Airline customer care

Airlines care about their customers and their custom, but this use case shows how Decision Server Insights can take customer care to new heights.

Mary is going to be late for her next flight due to a late arrival at the airport from a connecting flight. The airline developed a solution to enroll Mary into a program where her whereabouts are tracked, and the airline is notified if she is likely to miss her connecting flight.

The solution models all of the airline flights and the passengers that are enrolled in the program, and uses business rules, predictive models, and analytics to determine the best action to take as a result of an event. The solution tracks all of the airlines aircraft in the air and relevant events at the airports at which the airline operates. It tracks every passenger in the program to optimize the relationship with these customers. It knows when Mary’s flights take off and when they land, and the time she spends at an airport between flights.

From the moment the airline’s system registers Mary as a passenger (passenger entity) and her flight takes off (flight event), Mary’s location is tracked. When the arrival time of her incoming flight is changed, an event arrives and informs the system that Mary is going to arrive at gate G4 at 4:53 p.m.. This arrival time leaves insufficient time for her to get to her next departure gate, so the solution uses business rules to update the number of expected late connections.

The delayed arrival of Mary’s flight (an event) triggers a call to a predictive model to calculate the estimated time of arrival for Mary at her next departure gate. The model uses historical data from similar situations in the airline’s data warehouse to compute the time Mary is likely to get to the new gate.

• The locations of the arrival and departure gates to calculate the distance between the two.
• The origin of the incoming flight, which might determine whether Mary needs to go through customs.
• The time of day.

An agent within the solution sends an action alert to the gate agent. The action is based on a set of rules that determines the connecting flight is the last one out to a regional airport that day, and Mary can be accommodated by a 15-minute delay caused by airport congestion. The agent sends a message to the flight crew, and sends a new event that updates the new departure time.

Mary is a frequent flyer with this airline and missed two connection flights this month already. Another agent in the solution determines that Mary receives an Elite Lounge coupon to show gratitude for her loyalty, and to compensate her for the inconvenience of the delayed flights.

The airline also has a service that is named Road Warriors, which allows subscribers to meet up with like minded people at airports during layovers. Mary works for IBM®, and knows many other IBM employees who fly with the airline as frequently as she does. Last week, Mary had a 3 hour layover while she waited for her next flight in Philadelphia. She used the Road Warrior App on her smartphone to inform other subscribers she was at the airport. The Road Warrior App sent a message to all of the members of the same group with overlapping overlays to inform them that Mary was there. Mary received a message with a list of their names, and arranged to meet up with an old friend she knew from Littleton, Massachusetts.

Even though Mary is a loyal customer, this airline is using Decision Server Insights to demonstrate that the company appreciates her custom and they want Mary and IBM to continue to fly with them.