Automated Personalization Study

Research MORE IN Research

Inspiring guest services via machine learning

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Questions Answered (and many more…)

  • How can machine learning (ML) trigger relevant responses for individual guests and target groups?
  • How can intent-based technology help to increase conversion?
  • Does personalized pricing yield better vs. target segment pricing?
  • Which technologies (tools/integrations) are required, and which skill sets?
  • What are the new, trust-building factors for guests in a post-pandemic world and how can ML help?
  • What are the most important use cases/services, where ML can assist the process?
  • How can hotels optimize data collection (avoiding data silos) and effectively manage automation?
  • Can new technology be rolled out fast, and how are the integration levels with existing infrastructure?
  • What is the potential of operational cost savings via ML including areas of highest impact?

Key Insights


  • Detailed insights on market specifics, hotel chain needs and industry viewpoints
  • Identification of typical personalization and machine learning operational and other challenges including ideas to overcome these deficiencies
  • Description of today’s strategic issues
  • Recognition of innovative and upcoming solutions
  • List of actionable tasks for serving general, key market requirements
  • Strategic implications by region
  • Extensive promotional activities

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