Forward-looking data for hotel forecasting: What's available in 2026
A practical guide to free and paid tools that capture demand signals before they show up in your PMS
The gap between when travelers search and when they book creates an opportunity. Flight searches happen more than four months before departure. Hotel searches happen around three months out. Bookings follow weeks later. Tools that capture these early signals give revenue managers lead time to adjust pricing, distribution, and staffing before demand materializes in the reservation system. Here's what's available today.
Free tools
Google Travel Insights remains the most accessible starting point. Destination Insights shows market-level travel demand by comparing current search volumes against prior years and identifying which source countries are driving interest. Hotel Insights narrows the focus to accommodation searches in a specific area, updated within five days. Neither tool delivers property-level granularity, but both provide a reliable read on whether demand is building or softening before booking pace confirms it.
Google Trends offers a simpler view of search volume over time for any query. Tracking searches for your destination, your property name, or category terms like "boutique hotel [city]" reveals shifts in interest that precede booking activity. The data is directional rather than precise, but the price is right.
Your own website holds signals most properties underutilize. Booking engine analytics can show which dates visitors are searching before they convert or abandon. Tools like The Hotels Network or built-in PMS analytics surface this intent data, revealing demand your historical forecast cannot see.
Market intelligence platforms
Lighthouse (formerly OTA Insight) offers Market Insight, which aggregates search data from OTAs, metasearch engines, GDS queries, flight searches, events, and alternative lodging inventory. The platform translates these signals into demand levels by date, length of stay, and source market. Properties using it report visibility into demand 80 to 145 days before bookings arrive. Lighthouse also provides Rate Insight for competitor pricing and Benchmark Insight for forward-looking performance benchmarking with daily PMS data updates.
Amadeus offers a suite of forward-looking intelligence tools. Demand360 provides on-the-books occupancy data from over 35,000 hotels, updated daily, with 12 months of forward visibility. Agency360 tracks GDS booking activity and agency performance. RevenueStrategy360 combines occupancy forecasts, rate data from 600-plus sources, and alternative accommodation signals into a unified view. The depth depends on selecting an appropriate competitive set.
RateGain's Demand AI focuses on rate intelligence and distribution strategy, processing real-time pricing and OTA data to inform channel mix decisions and demand forecasting. For properties heavily dependent on OTA channels, the granular visibility into rate parity can inform pricing well before competitors adjust.
Benchmarking data
STR reports remain the industry standard for competitive benchmarking. The weekly STAR reports compare your property's occupancy, ADR, and RevPAR against a custom competitive set and broader market segments. While primarily historical, the data establishes whether you're gaining or losing market share. Lighthouse's Benchmark Insight offers similar functionality with real-time PMS integration and forward-looking metrics.
CoStar and Tourism Economics produce macro-level hotel forecasts by market, updated quarterly. These help frame whether local demand trends reflect broader industry patterns or property-specific issues.
Event data
PredictHQ aggregates scheduled and unscheduled events across 19 categories — concerts, sports, conferences, festivals, school holidays, severe weather — from over 30,000 cities. The platform correlates event data with historical demand patterns to quantify expected impact. Research indicates a 10 percent improvement in forecasting accuracy can translate to a 3 percent revenue increase. PredictHQ integrates directly with Lighthouse's Market Insight and several revenue management systems.
For properties without a dedicated event data subscription, manual tracking of major local events remains essential. Conferences shift dates year over year. Festivals relocate. Eighty-five percent of recurring events change timing or location between occurrences, making automated tracking valuable.
Flight and aviation data
OAG provides the most comprehensive aviation dataset, including passenger booking data, forward-looking schedules from 900-plus carriers, and airfare trends with over a decade of history. Hotels in destination markets can track flight capacity and booking patterns to anticipate inbound demand. The data reveals feeder markets, seasonal route changes, and capacity shifts before they affect hotel bookings.
Lighthouse incorporates flight search data into Market Insight. Research by Lighthouse found flight searches occur 145 days before arrival in some markets, hotel searches around 80 days out, and actual bookings around 3 weeks after hotel searches begin. Flight data provides the earliest demand signal available.
Alternative accommodation data
AirDNA tracks performance data from over 10 million Airbnb and Vrbo listings, including occupancy rates, average daily rates, and revenue estimates by market. For properties competing with short-term rentals, this data reveals whether alternative supply is absorbing demand or leaving room for hotels to capture share. Amadeus integrates alternative accommodation data into its business intelligence suite.
Travel intent data
Sojern (acquired by RateGain in late 2025) aggregates travel intent signals from airline and hotel booking partners, providing visibility into where travelers want to go and when they plan to travel. While primarily marketed for advertising targeting, the underlying data reveals demand patterns useful for forecasting. Sojern maintains a free public dashboard showing flight and hotel search trends by destination. The RateGain acquisition creates a combined platform linking travel intent data with pricing intelligence and distribution tools.
Revenue management systems
Modern RMS platforms increasingly incorporate forward-looking data into their pricing algorithms. IDeaS G3 uses machine learning to forecast demand and optimize pricing at the room type level. Duetto's GameChanger combines open pricing methodology with forward-looking demand data and predictive analytics. Atomize uses real-time market signals and competitor pricing to generate automated rate recommendations.
For smaller properties, RoomPriceGenie and PriceLabs offer automated dynamic pricing at accessible price points, typically starting under $100 per month. These systems pull competitor rates and market data to adjust pricing without manual intervention.
Cloudbeds Revenue Intelligence represents a newer approach, using what the company calls causal AI to incorporate external data — competitor rates, OTA rankings, search traffic — alongside internal booking patterns in a unified forecasting framework.
What each signal tells you
Flight search data is the earliest indicator, capturing intent when travelers are still deciding whether to visit a destination. A spike in flight searches to your market suggests demand is forming — though it doesn't guarantee hotel bookings will follow. Hotel search data is more specific, showing when travelers are actively comparing accommodation options. The correlation to actual bookings is tighter, but the lead time is shorter.
Competitor pricing and availability signals reveal how the market expects demand to develop. If your compset raises rates for a future weekend, they likely see something worth investigating. Event data fills gaps that historical patterns miss. Alternative accommodation data shows whether you're competing for a fixed pie or whether the overall market is expanding.
The bottom line for revenue managers: Forward-looking data tools have matured considerably. Free options provide market-level context. Paid platforms offer property-level precision with lead times measured in months rather than days. Revenue management systems increasingly integrate these signals automatically. The right combination depends on your operation's complexity, market volatility, and the value of incremental accuracy. What no longer makes sense is forecasting without any of them.
by Markus Busch, Editor and Publisher of Hospitality.today
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