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ANALYZING SOCIAL MEDIA BIG DATA IN THE AVIATION
INDUSTRY:
A CASE STUDY OF
KLM ROYAL DUTCH AIRLINES
A study submitted in partial fulfilment
of the requirements for the degree of
Information Systems (Professional Enhancement)
at
THE UNIVERSITY OF SHEFFIELD
by
AYOBAMI OLUWATONI ABRAHAM
September 2016
i
Abstract Background. This dissertation explains the impact of social media on airlines, it
focuses on KLM Royal Dutch Airlines, KLM has been reported as number one for social
media in the world. Based on this finding, KLM was chosen to be analyzed in order to
get a glimpse of how they interact with their customers with the use of social media,
KLM’s Twitter was chosen to be focused upon because data can easily be gathered
from it.
Aims. This research starts by explaining the importance of social media/big data and
then further explains its usefulness in the aviation industry, it then introduces the
research questions and objectives. The research is based on answering the questions
that have been specified and the objectives explains what will be achieved in answering
these questions. This research has two questions, first is what achievements KLM has
made by using its social media strategy particularly Twitter, and second is what
activities are enabled from KLMs interaction with its customer based on contents posted
on its Twitter platform.
Literature Review. The next chapter reviews some literature to show KLM’s social
media strategy success, it explains some of KLMs social media strategies and cites
ways in which they have influenced their customers.
Methods. The next chapter first explains why Twitter has been chosen for this research
and then further explains the methodology that would be used in analyzing data that will
be collected from KLM’s Twitter page, it further explains how the data will be collected
and analyzed, and then explains the selected research methods, finally, it explains why
the selected methodologies have been chosen. The methodology that has been
selected is the exploratory case study research, using a qualitative method.
Results. The next chapter analysis the data that was collected from KLM’s Twitter page
applying the selected procedures and methodologies highlighted in the previous
chapters. Analysis is done on both tweets made by KLM to its customers and tweets
made by KLM customers to KLM airline, these analyses show various angles that KLM
uses in interacting with its customers using tweeter and also shows its customers
interactions with them.
ii
Conclusions. Finally, this research discusses the findings from research done and
makes relevant recommendations based on the findings.
iii
Contents Abstract ........................................................................................................................................... i
List of Figures .................................................................................................................................. v
ACKNOWLEDGEMENT .................................................................................................................... vi
CHAPTER ONE: INTRODUCTION AND CONTEXT .................................................................. 1
1.1 Background .................................................................................................................... 1
1.1.1 Social media big data. ............................................................................................ 3
1.1.2 Airlines and Social Media ....................................................................................... 4
1.2 Significance of the Study ................................................................................................ 5
1.3 Research Aim and Objectives ......................................................................................... 5
1.3.1 Aim ......................................................................................................................... 5
1.3.2 Research Question ................................................................................................. 6
1.3.3 Research Objectives ............................................................................................... 6
1.4 Dissertation Structure .................................................................................................... 6
CHAPTER TWO:LITERATURE REVIEW ............................................................................................. 8
2.1 Introduction ................................................................................................................... 8
2.1.1 KLM’s Social media efforts ................................................................................... 10
2.2 The Theoretical Framework ......................................................................................... 11
2.2.1 Reputation ........................................................................................................... 11
2.2.2 Service .................................................................................................................. 11
2.2.3 Commerce ............................................................................................................ 12
2.3 KLM and Twitter ........................................................................................................... 13
2.4 Summary ...................................................................................................................... 14
CHAPTERE THREE: METHODOLOGY ............................................................................................. 15
3.1 Research Design ........................................................................................................... 15
3.2 Sampling Strategy ........................................................................................................ 15
3.3 Methodology Description ............................................................................................ 17
3.3.1 Exploratory research ............................................................................................ 17
3.3.2 Case study approach ............................................................................................ 17
3.4 Research Methods ....................................................................................................... 18
3.5 Data Analysis Methods ................................................................................................ 18
3.5.1 Content Analysis .................................................................................................. 18
3.5.2 Thematic Coding .................................................................................................. 19
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3.5.3 Inter Coder Reliability .......................................................................................... 19
3.6 Justification of the Methodology. ................................................................................ 20
3.7 Ethical Issues. ............................................................................................................... 20
CHAPTER FOUR: RESULTS AND FINDINGS ................................................................................... 22
4.1 Introduction ................................................................................................................. 22
4.2 Findings from Content Analysis. .................................................................................. 23
4.2.1 Findings from the KLM Code frames. ................................................................... 23
4.3 Conclusion .................................................................................................................... 31
CHAPTER FIVE: DISCUSSIONS ....................................................................................................... 32
5.1 Introduction ................................................................................................................. 32
5.1.1 Discussion 1 .......................................................................................................... 32
5.1.2 Discussion 2 .......................................................................................................... 36
CHAPTER SIX: CONCLUSIONS AND RECOMMENDATION FOR FURTHER STUDY .... 37
6.1 Conclusion .................................................................................................................... 37
6.2 Recommendation for further study ............................................................................. 37
REFERENCES ................................................................................................................................. 39
APPENDIX ..................................................................................................................................... 47
Appendix 1 ............................................................................................................................... 47
Appendix 2 ............................................................................................................................... 49
Appendix 3 ............................................................................................................................... 50
v
List of Figures
Figure 3.1 Krippendorff's Alpha (nominal)………………………………………. 20
Figure 4.1 Distribution of Tweets collected globally……………………………..22
Figure 4.2 Graph of themes of tweets……………………………………………23
Figure 5.1 Combination of themes showing Reputation………………………...33
Figure 5.2 Combination of Themes showing Service…………………………. .34
vi
ACKNOWLEDGEMENT I acknowledge God for the grace to complete the Master’s degree program. The year
has been a wonderful one, all thanks to him.
I acknowledge my family, who have stood by me all through this year and have made
sure I was provided for; you have all been the source of my strength.
My friends who helped contribute to the success of this degree in one way or the other
are not left out, thank you for being there when I needed you.
God bless you all.
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CHAPTER ONE: INTRODUCTION AND CONTEXT
1.1 Background The global aviation industry has become early adopters of big data by applying it to
different parts of their businesses as it translates into business efficiency, reduction in
operational expenditure and supports internal business decision (Davenport, 2013).
