Optimizing Customer Satisfaction With Machine Learning
Analyzing an airline satisfaction dataset.
Flying can be a hassle. Long lines, uncomfortable seats, bad food… the list goes on. Now, mandates on mask-wearing, physical distancing, PCR tests, temperature checks, health forms, and more make the whole process a dizzying ordeal.
This is bad news for airlines. Airline revenue is already way down, and traffic isn’t expected to fully recover until 2024. Flying is more stressful than ever. Given this, airlines need to optimize customer satisfaction to recover faster, and emerge successfully out of this downturn.
I analyzed an airline passenger satisfaction dataset using the predictive insights tool Apteo to find what factors impact flyer satisfaction the most.
Inflight Wi-Fi is King
Studies show that in-flight WiFi is a major driver of airline loyalty. This is reflected in our dataset as well, as inflight wifi service is the biggest predictor of satisfaction.
Among those who rated the WiFi service as 1 out of 5, less than one-third were satisfied with the airline. Among…
