Hotel demand forecasting
Predicts occupancy and pickup by date and room type from booking pace, seasonality and the events calendar.
Data Analytics · Hospitality
Hospitality Data Analytics for Hotels, Restaurants & Travel
Bring PMS, channel manager, POS and review data into one place. See occupancy, pickup, channel mix and guest sentiment today, and forecast demand before you set the rate.
Overview
Hospitality data analytics that feeds pricing and operations
Hotels and travel businesses produce data with every booking, cover and review, yet most reporting still means spreadsheets exported from five systems. The PMS knows occupancy and ADR. The channel manager knows which OTA sent which booking. The POS knows what sold in the restaurant. Reviews sit on Google and booking sites. Hospitality data analytics joins these sources so owners and managers see the full picture and can act while it still matters.
We build the full stack. Pipelines pull data from your PMS, channel manager, booking engine, POS, CRM and review sources into a secure warehouse. Data is cleaned so that a room night, a booking and a guest mean the same thing in every report. Dashboards show occupancy, ADR, RevPAR, pickup, cancellations, channel mix and commission cost by channel, alongside F&B covers and spend. On top of that, hotel demand forecasting models use booking pace, seasonality and local events to predict demand, so revenue management analytics points to where rates and restrictions should move.
For travel agencies and tour operators, travel analytics shows which packages, routes, seasons and lead sources convert, and where enquiries drop off. Guest review analytics groups comments by theme and sentiment across properties, so you can see whether breakfast, Wi-Fi or check-in is costing you stars. The analytics panel we built for AA JoyLand's WhatsApp chatbot is a smaller version of the same idea, with every conversation and lead in one view. Access controls and data minimisation keep guest data limited to the people who need it.
Use cases
AI Data Analytics use cases in Hospitality
Revenue management analytics
ADR, RevPAR, pace and rate position in one dashboard, with forecasts that support rate decisions.
Channel mix and OTA cost
Shows how many bookings each OTA, your website and your phone line bring in, and what each costs in commission.
Guest review analytics
AI groups reviews by theme and sentiment so you can see what guests praise and what drags scores down.
Travel analytics for agencies
Package, route and season performance, lead conversion and consultant results in one view.
F&B and venue performance
Covers, spend per head, menu performance and event revenue from your POS and reservation systems.
How it works
How it works
- 01Connect your sourcesSecure pipelines pull data from the PMS, channel manager, POS, CRM, review sites and spreadsheets.
- 02Clean and alignBookings, room nights and guest records are de-duplicated and defined the same way across systems.
- 03Build dashboardsRole-based views for owners, revenue managers, operations and sales.
- 04Add forecastsMachine-learning models forecast demand, cancellations and revenue on top of the clean data.
- 05Push insight to peopleDaily pickup reports and alerts land in email, Teams or WhatsApp.
Capabilities
Key features
One hospitality data warehouse
Rooms, F&B, channels, guests and reviews in one trusted source.
Role-based dashboards
Owners, revenue managers and department heads each see the metrics they own, with drill-down.
Forecasting models
Demand, pickup and cancellation forecasts trained on your own history.
Review and sentiment analysis
AI reads reviews in many languages and tags themes and sentiment.
Natural-language questions
Ask "which channel brought the most room nights last month?" and get a straight answer.
Privacy controls
Row-level access, data minimisation and audit logs for guest data.
Integrations
Works with your Hospitality stack
- Oracle OPERA PMS
- Cloudbeds
- Mews
- SiteMinder
- Toast
- Google Business Profile
- Power BI
- Looker Studio
- BigQuery
- PostgreSQL
Using something else? If it has an API, a database or a webhook, we can connect to it.
Outcomes
Benefits for Hospitality teams
Rates set on evidence
Revenue managers price from forecasts and pace, not just last year's numbers.
Lower acquisition cost
Clear channel data shows where commission goes and where direct bookings can grow.
Faster fixes for guest complaints
Recurring review themes surface early, before they pull your scores down.
One set of numbers
Owners, finance and operations work from the same figures across every property.
Our work
Related Work
FAQ
AI Data Analytics for Hospitality: FAQs
What is hospitality data analytics?
It's combining booking, revenue, operations and guest feedback data to understand performance and predict demand. Hotels use it for forecasting, pricing, channel strategy and guest experience.
How does hotel demand forecasting work?
A model learns from your booking history, pace, seasonality, cancellations and local events, then predicts demand for future dates. Revenue managers use the forecast to adjust rates and stay restrictions.
Will this replace our revenue management system?
No. If you already use an RMS, we add the data and views it doesn't cover, such as channel cost, F&B and reviews. If you don't, forecasting dashboards give your team a solid starting point.
Can AI analyse guest reviews automatically?
Yes. AI reads reviews from Google and other sources in many languages, tags each one by theme and sentiment and tracks how scores move over time.
Can we keep using Power BI?
Yes. We can deliver dashboards in Power BI or Looker Studio, or build custom dashboards if you need something more tailored.
How do you protect guest data in analytics?
We bring in only the guest fields the analysis needs, restrict access by role, encrypt data and log access. We design to support GDPR and the UAE and Saudi PDPL, and can host in your region.
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Price tomorrow's rooms with today's data.
Tell us the three numbers you wish you saw every morning. We'll show you the dashboard and forecast that put them in front of you.