Airline owners, aircraft manufacturers, original equipment manufacturers, ticket
reservation staff, customer experience department and even the human resources
departments of various airlines have adopted one form of big data technique or another
to boost revenue and enhance decision making, safety, reduced flight delays among
other applications.
According to Davenport (2013), the benefits big data brings for airlines include:
Fostering better customer services through customer interactions and insights
New products and services offerings from customer opinions and requests
Better decision support for service improvement and aircraft maintenance
Cheaper and faster data processing due to improved storage and processing
capabilities.
Tapping into big data’s potentials through airline servicing, a research conducted by
Cosmas & Tunasar (2014) showed that airlines can optimize three core areas of
operations including:
Airline Market Performance;
Passenger Behavior and;
Consumer choice.
According to the 2011 McKinsey report, big data is defined as those datasets whose
size is greater than the ability of traditional database software tools to capture, store,
manage and analyze. A caveat was put on the subjectivity of the definition as it
discloses the size of the dataset for it to be considered big. This is based on the
assumption that technology advances over time and the size will also increase and that
the sector where the data is gotten from will also qualify its size where it will range from
terabytes to petabytes (Manyika et al., 2011).
2
From a business perspective, big data speaks of the volume of data in structured and
unstructured forms that businesses acquire daily, while the amount of data is not so
important, the activities carried out with the data is of utmost importance to the
organization that has acquired it. It helps businesses analyze insights and make better
decisions and strategic business moves (SAS Institute Inc., 2016).
Gartner (2012) defines big data as high volume, high velocity and high variety
information resources which necessitates the availability of state of the art, low cost
processing systems that promote efficient insights, decision making and process
automation. The aim of Gartner’s definition being the insights, cost and ability for
automation to take place.
A more detailed explanation of big data is given by IBM, in the world today where 2.5
quintillion bytes of data is created daily and 90% of the data in the world was birthed
from the past two years. The expansion of information technology has given birth to
more devices transmitting data including sensors, social media, digital pictures and
videos, GPS trackers, purchase transactions and mobile telephone transmissions which
are just part of the list. The definition also looked critically at the 3V’s of big data
including volume, velocity, and variety (International Business Machines, 2016).
Volume: Big data volumes have grown to terabytes and now petabytes. They
include data transmitted in different formats every day.
Velocity: Velocity which speaks about the condition the data is ensures that data
generated is quickly put to use before it becomes obsolete.
Variety: Variety looks at the availability of the data in terms of format. This
means data that is structured or unstructured, where structured data is data that
can fit into tables and unstructured which talks about data that comes in different
formats including videos, pictures, sensor data, and click stream data.
The three are important to understanding big data (International Business Machines,
2016).
3
Source: 5 FAQs about big data (De Castro, 2013)
1.1.1 Social media big data. Social media big data analyses crucial insights into human behavior and has been
adopted as a means for social research by scholars, organizations, journalists and
governments (boyd & Crawford, 2012). Social media data is classified as big data
because of its unstructured and fragmented nature, they help to improve the
understanding of social phenomena that is found in the data generated (Zelenkauskaite
& Bucy, 2016).
Organizations now benefit from social media big data as they can use their historical
data to search for emerging trends from customer behavior. This helps them transform
costs and the effectiveness of their processes in terms of new product development,
market segmentation and product valuation (The Association of Chartered Certified
Accountants, November, 2013). Social media shifts content control from the
organization to the consumers they serve in which case can help them achieve their
goals or fall short of their expectations (Heller Baird & Parasnis, 2011).
The introduction of social media to the organization enhances the customer experience
of the organization’s brand through tapping into a wealth of reaction acquired first hand
from the customers that enjoy the product of the organization. Customer’s become the
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underlying factor for the success or failure of a brand based on what they share with the
public on social media about such brand (Thomases & Evans, 2010).
1.1.2 Airlines and Social Media In improving their brand image and expanding product reach, Airlines have included
social media platforms to suit their services with most airlines having departments in
charge of social media responsible for marketing, customer service, e-commerce and
corporate communications among other services (Kahonge, 2013).
Kahonge (2013) also mentioned social media business objectives for airlines which
include:
Building relationships and improving communications with customers;
Real time monitoring and response;
Improving customer engagement, driving traffic and improving brand
awareness;
Openness and reliability in operations.
Grančay (2013) identified different types of social media interaction. Bi-directional
interactions allow airlines, customers and the public free access to communicate with
each other. This is popular with Facebook and Twitter. While the Airlines keep the
public informed about trending news, promotions and other engagement documents,
customers can communicate with the Airlines while expecting feedback from them and
the public.
A classic example of bi- directional interaction which sparked a lot of reaction and
dented the business objectives was demonstrated with United Airlines where there was
a case with a customer, David Carroll who found out that the baggage handlers of the
airline had broken his guitar on a particular trip to Chicago. Filing a complaint against
the airline, he was ignored and the airlines refused to compensate him for the damages
done. He wrote a chain of songs depicting the story and uploaded on YouTube and put
up links to the song on Twitter (Ayres, 2009).
The first song in the story collection did so well after its release; it went viral on social
media and even broke into mainstream media having being aired on CNN and other
television channels. The video went international and had a negative effect on United
Airlines, it was published in The London Times that United Airlines had a 20% decline in
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market capitalization. This was equivalent to a $180 million loss to shareholders (Ayres,
2009).
1.2 Significance of the Study The focus of this dissertation is on KLM Royal Dutch Airlines, this airline has been
selected based on merits that have been showered on it by different data analysis
organizations for its application and use of social media data to provide better customer
service through proper interactions and quality social media service delivery. This
research serves to analyze what KLM has done right and to serve as an insight for
other airlines that haven’t jumped on the big data bandwagon yet to do so quickly.
This research area has been chosen to understand how Airlines have been able to
cope with social media data and its applications to customer service. While this is an
important aspect of the application of big data, it is important to note that this area of
study has been under researched academically, hence the lack of academic literature
on big data applications in the Aviation industry.
The area of research has been selected to understand how Airlines have adopted and
owned their social media strategy, especially with the case of KLM who have not only
successfully made their social media strategy work for them but have also monetized it
without compromising on quality of service thus, being associated with the best social
media strategy in the industry this also adds to the almost non- existent body of
knowledge in this regard, by looking at a particular area of focus of big data
applications.
KLM has crafted their social media strategy based on the pillars of Reputation, Service
and Commerce (van Drimmelen, Nobbe, van Houwelingen, van der Zee, Filippo,
Spruijt, Parren, et al., 2012).
