The process can be run either with the objective of driving incremental ancillary revenues (by enabling the resell of the seat), or to reduce operational costs (by betting managing oversold flights). However, a MAJOR tension exists in this entire flow. Airlines want to maximize the probability that sufficient number of passengers volunteer without annoying more passengers than necessary.
The simplest solution would be to blast messages to the entire aircraft, but again this would be highly inefficient and unnecessarily annoy passengers.
Volantio's data science team has been working hard on algorithms to determine the optimal number of passengers to contact in order to achieve the targeted number of acceptances. These algorithms then feed the Yana platform to ensure that we do not "overcontact" the flight manifest.
The graph below shows some of the early insights. For example, an airline needing 1 volunteer should probably contact roughly ~10 passengers on average, whereas an airline needing 4 volunteers would probably need to contact about ~30 passengers.
This is good news for airlines - most of our partners are not looking to move more than a handful of passengers at a time, and knowing this information means that we can be very selective around how many passengers must be contacted.
This avoids unnecessary contact with passengers, improving the overall customer experience.
If you are interested in discussing more about the Yana platform, please do not hesitate to reach out (firstname.lastname@example.org)