times and address any issues promptly.
Optimize Hotel Operations
- Implement
predictive analytics: Use tools to anticipate demand for
upcoming events and optimize pricing accordingly.
- Effectively
manage maintenance: Prevent equipment failures by
identifying issues before they arise through machine learning and
predictive analytics.
- Create
eco-friendly initiatives: Analyze energy
consumption patterns to introduce paperless registration and reduce
operational waste.
Generate More Revenue
- Understand
booking patterns: Leverage historical booking data
to dynamically adjust room rates during peak seasons or off-peak times.
- Get
granular with marketing: Use data-driven
insights to target specific traveler personas with personalized
promotions.
- Strategically
offer upsells: Tailor upsell options based on guest
preferences and popular add-ons, optimizing revenue potential.
- Strategically
offer upsells: Tailor upsell options based on guest
preferences and popular add-ons, optimizing revenue potential.
Your Security Checklist for Managing Hospitality Data
Hotel Data Security Checklist
On-Site
- Implement
strong security protocols for all data gathered.
- Regularly
update hotel software.
- Conduct
staff training focused on data security.
- Encrypt
sensitive information such as credit card numbers.
- Create
an incident response plan.
Digital/Online
- Ensure
your payment processor is PCI-compliant.
- Use
strong Wi-Fi encryption and firewalls.
- Regularly
back up data.
- Monitor
network traffic to detect suspicious activity.
Operations
- Map
the guest journey to track data access and usage.
- Implement
regular security audits to ensure compliance.
- Communicate
the hotel’s data privacy policies clearly.
Hospitality Analytics: Turning Data into Revenue
Modern hoteliers are utilizing AI, data analytics, and
security protocols to stay ahead of the curve. By leveraging analytics tools,
hotels can not only improve operational efficiency but also enhance guest
experiences and ultimately increase revenue.
The original article was published by Canary
Technologies
To find out more about Canary Technologies, visit their website