1.3 Research Aim and Objectives
1.3.1 Aim To analyze the factors that have contributed to the success of KLM Airlines social
media adoption and draw out inferences on how other Airlines can learn from their
success stories in adequately adopting the right processes in social media use.
6
The research methodology that I will undertake towards finding the outcomes and
answers to all my research objectives and questions stated below;
1.3.2 Research Question 1. What achievements have KLM made from the adoption of its social media
strategy through information gathered on its Twitter Platform?
2. What underlying activities are facilitated from KLM’s engagement with its
customer’s based on content posted on its Twitter platform?
1.3.3 Research Objectives To carry out a literature review on the key impacts KLM has made in its social
media adoption.
To look into the activities carried out on KLM’s Twitter platform in relation to its
social media strategy.
To collect data for analysis from KLM’s official Twitter account.
To perform a content analysis on the data collected to gain insights into KLM’s
interaction with its customers with respect to its social media strategy.
To make suggestions for future work on social media adoption in this sector.
To contribute to the almost non-existent academic body of knowledge in this
field.
1.4 Dissertation Structure The dissertation is structured in the following order. In chapter two, the literature on
KLM Airlines and its success with its social media strategy will be reviewed. The review
will cover the history of its social media quest and the present situation. The review will
also try to cover plans that KLM has for the future of its social media strategy. In the
third chapter, the research methodology of the dissertation is discussed. Here, the use
of case study and qualitative analysis, the data collection methods, tools and
techniques adopted are justified, discussed and critically analysed. The fourth chapter
discusses the results of the data collection and the significant findings of the study
which are clearly presented and explained in text and graphical formats. In the fifth
chapter, the major findings of the study are identified and discussed. Appropriate
relationships are connected with these findings and the existing theories and problems
in the literature. In the sixth chapter, a summary of the aims, objectives, the main
chapters and the most significant results of the dissertation are presented. The
7
limitations of the study are stated here and recommendations are given for further
research of the topic.
8
CHAPTER TWO: LITERATURE REVIEW
2.1 Introduction The significance of KLM Airlines social media achievements forms a critical component
of the research endeavour as it gives an insight into the applications of social media for
airlines in the industry. In this literature review, the research objectives in the
introduction chapter will be considered in giving structure to the research by conducting
a thorough review on how KLM harnesses the content from their Twitter account in
delivering the required services to their customers and how they have been able to
stand out from their peers. The knowledge derived here will inform the process of
progress that has been made by KLM on its social media platforms especially on their
Twitter platform. The outcome of this literature review will inform the research
methodology this study has decided to adopt.
1 Source: “Official KLM Twitter page,” n.d.
The journey into social media success for KLM began in 2010 after the Eyjafjallajökull
eruption that left millions of travelers stranded. KLM had to devise a strategy to
communicate with its customers who were among the number of people that were
stranded at that time. A team of 150 volunteers across departments helped make the
hassle of rebooking passengers possible after the incident when operations resumed as
normal. This effort was carried out through social media using the Twitter and Facebook
platforms (van Drimmelen, Nobbe, van Houwelingen, van der Zee, Filippo, Spruijt, &
Parren, 2012a).
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After the Icelandic Ash cloud incident, in October 2010, the company decided to
establish their social media hub that would be located in the Headquarters and this
comprised of their Corporate Communications and E-commerce departments. People
from different backgrounds in the company joined forces to establish this unit. Their
collaborative efforts were connected under their CRM tools, Salesforce and Radian6
which was accessed through the cloud for monitoring and insights. By the 18th of July
2011, they were live 24/7 on the internet providing all day and everyday response to
customer requests. Their subsidiaries also opened social media accounts so that they
could monitor messages related to them. At that point, they offered services in 5
languages and were handling about 2,000 communications weekly (van Drimmelen,
Nobbe, van Houwelingen, van der Zee, Filippo, Spruijt, & Parren, 2012b).
From their collaborative efforts across the Headquarters and subsidiaries, they have
been able to launch successful social media campaigns amidst a few blunders. Their
campaigns have won them lots of awards but they even endeared themselves by boldly
making public their gaffes and blunders and learning from the experiences which have
made people like them even more.
For every campaign that was launched, the feedback derived gave them insights to
adjust their strategy to provide even better service. A couple of their campaigns include:
“Personal Space”, “Dreamy Destinations”, and “KLM Fans” which was aimed at using
talented filmmakers to promote their Facebook page.
Their best known campaign to date has been the “KLM Surprise” which surprised their
passengers who checked in through Foursquare or Twitter at different locations.
According to them, this gave passengers a special kind of feeling and sense of value
that their airlines were thinking about them.
Another spectacular campaign was the “Meet & Seat “; where a passenger could pick a
sitting partner through social media for the purpose of business or pleasure. This
campaign was welcome with much accolade (van Drimmelen, Nobbe, van
Houwelingen, van Buuren, et al., 2012).
A campaign that fascinates because they lost the bet was their “Fly2Miami” campaign
where they dared Dutch Film maker Wilco Jung and DJ/ Producer Seid van Riel to get
150 pre registrations within 7 days and KLM would fly them for free to Miami just in time
for the Ultra Music Festival and other spring events taking place in Miami. They got all
10
150 subscriptions in 5 hours, with the campaigns all taking place on Twitter (van
Drimmelen, van Buuren, Groot, & de Nooy, 2011).
In 2014, they were praised by Social Bakers who rated their services as number one
“Socially Devoted” brand globally where data showed their response was a surprising
98.5% from the 80,000 questions sent to them on Facebook- a response time 3 hours
more than the Airline’s industry average (Hutchinson, 2015).
In 2014 alone, KLM was able to generate $25 million in revenue from its social media
activities by selling tickets online through their Twitterbots @KLMflights and @KLMfares
and by introducing the “Meet & Seat”, and “Trip Planner”, conversions from these
platforms are measured on their website (Kollau, 2014). By monetizing their activities,
they showed that their activities on social media could be tied to revenue, a good key
performance index. Today the social media team is armed with 200 customer service
agents and growing, dedicated to giving customers a personal experience through
social media (Koetsier, 2015).
2.1.1 KLM’s Social media efforts The introduction of social media has given customer service a new meaning as airlines
have considered it a powerful tool to listen and provide feedback to customers (Walden,
Carlsson, & Papageorgiou, 2011).
