Hear Your Customers: An Airline Case Study Analysis

In today's business landscape, customer feedback is crucial for organizations looking to improve their services and stay competitive.

Here are the 5 key takeaways from listening to the airline customer :

Data-driven decision-making is crucial in the airline industry for understanding customer needs and expectations.
Social media can be a valuable source of real-time feedback for airlines to improve customer satisfaction and build better relationships.
Collecting customer feedback through surveys and other mechanisms can help airlines identify areas for improvement.
Analyzing customer comments using hierarchical sentiment analysis can help airlines better understand what is important to customers and where to allocate resources.
By improving the customer experience, airlines can increase customer loyalty and revenue, leading to a better bottom line.

This is a guest post by Bill Inmon, a renowned author, lecturer, and consultant in the field of data warehousing and business intelligence. In this article, Bill Inmon analyzes a case study of an airline and explores the importance of listening to the airline customer. This article aims to provide insights into the benefits of a customer-focused approach and offers practical tips for airlines looking to improve their customer experience.

Introduction

The airline industry is complex, with multiple facets to manage and improve upon to satisfy passengers. From baggage handling to flight delays and cancellations, the airline manager has a finite budget and almost infinite demand for attention. So, how does one allocate limited resources to improve the customer satisfaction index of the airline?

A good place to start is by asking customers what they think should be improved. The internet provides a productive starting point for listening to the voice of the customer. There are many sites where people can express their experiences with the airline in the public domain, allowing anyone to see what they have to say.

By understanding what the customer is saying, airline management can deploy their resources where they will do the most good. In this article, we will explore how airlines can empower a better customer experience by using social media, data-driven metrics, real-time feedback

The Importance of Data-Driven Decision-Making in the Airline Industry

Data-driven decision-making has become increasingly essential in the airline industry to help airlines better understand their customers' needs and expectations. The airline industry generates an enormous amount of data from various sources, such as customer data, social media, and customer feedback, which can be used to improve their overall experience.

Through the analysis of customer data, airlines can gain insight into customer behaviors, preferences, and patterns. This information can help airlines understand what customers need and expect, allowing them to tailor their services to better meet these expectations. For instance, airlines can use data to determine which routes are most popular among customers, which amenities are preferred, and which inflight entertainment options are most enjoyed.

Social media platforms have also become valuable sources of customer data for airlines. Airlines can monitor social media platforms to gain an understanding of how customers perceive their brand and services. Social media provides airlines with real-time feedback on customer experiences and opinions, allowing them to respond promptly to issues and improve customer satisfaction. In addition to providing real-time feedback, social media can also help airlines build better customer relationships. By responding promptly to customer inquiries, complaints, or feedback, airlines can show that they value their customers and are committed to improving their experience.

With that, airlines can use customer feedback to understand customer needs and customer expectations. Airlines can collect feedback through surveys, focus groups, and other feedback mechanisms. This data can help airlines identify areas for improvement, such as customer service, onboard amenities, and in-flight experiences.

By using data to better understand customer needs and customer expectations, airlines can create a better customer experience, increase customer loyalty, and build better customer relationships leading to increased revenue and a better bottom line.

Recommended Reading: Where Is Your Customer Data Located?

Airline Case Study Analysis

Late in 2018 Forest Rim Technology (FRT) went to the Internet and plucked about 2,000 comments from the Internet, using several sites. FRT chose two very popular American airlines as the basis for gathering customer comments.

As an example of what a typical comment looked like, the following was taken from the Internet:

Location: United States
Rating:10
Date: 2018-11-20 00:00:00
Description:✅ Trip Verified | I am so thankful to be coming home this week to work at Corporate, and to spend Thanksgiving with family and friends. A big shout out to XXXXXXXXX as I booked my ticket in reverse from Columbus to Tampa leaving today except I’m in Tampa! They were able to get me home today still on the next direct flight and fixed my ticket for the following Tuesday. They even let me keep my incredible price of $199.96 round trip. This is why I fly XXXXXXXXX regularly. It pays to be a loyal flyer!

The comments were gathered and fed into Forest Rim Technology’s textual ETL. From textual ETL a standard database was created. The database was then fed into a tool for visualization.

As part of the processing, the object of each sentence was identified. The object of the sentence was then classified upward for two levels of abstraction. For example, if the comment mentioned the word – “dollars” – the database contained three entries – “dollars”, “price”, and “cost sensitive”. Or if the customer mentioned “hypertension”, the database was loaded with “hypertension”, “illness”, “medical condition”. By organizing and classifying these words in a hierarchically classified manner, it is possible to do an analysis at different levels of perspective.

In addition, the words that operate on the objects being discussed can be examined with regard to their sentiment. For example, the words “…I hated …” led to the conclusion that there was a negative feeling toward the object being discussed. Or the words “…we really adored …” led to the conclusion that there was a positive sentiment toward whatever was being discussed.

