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“The use of our own data allowed us to align our marketing campaigns with our business objectives in [our] premium inventory, feeding smart bids with the real value that each lead has on our business, and significantly expanding our sales and profitability.”
RIU Hotels & Resorts is a Spanish hotel chain specializing in high-value, premium vacation experiences. A major focus of their portfolio includes their Caribbean resorts, which primarily offer luxury, “all-inclusive” vacation products and long stays.
Historically, RIU relied on a passive “look to book” strategy to attract US guests to its Caribbean resorts. They waited for potential customers to search for hotel availability—a common top-of-funnel action, but one with a notoriously low conversion rate.
Furthermore, RIU faced a common hurdle for premium brands: data scarcity. Because their high-value, all-inclusive packages naturally result in lower overall transaction volumes, they lacked the robust reservation data required to properly train and optimize machine learning algorithms for digital marketing campaigns. They needed a way to proactively target high-value clients without relying solely on bottom-of-the-funnel conversion data.
To stop waiting to be discovered and start generating demand, RIU partnered with Google and the technology company Making Science. Their proactive strategy focused on automation and first-party data:
Google Discovery Campaigns: RIU launched visually powerful, personalized native ads across multiple Google feeds (including YouTube Home and ‘watch next’, Discover, and Gmail tabs). This allowed them to reach potential customers based on their content consumption habits and interests, rather than waiting for a direct search query.
Leveraging First-Party Data: Using Making Science’s AI technology, Gauss Smart Advertising, RIU integrated its own historical data (such as average reservation prices and lead-to-booking percentages) directly into the Google suite in real time.
Micro-Conversion Modeling: To bypass the lack of final booking data, RIU designed an optimization model based on early-funnel micro-conversions (the initial availability searches). This allowed them to assign an estimated average value to each lead.
Smart Bidding Strategy: By feeding this enriched, predictive data into a beta Smart Bidding strategy (Target ROAS) for their Discovery campaigns, the algorithms could effectively predict the value of conversions and bid appropriately for the highest-value users.
What began as an experiment in the Caribbean transformed into a highly profitable, long-term model that RIU now plans to roll out globally. By effectively combining their own data with targeted ad placements, RIU achieved:
2x overall sales volume.
1.5x increase in their conversion rate.
Over 2x increase in revenue generated from bookings.
2.3x multiplier on their Return on Advertising Spend (ROAS).