The awareness of social media has brought about the ability for airlines to be able to
connect with their customers on a personal level (Scaglione, Schegg, & Trabichet,
2013). By connecting their social media platforms to their CRM’s, Airlines create
personalized services and products for the customers use (Buhalis & Law, 2008).
The insights from this stands out that KLM mastered the art of social customer service
and used it to transform their business early. From forming learning curves from 2009, a
structure was put up in 2011 to grow the terrain and put an efficient system of
governance in place. In 2012, the social media team was ready to overhaul and
monetize the department. The team created their new standard from the growth and
lessons they had learnt along the way. They were poised to be the social media leaders
among airlines. They crafted their social media strategy based on the pillars of
Reputation, Service and Commerce (van Drimmelen, Nobbe, van Houwelingen, van der
Zee, Filippo, Spruijt, Parren, et al., 2012).
11
2.2 The Theoretical Framework The theoretical framework for this research is built on the strategy KLM has crafted, and
would be carried out by looking at how social media affects the three pillars of strategy
which are reputation, service and commerce. Insights drawn from the tweets sampled
for this project will determine if KLM is in alignment with its social media strategy.
2.2.1 Reputation Social media has given customers the power to influence the actions of companies by
speaking out when they are wrong and promoting or praising them when they do well.
This act has made the consumer society dependent on the customer for decision
making (Cormode & Krishnamurthy, 2008). Customer information seeking behavior with
regards to products is now on the rise in social media (Gruen, Osmonbekov, &
Czaplewski, 2006).
Corporate reputation is defined as the result of a business’s ability to deliver valued
results to various stakeholders which encompasses the businesses past behavior
(Gardberg & Fombrun, 2002). Reputation is seen as a concept that builds emotional
and rational attitudes (Fombrun, Gardberg, & Sever, 2000).
Corporate reputation is the determining factor of consumers when they make
purchasing decisions (Walsh, Mitchell, Jackson, & Beatty, 2009) as consumers tend to
select businesses that show positive corporate behavior towards existing customers.
Positive customer reputation also leads to high market value and net worth as it
promotes customer loyalty (Gardberg & Fombrun, 2002). Also, it promotes shareholder
confidence and investment as it attracts loyal workforce and higher profit margins
(Chun, 2005).
One of the goals of this research is to investigate a relationship between the tweeting
behavior from KLM’s Twitter page and its corporate reputation, in order to understand
how its social media activity affects its corporate reputation.
2.2.2 Service Agnihotri et al. (2012) defined service using social media as successfully carrying out
activities that help customers gain trust in the business involved. In delivering quality
service, customer engagement plays a strategic role as the customers determine the
success of the brand in question (Brodie, Hollebeek, Juric, & Ilic, 2011).
12
Customer engagement can be increased by providing a platform for quality
engagement with customers that transcends from mere responses (Chu & Kim, 2011)
to keeping the customer interested in services provided through secondary
communication means.
Service is a measure of value creation (Plouffe & Barclay, 2007) as the occurrence of
social media has created an avenue for service providers to be in real time connection
with customers (Michel, Vargo, & Lusch, 2007) with respect to the type of social media
used.
Information sharing is a crucial part of service as it is bidirectional; it is only when
information is shared that service can be rendered. The information sharing behaviors
that have been identified include information giving, information receiving and
information use- that which is done with the information that has been obtained
(Agnihotri, Rapp, & Trainor, 2009). This introduces the CRM used by businesses to
harvest information to help target services better to customers in a view to augment
customer experience.
Customer service is about action, reaction and reliability. This means following up on
customer’s issues and commitments, and ensuring that the time to resolve such issues
are very short and remaining available to the customer around the clock (Ahearne,
Hughes, & Schillewaert, 2007). The introduction of social media to service puts a
personal touch on the service provided which improves the customer’s perspective
about the business.
Social media communication is also seen as an opportunity to build trust in the
business. This comes by the level of personal touch in the sentiments carried out by the
business (Boujena, Johnston, & Merunka, 2009).
2.2.3 Commerce Companies now use social media to transact business with their customers where
customers are able to quickly buy products and services while being engaged
(Anderson, Sims, Price, & Brusa, 2011). Social commerce is becoming more
commonplace. Facebook recently announced its latest invention, bots that would craws
user’s pages and allow businesses contact the users for marketing purposes (Murgia,
2016).
13
The reason why social commerce thrives is because of the success of social
relationships that have been built online by the participating business (Liang, Ho, Li, &
Turban, 2011). O’Reilly, (2005) listed some characteristics of social commerce which
include gathering collective intelligence, participation, viral marketing and market
disruption.
Between the years 2014 to 2015, social commerce increased in use by 200% (Digital
Agency Network, 2015). It has been touted that the prospects of social commerce will
only become more realistic as time progresses since social media affords businesses to
reach out to their customers more largely (Brown, 2016).
While the findings of this study provide a general knowledge of how KLM uses Twitter
as a tool for successful customer service implementation, it is quite rigid to investigate
the overall impact on other Airlines or in the context of social media for other Airlines.
This study addresses the research gap by understanding how Twitter has helped KLM
achieve its strategy through the communication it has with its customers in terms of
what information they share and how the information has been categorized to help
customers feel closer to the Airline.
2.3 KLM and Twitter Twitter is a micro- blogging site that emerged in 2006 and basically allows people
publish, reply to and re-post information in no more than 140 characters. The posts
usually include links to news stories, pictures, and videos. The user interaction is
usually a follow back mechanism where a user follows another user who follows back
for them to have a more private conversation (Marwick & boyd, 2010). This research
focuses more on what people post which has gained some research focus (Java, Song,
Finin, & Tseng, 2007, Naaman, Boase, & Lai, 2010).
Twitter is examined in this study for specific reasons. First, it is classified as a microblog
where short and specific content can be posted and where the content posted matters
more than the user profile and the user (Thelwall, Buckley, & Paltoglou, 2010). Second,
it communicates a real time reflection of customer’s feelings and expressions at the
time they write a post (Sreenivasan, Lee, & Goh, 2011). Due to the nature of the
limitation of words, customers are only allowed to express what they have in mind and
this takes the form of different themes usually in one post (Naaman, Becker, &
Gravano, 2011).
14
Twitter is largely a platform for communication, information sharing and reporting news
(Smith, Fischer, & Yongjian, 2012). Content is usually user generated and serves as a
form of expression for customers and communication with other users (boyd & Ellison,
2007).
