The Hotels Network Unveils Innovative AI Solution to Help Hoteliers Increase Return On Advertising Spend

Submitted Announcement

Powered by AI and hospitality-specific algorithms, this innovative tool makes it possible to optimize retargeting campaigns, effectively bringing high-value users back to the hotel’s website.
1.23.2024

The Hotels Network (THN), a direct growth platform for hotels, has launched Predictive Audiences to boost Return On Advertising Spend (ROAS) for hoteliers. Powered by AI and hospitality-specific algorithms, this innovative tool makes it possible to optimize retargeting campaigns, effectively bringing high-value users back to the hotel’s website. Predictive Audiences is redefining traffic acquisition by empowering hotels to fine-tune retargeting campaign bidding for guests that are more likely to convert or with higher spending, resulting in a CPA of up to 70% lower.

How does Predictive Audiences work?

Based on the observation of hundreds of millions of users across THN’s extensive network of 19,000+ hotels, this technology uses machine learning techniques to find patterns in real-time based on hundreds of variables. Subsequently, it makes predictions on user behavior by considering factors such as past and present user behavior, THN interactions, and external data, offering hoteliers a comprehensive understanding of user engagement.

Predictive Audiences streamlines the process for hoteliers by automatically analyzing and understanding user behavior, thereby creating high-value audience segments from the overall web traffic. These audiences are then used to target users, optimize bidding, and drive higher conversion rates. Importantly, this is achieved without increasing ad spend, as it allows hotels to adjust campaign bidding for guests more likely to convert or with higher spending.

The top-performing algorithms for the optimization of retargeting campaigns are:

  • Purchase Intent: This algorithm empowers hotel marketers to target users based on their probability of booking a room on the hotel’s website.

  • High Spend: The algorithm detects the likelihood of a user opting for higher or lower rates on the hotel’s website, indicating which room category a user is likely to book.

The audience segments can be combined with other behavioral targeting rules based on user interactions with the hotel website, such as stay dates searched or URL variables. Utilizing Predictive Audiences in this way will benefit hoteliers by ultimately boosting ROAS (Return on Ad Spend), lowering CPA (Cost Per Acquisition), and driving higher conversion rates.

“Having achieved considerable success with our initial Predictive Personalization platform, we are excited to broaden its capabilities and the value we provide to hoteliers for their direct channel strategies,” said Juanjo Rodriguez, Founder of The Hotels Network. “With the plug and play implementation of Predictive Audiences, seamlessly connecting to the hotel brand’s Google Analytics account, hoteliers can effortlessly launch retargeting campaigns that immediately and significantly enhance their direct channel performance.

In addition to price comparison, reviews summary and a full suite of personalization options, THN’s Predictive Personalization product harnesses machine learning techniques to predict user behavior and then automatically personalizes both the message and the offer for each user. The company’s latest innovation, BenchDirect, is the first benchmarking product for the direct channel, providing hotels with never-before-seen competitive data that completely changes the rules of the game.

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