What Do Airline Passengers Really Complain About? The Data Was Already Online

What Do Airline Passengers Really Complain About? The Data Was Already Online

G. Monray on how 1,222 online reviews can reveal what customers really think about airlines

For decades, companies have relied on surveys, focus groups and customer interviews to understand what consumers want.

But the digital economy changed the equation. Customers began voluntarily publishing thousands of opinions online—often in considerably more detail than they would provide in a conventional questionnaire.

In 2017, G. Monray, together with David Rimbo, Rocky Nagoya and Ikin Solihin, explored how this new source of consumer information could be analyzed systematically.

Their study, Perceptions of Consumers in the Airline Industry Using a Qualitative Data Analysis Methodology: An Applied Research under an International Orientation, published in International Business Research, examined 1,222 written passenger reviews relating to two airlines in Asia.

The research used Qualitative Data Analysis (QDA) and text-statistical techniques to identify recurring themes and the most common complaints expressed by passengers.

The broader question was increasingly relevant to any consumer-facing company:

What can businesses learn when customers speak freely about them online?

INTERVIEW

Q: Why did you decide to study airline passengers' online reviews?

G. Monray: Because the relationship between companies and consumers was changing rapidly. By 2017, customers were no longer simply responding to surveys created by companies. They were creating their own content. They were writing reviews, describing experiences and sharing their frustrations publicly. From a research perspective, that creates an enormous amount of qualitative information. The question was how to transform that information into something that could actually support managerial decision-making.

Q: So the internet effectively became your research database?

G. Monray: In a sense, yes. The reviews were already there. Customers had voluntarily described their experiences in their own words. The challenge was not collecting another questionnaire. It was developing a systematic methodology for analyzing what those customers had already said. That is where Qualitative Data Analysis becomes particularly useful.

Q: How large was the dataset?

G. Monray: We analyzed 1,222 written reviews concerning two airlines in Asia. For a qualitative study, that is a substantial volume of textual information. It allowed us to move beyond individual anecdotes and look for recurring patterns across a large number of customer experiences.

Q: What does QDA allow you to do with thousands of customer comments?

G. Monray: It allows you to transform unstructured text into structured information. You identify recurring concepts, create codes, classify statements and examine relationships between different themes. For example, if hundreds of passengers complain about different things, you can determine whether those complaints are actually manifestations of a smaller number of underlying categories. The objective is to move from: "Here are thousands of comments." to: "Here are the principal patterns contained within those comments."

Q: What did the analysis reveal?

G. Monray: Several recurring areas of dissatisfaction emerged. The study identified food and beverages, in-flight entertainment and seat quality as particularly important concerns during the service encounter. These findings were also consistent with other quantitative research cited in the article. What is interesting is that customers may not necessarily express these issues using the same terminology. One passenger talks about uncomfortable seating. Another complains about insufficient legroom. Another may describe the cabin experience as uncomfortable. Qualitative analysis allows you to identify the common theme behind those different expressions.

Q: Why is that more useful than simply counting complaints?

G. Monray. Because counting alone can hide meaning. Imagine that 500 passengers mention "seats." That tells you something. But qualitative analysis can tell you how passengers are talking about seats, why they are dissatisfied and what other issues appear alongside the complaint. The text contains context. And context is extremely valuable in customer research.

Q: Does this mean online reviews can replace traditional surveys?

G. Monray. Not necessarily. I would see them as complementary. Surveys allow researchers to ask precisely defined questions and generate standardized responses. Online reviews are different. The customer decides what to talk about. That means the researcher can discover issues that were never included in the original questionnaire. The two approaches answer different questions.

Q: Is there an advantage in allowing customers to choose what they want to discuss?

G. Monray. Absolutely. A questionnaire reflects the researcher's framework. A spontaneous review reflects the customer's framework.

That distinction is important. If you ask a customer whether they are satisfied with ten predetermined aspects of a service, you already decide what matters. When customers write freely, they can introduce issues that the researcher did not anticipate. That can generate new hypotheses.

Q: But aren't online reviews subjective?

G. Monray. Of course. And that is precisely why methodological discipline is necessary. A review represents an individual perception.

It should not automatically be interpreted as an objective description of reality. But when you analyze thousands of reviews systematically, individual subjectivity becomes part of a broader dataset of consumer perceptions. The research question is not necessarily: "Is every review factually correct?" It is: "What patterns appear in the way customers perceive and describe their experiences?"