The company considers its reputation as returns on social media investment to be the
quality content they publish across their platforms which has to be consistent and also
through sentiments from the published content as positive sentiment means increased
revenue and happy and satisfied customers. Their service currency has been their
proof of been a diverse brand, currently serving about 14 major languages and
operating 24 hours a day in shifts such that no automated responses are given to
clients at any time of the day. This has resulted in about 70,000 query resolutions
weekly. To show diversity, the company is actively on different platforms including
Facebook, Twitter, YouTube, WhatsApp, WeChat, Instagram and Pinterest where the
company tries to keep in touch with its numerous users. In February 2016, they
launched their WhatsApp rebooking system where you can re-book your cancelled
connecting flight and hope to extend this to all flights later (Filippo & ter Haar, 2016).
2.4 Summary Researching KLM’s social media is imperative as it gives insights to how much the
company has achieved its objectives and how it has been at the forefront of social
media success in the airline market. An historical background has been given as to why
the company chose to adopt a solid social media objective and even more chose
Twitter as the official customer relationship platform. Having pivoted its social media
strategy along the line in different ways, it is good to know how they have set
themselves to achieve their social media strategy. A three-point strategy has been
identified here and broken down in the social media context. They include reputation,
service and commerce. Literature has been broken down to understand the points in a
social media context and to validate previous work in the subject area. The literature
that has been formed will be used to consolidate the research efforts at the end of the
research.
15
CHAPTERE THREE: METHODOLOGY
3.1 Research Design The overall strategy used to integrate the different components of the study in a
comprehensible and rational way, thereby allowing for effectiveness in tackling the
research problems mostly consisting of the plan for collection, measurement and data
analysis is the research design (De Vaus, 2001). The context of the research design
from this research puts into consideration, the research questions and propositions, the
validity and reliability of the research findings and the right design intended (Rowley,
2002).
The research question that emerged from the literature review includes:
1. What achievements have KLM made from the adoption of its social media
strategy through information gathered on its Twitter Platform?
2. What underlying activities are facilitated from KLM’s engagement with its
customer’s based on content posted on its Twitter platform?
This chapter has been dedicated to discuss the research methods that will be used in
tackling the research questions listed above and tackle the research objectives. This
section considers the best possible approach for the analysis and breakdown of the
conceptual framework that emerges from the review of existing literature by explaining
the approaches of analysis that have been selected. The aim is to provide validity and
comprehensibility by justifying the research methods.
3.2 Sampling Strategy Academics have discovered Twitter to be a valuable tool for academic research as it
provides a variable amount of qualitative data that aids research aims, this is due to the
fact that Twitter users make publicly available the information they post for others to
view and engage in (Mislove, Lehmann, Ahn, Onnela, & Rosenquist, 2011). This
dissertation used tweets scraped from KLM’s official verified Twitter page not restricted
to its partner pages around the world as the major data collection method for the
purpose of the research.
16
To acquire data from Twitter, a variety of tools can be used to crawl the user page on
Twitter through access to an Application Programming Interface (API). The APIs
provide different levels of access to the Twitter data and as a result, different APIs exist.
The reason for this method is because it helps give us an insight into answering the
research questions as the company would not want to disclose sensitive information for
competitive reasons. The scope of data collection means the reach includes samples of
all tweets that have been shared between KLM and their customers. The cost of
collecting this data is low as one only needs to settle for a tool that can help with the
collection of data.
The practice of using Twitter for data collection is quite simple as there are processes
involved in making the most of it. The procedure includes the first step of identifying the
official Twitter handle for KLM. This can be done by Twitter verification as Twitter
verifies popular public brands through the use of a blue tick placed next to the User’s
name known as Twitter badges for authenticity, to differentiate them from fake or
unauthentic accounts to protect Twitter users (Twitter Support, 2016). Second, it is
important to check that the user has enough researchable content. This is done by
looking at the posts that are available on the user’s Twitter page, in this case KLM.
Third, the tool for collecting Twitter data is selected. There are a range of tools available
for data collection but the emphasis here should be that the main goal of the tools is just
to collect data and not necessarily analyze such.
The tool that was used to crawl Twitter for the data needed is the Klood engine. Klood
engine is a tool that has been designed to crawl social media for the purpose of data
collection (Klood, 2016). With respect to the API, Klood accesses the Twitter Firehose
API which grants 100% access to Twitter data in near real time in an almost similar way
as the Streaming API (Twitter API, 2014). The preference of the Firehose is such that at
the point of analysis, the most relevant customer and company tweets are what would
be available for analysis. The Firehose will be crawled for a period of time and 1000 of
the most recent Tweets generated would be selected for analysis. The information
contained in the firehose is usually in JSON format but the tool exports it in Microsoft
Excel readable formats.
While the Firehose gives complete access, it has a control mechanism that limits the
rate of data pushed through the tool as a way of protecting user data. Also, due to the
17
limitations of the tool, the representativeness of the data collected cannot be fully
asserted as it cannot be determined if the API grants the tool access to scrape the
whole data from the firehose and if all the tweets scraped during the period are tweets
posted during the period. While Twitter data is considered as big data due to its
unstructured nature (Pictures, Videos, words), the most important area of focus is the
information tweeted in words at any given point (Cheong & Lee, 2010).
After the details to push the data to the tool were supplied, Klood allowed access to
KLM tweets between June and July 2016. Altogether a total of 10,550 tweets were
scraped but the tweets were filtered to remove unwanted noise and other information
including tweets that were contained in other languages. Upon applying the filter to only
keep tweets that were in English language and had KLM Airlines information, a total of
5,300 tweets were left. These tweets were exported in Excel and were randomized to
leave the 1,000 tweets that would be used as the sample size for the analysis.
3.3 Methodology Description The methodology to be adopted for this research is the exploratory case study
methodology. The research first adopts an exploratory approach and tends towards a
case study to understand the research context better.
3.3.1 Exploratory research Research problems that have not been clearly defined usually adopt an exploratory
approach. This often leads to social research (Tellis, 1997). The objective is mainly to
identify key variables in the research area for better understanding often leading to the
feasibility of a more extensive study. Validity is key in exploratory researches in terms of
construct, internal and external validity (Yin, 2009).
