3

Can a New Kind of Computing Help Customers Make Better Travel Decisions? From the choice of destination to lodging selection and dining, the travel industry is heavily impacted by recommendations. Before the Internet, most recommendations came from close friends, or recognized travel and dining resources, such as travel writers and guidebooks. For many business and leisure travelers, travel agents served as both booking agents and as an important source of guidance in making travel decisions. Today, online booking has in many cases replaced the travel agent, while online reviewers have become a major influence in buyer decisions. This environment, in providing travelers direct access to such a wide array of information and selfservice booking capabilities, can itself become a source of frustration and indecision if consumers become overwhelmed by too much data and too many choices. In addition, online travel booking as it now stands tends to drive purchasing decisions to the lowest price offered, which in turn can negatively impact travel industry profits and may ultimately lower the quality of the traveler’s experience. But what if the travel industry could influence booking decisions by helping customers make more knowledgeable choices with a higher level of confidence? To be effective such a system must be reliable, robust, and scale to meet demand. And most important, it has to be intelligent—combining recent advances in areas such as machine learning (ML) and natural language processing (NLP) to provide the most relevant travel recommendations. This white paper explores the development of these advanced cognitive computing systems and how they differ from the structured-data systems that came before. We will look at how this new kind of computing is transforming organizations and businesses around the world. And finally, we will look at what better travel recommendations and a more personalized online experience for travelers could mean to the travel business. 3