The panel focused on going beyond the headlines about customer centricity, improved user experience and technology. The attendees discussed how changes to the industry have brought renewed transformation and reinvention, modernizing travel and simplifying retailing. The panel, moderated by Phocuswright’s Senior Technology and Corporate Market Analyst, Norm Rose also included:
- Greg Abbott, Head of Travel, Transportation & Hospitality, DataArt Solutions, Inc.
- Tom Kershaw, Chief Product & Technology Officer, Travelport.
Industry leaders discussed ways to improve user experience and technology.
Topic 1: Anonymous Personalization
We’ve heard for years that the future is in Big Data driven hyper-personalization, but there is also a push towards anonymisation. According to Travelport CPTO Tom Kershaw, personalization should not be overhyped, though critical to the travel and hospitality industry. “It’s historically been characterised by a one-size-fits all, with the same options being presented to everybody based on two parameters: duration and price.” Personalization is much more than customization, it is about optimization. That is what makes speed and efficiency more important right now, putting the right offer in front of the right traveller.
While avoiding to disagree, Greg Abbott cautioned that this sort of personalization remained “way off.” That said, he does see that certain trailblazers in the industry have already pushed towards leveraging technology personalize offers. In terms of ML-driven optimization, Abbott added, “I’m watching other sectors such as retail, finance and so on that are leaps and bounds ahead of travel.”
Topic 2: How Are We Learning Through Machine Learning?
With 80% of travellers taking only one trip a year, there is not enough data around to predict their preference. On top of that, travellers look for so much more than destination, price, or trip duration. They are concerned with carbon emission, Wi-Fi and so much more. “AI and machine learning are the only way to make these predictions.” Chiming in, Abbott went into detail about how cloud technology forms the underlying baseline for using ML and AI tools. That said, cloud implementation does not automatically add these capabilities, but it still is a building block towards achieving them.
Topic 3: Privacy and Self-Sovereign Identity
There is a blockchain-based movement, known as self-sovereign identity, which allows users to retain full control of their online identities and share only what they feel is relevant. For Abbott, the key here is in the seamlessness of the process. Kershaw, on the other hand, believes that self-sovereign identity’s key flaw is that people do not care enough to opt in. “Machines need to do it.”
Topic 4: Unstructured Data
Unstructured data is a real problem. "How can you run a business when your data is a bunch of free-form comments?” Kershaw argues. Standardization and cooperation are necessary to get unstructured data out of the industry and use it in an intelligent way. Nodding in agreement, Abbott adds that not enough has been done over decades to care about this unstructured data.
Topic 5: The Need for Sustainability
ML is the only way to figure out how much users actually care about sustainability. In theory, most people might be interested in it until the time comes to buy the tickets. Only ML can elevate flights that provide a good balance between carbon emissions and price since humans can’t figure this out. It is up to the corporate travel managers to drive sustainability. “We need to put control in the hands of corporate travel managers to wake the results which reflect what their company’s values are about,” said Kershaw.
Topic 6: Dynamic Bundles
Fragmentation is necessary since bundled services create a lot of waste. The same traveller might be on both a leisure and business trip on two different bundles, according to Kershaw. Less optimistically though, Abbott believes, “the industry is a long way off.”
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