In addition to understanding sentiment, there is the possibility of merely finding out what was on the customer’s mind, regardless of sentiment. This is useful to the airline executive in a thousand ways once you know what is important to the customer (in either a positive or a negative sense), you know where to place your dollars to the greatest effect. Stated differently, without knowing what is important to your customer, as an executive you are flying blind. The executive might well spend a lot of resources optimizing something that is of importance to only a few customers. By hearing the voice of the customer, the airline’s executive knows where the customer's “hot spots” are.

So, two important aspects of the study were – a hierarchical analysis of the objects of sentiment and a disclosure as to what subjects are of importance to the customer.

At a High Level

At a high level, the study found that customers attention and sentiment looked like this:

Some of the high-level categories mentioned by the customer were:

Product: An airline flight, baggage handling, frequent flyer club, etc.
People: Stewardesses, pilots, gate agents, etc.
Process: Boarding, seating, service, etc.
Place: Airport, gate, location, etc.
Price: Tickets cost, food cost, etc.
Financial activity: paying for the ticket, credit card, etc.

Not surprisingly the airline flight itself was the most important thing to the passengers who expressed their thoughts. And surprisingly the price of the ticket was not a great concern.

In addition, the positive comments were a little above the negative comments. In general, this indicates a generally happy customer base.

Looking at data at a high level allows the executive to get a clear overview of everything on the customer’s mind and the prioritization of what’s important.

At a Lower Level

In the analysis of what the customer was saying, given that the object of sentiment is organized hierarchically, it is possible to drill down on what was said about each major topic. In this study, the major concern of the customer was the product of the airline itself.

The next figure shows that drill down from the product to the components of the product:

The drill down shows that when examining the product, the number one concern of the customer was on the trip itself. This includes seating, arrival time, and other aspects of the journey. In a distant second place were reservations, then the airline rewards program. And consistent with the high-level analysis is the fact that there were more positive comments than negative comments.

Of course, ANY subject can be drilled upon. This article focuses just on the drill down of the product.

But it is possible to continue the drill-down process to see exactly what people were saying about the trip.

At The Detailed Level

The drill down from the product to its detailed objects displays what the customer is saying down to the detailed level. The detailed level shows the actual words that were found in the customer comments. The next figure shows the detailed drill-down of the product:

The detailed drill down shows that the number subject on the mind of the customer was the flight itself. The flight included every aspect of the flight – boarding, baggage, seating, service, and arrival.

When going down to the detailed level, it is often instructive as to what NOT is found there, as well as what is found there. For example, arrival time is not found in the detailed level. This means that the airline is delivering to its customers on time.

The full case study is available for free by contacting Bill Inmon, at whinmon@msn.com.

The Future of Data in Air Travel

With emerging technologies such as AI and machine learning, the possibilities for improving the airline customer experience are endless.

One way airlines can continue to use data to create a positive experience is by collecting and analyzing more customer data. This can include data on customer preferences, travel habits, and purchasing behavior. By using this data, airlines can better understand their customers' needs and expectations, and tailor their services to meet those needs.

Airlines have the opportunity to use real-time data analysis for a more personalized customer experience. By monitoring data in real time, airlines can respond quickly to any issues that arise during the customer journey, such as flight delays or lost luggage. This can help to minimize the impact on customers and improve their overall experience.

Emerging technologies such as AI and machine learning can also be used to further improve the airline customer experience. For example, AI-powered chatbots can be used to provide customers with personalized assistance, such as booking flights or checking in for a flight. Machine learning algorithms can be used to analyze customer data and provide personalized recommendations for flights, hotels, and other travel services.

AI and machine learning can also be used to optimize airline operations, such as flight scheduling and maintenance. By analyzing data on flight patterns, weather patterns, and maintenance needs, airlines can make more informed decisions that improve efficiency and reduce costs.

Conclusion

In conclusion, data-driven decision-making is crucial for the airline industry to enhance the customer experience, improve operational efficiency, and ultimately increase the bottom line. By leveraging customer data, airlines can gain a better understanding of customer needs and expectations, and use this information to inform their decision-making processes.

Additionally, Metrics and real-time data analysis can help airlines measure the effectiveness of customer experience initiatives and identify areas for improvement. As emerging technologies such as AI and machine learning continue to evolve, airlines can explore new ways to further enhance the customer experience through data-driven insights.

In summary, the airline industry must continue to embrace the power of data-driven decision-making to create a positive experience for customers and drive success. With the help of data integration solutions, airlines can continue to leverage data effectively to meet the evolving needs and expectations of their customers.

Big Data

Hear Your Customers:
An Airline Case Study Analysis

Table of Contents

Introduction

The Importance of Data-Driven Decision-Making in the Airline Industry