Finavia

Transferring between flights can be dreadful – running through crowds to a far-away gate only to miss your departure; then spending the night alone in a grimy airport hotel, waiting for that next red-eye out of town – yet the experience is far from it at Helsinki Airport, the pleasantly efficient transport hub of the Finnish capital region.

Finavia, which runs all of Finland’s 21 airports, including the Helsinki flagship, commissioned Reaktor to harness the airport's abundant passenger data. The result – a state-of-the-art contextual engine fueled by artificial intelligence – marks the evolution of Helsinki Airport into the world’s smartest transportation hub.

The contextual engine ensures the smooth transfer of passengers from A to Z, or any gate or terminal to an other, and makes sense as Helsinki Airport grows at an ever-quickening pace.

Just look at the numbers: Connecting passengers are now a major business focus for Helsinki Airport, one that has in recent years become a transfer hub – smack right between Europe and Asia. Most of the passenger flow in Helsinki is en route someplace else, and there are more visitors passing through the airport than ever before.

This past year, traffic reached a record 18.9 million passengers, and it is on track to surpass the 20 million mark in 2018. That will be almost four times the population of Finland. It is important for the airport’s business that transferring passengers are able to move through with ease and that their experience at the airport is a positive one.

This is the way to smoothly transfer big masses of people in a relatively small space. The personalized guidance from the contextual engine means that the airport never feels too crowded, slow, or inefficient. Helsinki Airport continues to be voted the best airport of its size in the world.

The vision for the customer journey at Helsinki Airport is one that is optimized to ensure passengers have all the information they need before they even think to ask for it.

The data for the contextual engine comes from flight schedules, simulation, and boarding passes that are scanned as transfer flyers arrive in the airport. That grouped data reveals surprisingly much about the travellers without breaching any single passenger’s privacy.

The engine is data-mining at its most helpful: it can tell where the most recent planes have arrived from and where their passengers are going next, but also what nationality those passengers are, whether they’re flying business class or economy, and even what their native tongue might be.

The AI machine then uses and analyses that information to show those passengers immediately relevant information to their needs as they move through the airport.

• Product roadmapping
• User research
• Design
• Development