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The Hotels Network’s Predictive Personalization tool identifies each visitor’s intent to book and adjusts messages accordingly. Silken Hotels applied it to focus discounts on those less likely to book while keeping standard rates visible for high-intent visitors. This targeted approach allowed them to increase direct bookings and optimize promotional spending.
Increase Low-Intent Bookings: Silken Hotels aimed to convert low-intent visitors into bookings by displaying targeted offers, focusing efforts on those less likely to complete a booking on their own.
Add Bookings, Preserve ADR: To grow direct bookings without compromising their average daily rate, Silken Hotels provided discounts only to those visitors who showed low booking intent, keeping high-value guests at standard rates.
Reduce Costs: By selectively offering discounts to guests needing extra motivation, Silken Hotels managed to cut down on promotional expenses while effectively boosting conversions.
"Predictive Personalization has proven to be the perfect tool to help us achieve increased direct bookings without increasing our spend along with it."
Itziar Poza
Revenue Management and Global Distribution at Silken Hotels
"Predictive Personalization has proven to be the perfect tool to help us achieve increased direct bookings without increasing our spend along with it."
Revenue Management and Global Distribution at Silken Hotels Itziar Poza said, about their decision: "The machine learning algorithms give us the confidence that we’re communicating the ideal offer to the correct visitor at the perfect moment in the booking process."
In just one year, 6% of all bookings across the chain were generated directly from clicks on Predictive Personalization messages.
By targeting discounts specifically to low-intent visitors, Silken Hotels effectively reduced promotional costs, ensuring more efficient use of their marketing budget.
Predictive Personalization influenced a total of 10% of bookings chain-wide.
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