“What is important is to make relevant recommendations based on the customers’ history that is stored and interpreted by the software. The self-learning engine takes into consideration the guest profile, nationality, gender, age, if they travel with extended family, friends, where they are sailing; it looks at many data points before making recommendations.”
For the supply chain, the AI engine can find correlations between cruise lengths, weather, deployment and special occasions, according to Lindthaler.
“Our current system can handle all of this,” he said, “but requires more data maintenance and also experienced provision masters. With the growth of the industry, there is a shortage of experienced crew, however, and this is where the technology can help. Sailing seven days out of Miami, it is not very difficult, but for global deployment, accurate forecasting becomes more of a challenge.”
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