MARKETING

How Silken Hotels Leveraged Machine Learning to Boost Direct Bookings & ADR

Verified case study Hotel Tech Report has reached out to hoteliers at Silken Hotels to verify this case study.
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Silken Hotels strategically utilized The Hotels Network’s Predictive Personalization to drive growth in direct bookings and revenue. By directing tailored offers toward low-intent visitors, they increased profitability, optimized promotional spending, and maintained a high ADR for high-value guests.
Why it matters: Silken Hotels used Predictive Personalization to reach only low-intent guests with offers, increasing revenue without overspending—a smart, efficient strategy for today’s industry.
  • 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.

Top 3 Core Objectives: Facing the challenge of maximizing direct bookings without over-discounting, Silken Hotels sought a way to identify which visitors would benefit from targeted offers. Their goal was to increase conversions among low-intent users while maintaining profitable rates for high-value guests.
  • 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.

The Hotels Network

Growth for your Hotel's Direct Channel

Innovators Mentioned

Silken Hotels
The Hotels Network
Itziar Poza
Hotel Tech Report reached out to Itziar Poza who verified this case study.

Revenue Management and Global Distribution at Silken Hotels

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."

Itziar Poza

Revenue Management and Global Distribution at Silken Hotels

👍 Revenue Management and Global Distribution at Silken Hotels Itziar Poza said that Silken Hotels saw Predictive Personalization as a game-changer for increasing direct bookings by delivering targeted offers precisely when needed, without raising promotional costs.:
  • "Predictive Personalization has proven to be the perfect tool to help us achieve increased direct bookings without increasing our spend along with it."

⚖️ The selection process: During their research process, Itziar Poza evaluated The Hotels Network's product differentiators, customer support, and holistic value as a strategic partner and ultimately decided that The Hotels Network was the best fit solution:
  • 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."

📈 The results: In one year, Predictive Personalization led to a 5% increase in additional revenue for Silken Hotels, driving strong growth in both revenue and bookings. Personalized messages contributed significantly to total bookings and boosted conversions across the chain.
  • 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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