Two technologies – NDC and artificial intelligence — will play significant roles in shaping the direction of travel distribution next year, according to the Advito 2018 Industry Forecast.
It has long been thought that airlines had widely disparate motives for adopting NDC, the IATA-backed initiative to establish XML as the language of choice for airlines’ communications with trading partners.
Lufthansa is promoting the use of NDC-enabled direct connections with travel agencies; at the same time, it is trying to make those connections more attractive to agencies by imposing a surcharge on all bookings processed by a GDS.
American Airlines, on the other hand, is taking more of a carrot than a stick approach to promoting the use of NDC. It is offering an incentive of $2 per AA-marketed segment booked through an NDC connection.
Either way, the airlines still have an uphill battle ahead of them.
The Advito report enumerates the obstacles: the GDSs’ so-far-unmatched success in aggregating content, and the difficulties that might arise in servicing clients if the airline “owns” the booking.
It is blunt in its criticism of the Lufthansa-led approach:
“By using a surcharge to pass on their costs from the GDS channel, airlines are unfairly penalizing corporate customers, who require the full services provided by a TMC.”
In addition, airlines might be viewed as biting the hand that feeds them:
“Typically corporate customers provide airlines with the most loyal repeat business and the highest yielding fares, coupled with a lower average number of flights in a trip – compared to leisure travelers.”
Artificial intelligence, and in particular machine learning, promises to enable “more accurate and targeted segmentation, allowing suppliers and travel managers to engage with travelers in a more meaningful way, with more relevant offers,” according to the Advito forecast.
So far, much of the fuss has been over chatbots, the most visible manifestation of AI in the industry. But what’s going on behind the scenes could have a greater impact.
Three startups are showing how machine learning might be applied to uncover new opportunities to take the stress out of travel:
FLYR Labs combines historical data and machine learning techniques in its FareKeep and SmartRate tools to predict the likelihood that airline tickets and hotel rooms will be available at lower prices. They come equipped with “wait or buy” recommendations.
FairFly uses machine learning to refine the ticket and fare types shopped in order to improve savings and conversion rates. It works through the GDS to track price variations for individual bookings, factoring in travel policies and preferences and notifies clients if the price, including cancellation fees, falls below a certain threshold.
Flightsayer uses predictive analytics to identify flight delay patterns. Clients can compare alternatives and reschedule to avoid delays.
It also points out a disturbing trend in the hotel industry.
Hotels regularly redefine “standard room” in their booking systems in order to manipulate their inventory and availability.
That means business travelers find they are increasingly unable to find and book rooms at their preferred rate, even when their contract specifies last-room availability on a standard room.
To meet the levels agreed with corporate clients, hotels offer high availability during off-peak periods, but restrict it when demand is high. Often, standard rooms are not available at the preferred rate when travelers really need them.
Advito advised corporate customers to closely monitor this practice.
The Advito Forecast also provides an extensive analysis of growth patterns in every region of the world.
It makes recommendations on how to save money in the specific regions; how to encourage compliance, and how to cope with expected changes in strategies and regulations.