True engagement begins with understanding people. Every traveler arrives on a hotel website with their own story, preferences, and hopes for their stay. Predictive Personalization acts on that story by recognizing what each guest needs and responding in a way that feels relevant and personal. It offers travelers the right encouragement at just the right moment, whether that means a thoughtful offer, a reassuring message, or an inspiring idea for their trip.
For hoteliers, it offers a strategic advantage by using incentives only when they matter. Not every website visitor needs a discount, and many are ready to book as they are. By understanding each visitor’s level of intent, hotels can reserve offers only for the visitors who truly need them to convert, protecting rate integrity while still encouraging more bookings where it matters most.
The result is an experience that feels intuitive and well-timed, where travelers are more open to being guided toward choices that benefit both their stay and the hotel’s revenue goals.
Now, let’s take a closer look at how this works behind the scenes and explore the technology that makes such meaningful personalization possible.
Predictive Personalization is an advanced form of website personalization that uses AI to anticipate what each visitor is likely to do next. Instead of relying solely on behavioral segmentation, it evaluates hundreds of behavioral and contextual signals to assign each visitor a dynamic value score. This score reflects their likelihood to book, upgrade, or leave the site, allowing hotels to deliver the most relevant message or offer at the right time.
Predictive Personalization recognizes that every traveler is unique. THN’s technology learns from hundreds of millions of user sessions across its global network of hotels. This proprietary data, combined with real-time behavioral signals, allows the system to identify booking intent, predict spend potential, and understand travel flexibility with great accuracy to enable true one-to-one personalization.
Representation of Identifying Unique Visitors
At the heart of Predictive Personalization is a suite of advanced algorithms that have already proven highly effective in helping hotels understand and influence guest behavior. These include the Intent, Spend, Flexibility in Destination, and Flexibility in Dates algorithms, each designed to predict a different factor of decision-making.
- Intent Algorithm – Identifies how likely a visitor is to book.
- Spend Algorithm – Predicts a visitor’s potential booking value.
- Flexibility in Destination Algorithm – Detects when a visitor is open to considering other cities or destinations.
- Flexibility in Dates Algorithm – Determines when a visitor is willing to adjust their travel dates.
Hotels can activate the models that best match their goals, whether they want to encourage more bookings, drive higher value stays, or guide guests toward alternative dates.
Building on the success of these proven models, THN is now introducing the Length of Stay (LoS) algorithm, which adds a new layer of intelligence by predicting if they are likely to extend it beyond their search and tailoring offers to maximize both revenue and guest satisfaction.
The newest addition to THN’s Predictive Personalization suite, the Length of Stay (LoS) algorithm, tackles the length of stay challenges by helping hotels identify when a visitor is likely to extend their stay beyond their initial search and when they may be open to the right incentive.
It anticipates whether a visitor is leaning toward a shorter or longer trip and identifies when someone may be open to adding extra nights, allowing hotels to craft offers that increase LoS and direct revenue. For guests predicted to book shorter stays, the system can trigger personalized incentives that encourage them to extend their visit. Campaigns such as “Book 3 nights, pay for 2” or “Get complimentary breakfast when you add an extra night” can turn a two-night getaway into a three-night booking.
Example of a campaign aiming to increase length of stay offering a discount
For guests who are already more likely to extend their stay, hotels can instead highlight premium experiences or upsells that enhance value without discounting unnecessarily.
Example of message to Increase Length of Stay without offering a discount
Predictive Personalization helps hotels turn intelligence into measurable outcomes. By understanding intent, spend potential, flexibility, and now stay duration, hotels can tailor their communication to match each guest’s needs and mindset. These insights allow teams to focus their efforts where they matter most, improving conversion rates and revenue across the direct channel, while protecting rate integrity.
Each algorithm helps hotels connect with travelers in a more personal and purposeful way, but together they create a powerful system that transforms the booking journey. The new Length of Stay algorithm builds on this foundation, helping hotels anticipate how long visitors plan to stay and tailor offers that encourage longer, more valuable bookings.
Learn more about how Predictive Personalization and the new LoS algorithm can help you grow your direct revenue.
