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<p><strong>How RaaS is personalizing the digital cruise experience</strong></p>
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<p>In a digital world where artificial intelligence (AI) and algorithmic machine learning are quickly becoming fair game, the keys to success are simultaneously evolving. Claiming the title of ‘cutting-edge’ is no longer about locking down the latest technology—the gates are wide open. The determining factor for getting ahead isn’t about access anymore. It’s about being smart with the tools you have.&nbsp;</p>
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<p>“We’re marking smart recommendations - suggestions that are relevant and make sense to guests,” says Emma Prevolis, from Royal Caribbean’s Recommendations as a Service (RaaS) development team.&nbsp;</p>
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<p>Presenting customers with data-driven recommendations isn’t breaking news. A quick visit online to common purchasing flows will lead to jarring pop-ups of “You May Also Like” suggestions, or “Frequently Bought Together” products sectioned off to a corner. In both scenarios, unsynthesized data is the cause, and low engagement is the result. Through the synthesis, analysis, and refinement of data, RaaS is able to craft recommendations that are actually meaningful to guests.</p>
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<p>What’s the best way to give thoughtful advice to someone? Get to know them. RaaS utilizes a variety of computations to understand the guest, including the current passenger schedule. Which activities has the guest already scheduled or booked in her calendar? Which activities has the guest removed from her calendar or cancelled? Which time blocks are open? Which time blocks are reserved? The algorithm considers all of these questions and develops sensible recommendations, while excluding inappropriate activities that present a schedule conflict or are similar to ones that were removed by the guest.</p>
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<p>The calculations don’t end here. RaaS continues to refine its recommendations by analyzing the guest’s traveling party (a traveling family leads to more family-friendly suggestions while a traveling group of friends leads to more adult-friendly suggestions), the age of the guest (RaaS excludes age-restricted activities), and even previous cruise activity for seasoned voyagers.</p>
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<p>“The final step is a quality check performed by the (human) team. This is very important because we want to offer a meaningful diversity of recommendations,” says Emma.<br></p>
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<p>When human judgment is removed from the equation, it’s likely that the algorithm—no matter how sophisticated--will yield irrelevant or bewildering results.</p>
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<p>“Right now, we’re only on Allure. We have a deployment schedule because each ship is different, and we have to fine-tune RaaS to fit each individual ship.”<br></p>
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<p>Beyond its understanding of guest preferences, the success of RaaS hinges on accounting for ship identities. For example, each ship has a unique set of passengers, ports of call, and activity offerings.<br></p>
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<p>“We’re also using onboard feedback from guests and crew to refine the process before we deploy on future ships,” says Emma.&nbsp;</p>
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<p>RaaS emphasizes the service part of its title. It helps guests maximize their vacations with meaningful recommendations. But most importantly, it ensures that guests never have to worry about missing out on any of the fun.</p>
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