3.3.2 Case study approach To make the research as concise as possible, the case study approach is used. The
case study research follows from clear objectives as set aside by the research. The
intent of the case study research is to focus on a particular issue bothering around the
research subject (Noor, 2008). In the case of this research, how KLM has managed to
transform Twitter to a tool for customer relations. The usefulness of the research is
described as asking questions of “Why” or “How” about a contemporary set of events
Yin (1994:9).
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3.4 Research Methods The research adopts a qualitative research method of data analysis. Qualitative
research discusses the use of words instead of numbers for the purpose of analysis
(Bricki, 2007). The aim is to understand and represent how people’s actions are
portrayed through the events they experience that have been documented (Elliott,
Fischer, & Rennie, 1999). The research takes a qualitative approach because the
tweets collected are represented in words and need to be grouped for better analytical
insights to take place. Also a qualitative method of analysis would do justice to the
answers for the research questions mentioned earlier.
3.5 Data Analysis Methods There are various methods of data analysis depending on the type of methodology
employed in a research. For the purpose of this research, the method that has been
deemed appropriate for this research is the content analysis.
3.5.1 Content Analysis Content analysis offers a systematic approach of comparing large data samples.
Krippendorff (2012, pp. 403–405), defines content analysis as a scientific method, that
assumes a “careful, detailed, systematic examination and interpretation of a body of
material to identify patterns, themes, biases and meanings”. The analysis that will be
carried on the Twitter data will identify common patterns in the tweets that have been
supplied and grouped into themes for proper understanding. Neuendorf (2002),
provides the most comprehensive definition of content analysis stating the requirement
for reliability and validity, he defines it as “the use of replicable and valid methods for
making specific inferences from text to other states or properties of its source”. This
helps us to determine the reliability of the data collected as we link it to the literature
review to test its validity and construct.
In identifying listed features quantitatively and methodically, content analysis can help
to make inferences on messages (Holsti, 1969). Also, without respect to the type of
variables that are measurable or the situations in which the messages were created,
content analysis summarizes the quantitative analysis of messages that rely on the
scientific method (Neuendorf, 2002).
Krippendorff (2004) suggests that there is a methodical reading of a group of texts in
content analysis after which the following six questions have to be asked before
carrying out content analysis. They include:
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1. What is the data to be analyzed?
2. How do you describe the data?
3. How is the sample population chosen?
4. How is the data contextualized in comparison to its analysis?
5. What are the limits placed on the analysis?
6. How is the inference derived?
The content analysis would be carried out on a sample population of 1000 random
tweets as earlier discussed, collected from KLMs official Twitter handle.
The benefits of using content analysis include the ability to be able to reduce large data
systematically, thereby compressing many textual data into content categories based
on well laid out coding techniques. The downfalls however, include poor definition of the
content categories and limited uncommon and incomprehensive categories (Stemler,
2001).
3.5.2 Thematic Coding We categorize the tweets under themes by building code frames. Thematic coding
comprises of recording passages of texts or images that have common ideas in such a
way that they can be indexed under one common topic known as a theme (Gibbs,
2007). The collected tweets were scanned to understand the content and group
according to the type of themes that will be suitable for them this is known as emergent
coding (Stemler, 2001). Once the themes are identified, the thematic code frame was
built. The code frame used is available in Appendix 1.
3.5.3 Inter Coder Reliability After the thematic code frame had been built, validity would be tested for clear
representation and understanding on a sample of the collected tweets by two
independent people to see if the themes agree with the overall tweets collected. In a
situation where the testers do not agree, the code frames have to be modified till there
is an agreement. This process is called the Inter coder reliability testing.
Inter coder reliability testing was created as a measure of validity for content analysis
studies. Its purpose is to ensure the analysis to be done is valid and well represented
(Freelon, 2010). The reliability test was carried out using Recal, Freelon’s online Inter
coder reliability service (Freelon, 2010). Before the reliability test was ascertained, two
independent coders were employed to code a sample of 100 tweets each along with the
research owner. The result below shows that the coded themes were suitable for the
20
tweets that were coded as there was an almost perfect level of agreement. The full
results are available in Appendix 2.
Figure 3.1
Krippendorff's Alpha (nominal)
Krippendorff's Alpha N Decisions Σcocc*** Σcnc(nc - 1)***
0.907 300 276 12430
3.6 Justification of the Methodology. In concluding this section, the methods that have been described here have been
selected as the most appropriate approaches for the study and research objectives.
Putting the exploratory and case study research together, there is the opportunity to
explore data that has not been provided in any literature which suits the case of KLM
Airlines and adapt it to suit their purpose to fulfil the aim of the research. Also, the
qualitative method that has been adopted alongside the content analysis gives us the
opportunity to sample KLM Airline’s tweets to be able to understand the implications of
the research objectives that have been set.
3.7 Ethical Issues. The ethical considerations in researching Social Network Sites (SNS) cannot be
underestimated as they frequently occur and are complicated. This comes as
researchers have found it easy to collect social media data for research, especially
Twitter data which gives easy access to its API (Kelley, Sleeper, & Cranshaw, 2013). It
is easy to collect free data from the API and source for the remaining data needed
when that which has been freely sourced is not complete but most of the time, the free
data collected is sufficient for the study they carry out (Pool, 2016).
The underlying ethical issue however is first the awareness of private individuals who
do not realize that their Twitter data is being used for research purposes as the
possibility of getting direct consent from them seems slim as they cannot all be
contacted this therefore, shows that they do not fully comprehend the implications of
using their Twitter data for research (Pool, 2016; Kelley, Sleeper, & Cranshaw, 2013).
The Twitter Terms of Service (TOS) contains legal documents that govern the use of
Twitter data on the site and the API. The TOS was drawn to protect the rights of users
21
but the TOS are usually updated to accommodate or condemn laws that have been
written therein (Twitter TOS, 2016a).
A look at the Terms of service (TOS) shows that Twitter gives a disclaimer about what
the Tweets can be used for as paraphrased here “This license is you authorizing us to
make your Tweets on the Twitter Services available to the rest of the world and to let
others do the same.” (Twitter TOS, 2016b). Twitter has made users know that their
Tweets can be used for any purpose which give researchers the leverage to even carry
out more research using Twitter data and reducing the rate at which they violate the
Twitter TOS altogether.