Q: That distinction seems particularly important in service industries.

G. Monray:, It is fundamental. Services are experienced. A passenger does not simply purchase transportation from point A to point B. The passenger experiences check-in, boarding, seating, cabin service, food, entertainment, staff interaction and the overall journey. Those experiences generate perceptions. And perceptions influence customer behavior.

Q: What can airline executives learn from this type of research?

G. Monray. They can learn that customer feedback contains much more information than a satisfaction score. A score of 7.2 out of 10 tells you something. But thousands of customer comments can tell you why the score is 7.2. That distinction is strategically important. If you only know that customers are dissatisfied, you have a problem. If you know why they are dissatisfied, you have the beginning of a management response.

Q: Could the same methodology be applied to other industries?

G. Monray. Definitely. That was one of the broader implications of the research. The methodology can be applied to hotels, restaurants, banks, universities, hospitals, telecommunications companies, retailers or virtually any organization that receives substantial amounts of customer feedback.

Today, the possibilities are even greater because companies have access to social-media comments, app reviews, complaint databases, emails, chat transcripts and other forms of customer-generated text.

Q: Would you describe this as an early form of sentiment analysis?

G. Monray. There is a clear connection. Modern sentiment analysis and natural-language-processing systems can process enormous quantities of text. But the fundamental research question remains similar: What are customers actually saying, and what does that tell us about their experience? In 2017, the methodology relied heavily on qualitative coding and text-statistical analysis.

Today, computational tools can accelerate the process enormously. But automation does not eliminate the need for interpretation.

Q: Why not simply let artificial intelligence analyze everything?

G. Monray. Because identifying words is not the same as understanding meaning. Suppose a passenger writes: "The entertainment system was fantastic—if you enjoy watching the same movie for ten hours." A purely mechanical system could misinterpret the first part of that sentence. Human interpretation remains important. The best approach is probably a combination of computational processing and human analytical judgment.

Q: Did the international dimension matter?

G. Monray. Yes. The research was explicitly conducted under an international orientation and examined two airlines in Asia. Airline customers come from different national, cultural and linguistic backgrounds. That makes consumer perception particularly interesting. What one customer considers a serious service failure may not be perceived in exactly the same way by another customer.

International business research therefore needs to pay attention not only to what consumers say but also to the context in which those perceptions are formed.

Q: What was the most important lesson for managers?

G. Monray. That customers are already generating enormous amounts of market intelligence. Companies don't always need to ask customers another question. Sometimes they need to listen more carefully to the answers customers are already giving. The information may be sitting publicly online. The challenge is turning that information into structured knowledge.

Q: How would you conduct the research today?

G. Monray. I would probably use a mixed methodology. First, computational tools could process millions of reviews.

Then machine-learning techniques could identify clusters and recurring themes. After that, qualitative researchers could examine representative texts and validate the meaning of those categories. Finally, the results could be connected with actual business indicators such as customer retention, revenue per passenger, complaints, ratings or repeat purchases.

That would create a much richer connection between customer language and business performance.

Q: So the real value isn't simply knowing what customers complain about?

G. Monray. Exactly. The ultimate objective is not to produce a list of complaints. It is to convert customer perceptions into managerial intelligence. A complaint is data. A pattern of complaints is information. Understanding why that pattern exists is knowledge. And using that knowledge to improve the business is strategy.

Q: What would you say to a CEO looking at thousands of online reviews today?

G. Monray. Don't ask only: "What is our average rating?" Ask: "What are customers repeatedly telling us?" Then ask: "Which of those issues can we actually change?" That is where customer analytics becomes strategic.

The 2017 study by Rimbo, Nagoya, Solihin and G. Monray appeared in International Business Research, Volume 10, Issue 5, pages 22–28. It was received in February 2017, accepted in March and published online on March 30, 2017.

The paper sits within a broader research trajectory in G. Monray's work on consumer perceptions, complaints and qualitative data analysis. His preceding research examined consumer perceptions in the financial industry using QDA, while the airline study extended the methodology into an international service-industry context.

That progression is significant.

The research moves from asking customers directly about their experiences toward analyzing the enormous amount of information customers generate spontaneously.

In today's digital economy, that distinction has become even more important.

Customers are not only consumers anymore. They are also producers of data.

The companies that can systematically interpret that data have an additional source of competitive intelligence.

And perhaps the most important lesson from the research is simple:

Don't just measure what customers think. Learn