In consideration for the ethics of this dissertation, the University of Sheffield ensures
that students consider the implications and are asked to grade the risk of the
dissertation undertaken as well as discuss the intended use of the data. Once this is
done, an application is put forth for ethics approval. As for this research, it is considered
to be low risk and steps have been taken to provide private users tweets by
anonymizing their user data by completely deleting their usernames or information that
could easily lead to them. The data collected has been stored in the University’s cloud
drive as provided by the Information School and would be deleted once the dissertation
has been graded.
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CHAPTER FOUR: RESULTS AND FINDINGS
4.1 Introduction This chapter engages a critical analysis of the coding that has been done with respect
to the Twitter data collected. The method that had been selected was social media
content analysis. The tweets were coded from a selection of 1000 tweets which were
collected from the Klood engine in a systematic manner. One code frame was built for
the tweets using thematic coding to represent the corpus of the tweets and provided
insights from the tweets.
Given that KLM Royal Dutch Airlines is a multinational organization, people
communicate with them in different languages including the official language of the
Netherlands, which is the headquarters of KLM Airlines, Dutch. Other languages
encountered included Deutsch, Spanish, Latin, English etc.
Also, because it’s a global body, tweets were collected from @KLM_UK, @KLM_US
and other official aliased handles of KLM Airlines. The map below gives us an idea of
the geographical distribution of the interactions between KLM and its customers from
the tweets collected, with most of the interactions coming from North America and Asia.
Figure 4.1: Distribution of Tweets collected globally.
23
4.2 Findings from Content Analysis. Again, Twitter was selected as the platform for the study because many Airlines have
shifted their customer service focus to Twitter, using the platform to communicate to
their customers to respond to issues as fast as they can. For KLM Airlines, it has been
noted that the fastest way to reach them in terms of complaints or when they need to
get their travel issues resolved. The findings below give us some insights into the
occurrences KLM faces from their social media encounters daily.
4.2.1 Findings from the KLM Code frames. The code frame built for KLM consisted of 13 coded themes as discovered from the
tweets. These 13 themes represent the corpus of the text. The code frame built can be
found in Appendix 3. A total of 1000 tweets were coded using the code frames with the
results presented in the graph below.
Figure 4.2: Graph of themes of tweets
Enquiries
The theme enquiries stood for tweets that consisted of customer interaction,
investigations and clarification. From the total of 1000 tweets sampled, 303 tweets
represented enquiries taking a large area of the sample size, representing 30.3% of the
sample. Customers mostly want to be able to communicate with their Airline to make
requests, engage them in discussions about different topics and sometimes seek the
24
help of the airline by clarifying what the customer is saying or has asked as in the
example:
“@user It's unfortunate to hear about that. Would you mind elaborating
on this for us to know how could we be of help to you?”
This shows that KLM is ready to handle any query the customer has as soon as the
information passed has been clearly stated.
The tone of their messages seems to be friendly, asking if customers are alright with
the response to the enquires as given below:
“@user Great to hear that. Please let us know if you have further
inquiries. Have a great day!”
They also make sure they engage their customers, with a view to foster the relationship
or to convert such customers to flying customers.
“@user @Fly_Norwegian You've never flown with KLM have you?
@KLM @KLM_UK”
The large volume of sample tweets that represent enquiries show that KLM value
communication with their customers and also keep customers engaged making sure
that their needs are met and as fast as possible too. They also communicate with the
customers to add the personal touch the needs of the customers.
Reservations
In terms of reservations, KLM has been found to help customers to make reservations,
change bookings, change flights, help with seat reservations, ticket cancellations and
upgrades, etc. Sales are usually made here. A total of 159 tweets represented the
sample for this theme which shows that KLM respects its commercial acumen to be
able to transform Twitter to a tool for social commerce. Some form of engagement here
includes the tweet below where the response suggests that the customer had tweeted
KLM to inquire about changing the travel date on their tickets.
“@user Hello, there. Can you provide us with your booking code and
new preferred travel dates via Direct Message so we can assist you.”
25
Tweets that originate from this theme also come with monetary benefits as sales of
tickets, upgrades and seats are transacted here. For instance:
“@user A trip with the kids is easy to arrange with us. We'd gladly look
into making your kid's new booking. Send us a Direct Message.”
Also, passengers ask for help with seat reservations and changes which KLM helps to
take care of.
“@user Hello. We regret to hear that you were not able to select a seat
online. We would like to check it for you and in order for us to do so,
could you please send us your booking code via Direct Message?
Awaiting your reply.”
Some other instances are also given where the customers enquire about ticket refunds.
The sample tweet below shows the response:
“@user Full refund is only possible if the ticket was cancelled within 24
hours after the booking was made. Otherwise it will depend on your
ticket conditions. Please share your booking code via a Direct Message
so we can check the possibilities.”
Compliments
Compliments were coded to accommodate tweets that accept friendly greetings from
the customers and also giving friendly greetings to customers, a positive way to engage
the customers. The theme consisted of 116 Tweets which suggest that KLM has
impressive service provision to customers as a lot of customers have complimented
their services. The tweets below contain some of such information.
“@user We are glad to be of service always. :) Have a
great weekend to you too!”
“@user We're very glad to hear that you were satisfied with our services.
We look forward to see you on board again soon.”
“@user Passengers satisfaction is our top priority. :) We wish you a
pleasant day.”
26
The customers are also complimented about by the KLM staff, a way to keep them
engaged:
“@user Awesome picture!”
“@user Glad we could surprise you, :D”
Baggage Handling
Baggage handling is an important aspect of KLM customer service activities as
customers can easily complain about their baggage issues. A total of 114 tweets were
associated to the theme of this code. The tweets usually talk about lost baggage,
damaged baggage, excess luggage enquiries and tweets that talk about Property
Irregularity Report- a report that is usually filled out when there is a case of lost
baggage.
The tweet below shows a new enquiry about lost baggage and the response that the
owner has gotten to that regard:
“@user We regret to hear about this, Andy. Did you already fill out a
Property Irregularity Report at the airport?”
Also they are giving updates about the situation of the lost baggage to the customers, a
way to engage with them and appeal to them.
“@user Please be assured that we are doing our utmost and working
tirelessly to trace your luggage, Jim. Any update concerning the status of
your luggage, we will make sure you are informed immediately. Sincerely
appreciate your patience and understanding.”
The response below has been given in the case of excess luggage enquiries which
suggest that the customer has excess luggage and wants to confirm the terms for
excess luggage.
“@user All between 23 kg to 32 kg is charged as an additional bag.
Above 32 kg won’t be transported. :)”
27
Complaints
Things go wrong, and when they do, it is for some reason or a number of reasons. The
theme was coded to substitute for baggage related complaints as there are other
complaints that come up. KLM’s response to customer’s complaints is given here. A
total of 84 tweets were recorded here. The theme handles complaint related tweets;
these are tweets by enraged customers who voice out their disappointment at the way
KLM has handled issues relating to them. While some complaints can be easily
resolved, some others take time and the aggrieved party needs to be compensated in a
way.
“@user We regret hearing about your delay, Nick. Any chance the 2000
miles being offered was through a Customer Care File (complaint)?”
While complaints are acknowledged, some need to be also investigated to ascertain the
root cause and take some action to ensuring they do not happen again.
“@user That does not sound good. We will definitely look into it for you.
Would you mind sending us a Direct Message as we need a few more
details to make a Customer Care file for you?”
The end goal is to reduce incidents and convert aggrieved customers back to strong
believers of the brand.
Feedback
The concept of this theme is to give feedback to customers who ask questions or to
receive feedback from customers about different ranges of issues. Feedback is a
common tool for people to improve their services and feedback sometimes is getting a
response for question asked or something said. About 82 tweets were coded from the
feedback theme and they include feedback where the customer brings some
information they feel should be able to change the way they operate to their knowledge.
This would be usually noted in the type of response given as in:
“@user Thank you for bringing this to our attention. Your feedback is
duly noted. Apologies for the inconvenience caused. If you need further
assistance, do not hesitate to tweet us again. Thank you!”
28
The tweet suggests that the customer had given KLM a feedback about service he
received which he felt would have been better and would not have caused him any
inconvenience. They accept the feedback and promise to work on improving their
services.
Also, the feedback can be from KLM, just stating that they have received a customer’s
message and have replied same.
“@user We have responded to you directly. We shall look into your
request and get back to you promptly. Speak soon! :)”
Travel Guide
The travel guide theme handles tweets related to promotions that KLM run. The theme
recorded about 39 tweets, which included retweets from KLM as it is used for
promotional purposes to help with marketing. The topics here range from places for
customers to visit to educational promotions and even promotions about the brand. The
aim is usually to guide the customers to want to travel with KLM at the end of the day.
“RT @KLM: She has just departed for her testflight! Our #OrangePride
#KL9851 http://Twitter.com/KLM/status/743020242096533504/photo/1”
Sometimes the tweets serve for information purposes about events that are taking
place like in this case where KLM talks about an explosion in Istanbul that caused a
disruption to their services, thus making customers aware of what is going on.
“Statement KLM - Explosies luchthaven van Istanbul
http://nieuws.klm.com/statement---explosies-luchthaven-van-istanbul/
http://Twitter.com/KLM_press/status/747898878435934208/photo/1”
The tweets are also educational, talking about KLM’s history or giving out information
about activities that keep customers engaged.
“RT @KLM: She has just departed for her testflight! Our #OrangePride
#KL9851 http://Twitter.com/KLM/status/743020242096533504/photo/1”
This is a way to call the customers attention to what matters and appeal their travelling
pleasures from discovering new places or things that make KLM work.
29
“We can make it happen, watch out for our flight offers here:
https://www.klm.com/destinations/nl/en/search?WT.mc_id=C_WW_Soci
alCampaign_Twitter_Servicing_Destinations_null_null&WT.tsrc=SocialC
ampaign. :)”
Observations
Observations bother around tweets that suggest customers have publicly displayed
private and confidential information including their Ticket details and personal details. A
total of 27 tweets were recorded for this theme.
While one cannot be too careful about the type of information they display on social
media, some customers reveal their personal details in public tweets and are
admonished to delete such tweets so they are not vulnerable to suspicious behavior.
The customers involved are usually met with tweets that tell them to “kindly delete the
tweet” that contains such information so it’s not available to the general public.
“@user We request you to kindly delete the tweets, as it contains your
personal information. Please get back to us via Direct Message.”
Flight Status
The theme looks at the updates about flights including flight status, cancellations and
disruptions. A total of 23 tweets were coded in this regard. Customers usually tweet
about particular flights to ascertain updates about them
“At the moment the flight is on schedule. Should there be any changes,
you will be informed.”
“Hello. Could you let us know which flight you are taking so we may
check the status? Thanks in advance.”
They also reach out to customers in cases where there has been a flight disruption.
@user We understand delays and cancellations are never pleasant,
Chris. We regret the inconvenience caused.”
Third Party
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The theme looks at the tweets that have been tweeted by third parties on behalf of
KLM; they are usually news updates, KLM promotional tweets, or general news
information from or about KLM. A total of 22 third party tweets were coded in this
theme.
“5 Reasons Global #Airlines like @airfrance-@KLM and @airchina are
upgrading their Networks http://www.aryaka.com/blog/5-reasons-global-
airlines-like-air-france-klm-air-china-upgrading-networks/
http://Twitter.com/AryakaNetworks/status/749047481670000640/photo/1”
This third party tweet talks about why KLM and some other airlines are upgrading their
networks, which gives an insight into the new features the mentioned Airlines want to
introduce.
KLM Blog
Perhaps an important theme, the KLM Blog features events about KLM including posts
about travel ideas, destinations and sometimes some history of KLM. A total of 12
tweets were coded here. The Blog is operated to keep customers informed about
events KLM finds noteworthy and gives customers a feeling of belonging
“RT @KLM: Find out why KLM is bidding farewell to this aviation legend.
#KLMblog https://blog.klm.com/4-good-reasons-to-love-the-boeing-
747/?WT.mc_id=C_WW_SocialCampaign_Twitter_Editorial_BlogOde74
7MAY16_blog_null_&WT.tsrc=SocialCampaign
http://Twitter.com/KLM/status/737463626290724864/photo/1“
KLM Quiz
The category of this theme talks about quizzes and competitions that KLM uses to
engage its customers to keep their interests. The theme is coded with 10 tweets. The
reason for quizzes is to keep customers entertained and engaged with the brand, while
maybe competing for a number of prizes.
“RT @KLM_UK: Welcome to #KnowKLM!
Q1 coming up...winner gets to choose their prize: a KLM Bowling bag or
a KLM Reporter bag! https://t.co/?”
31
The tweet suggests a new competition is up and the winner of the competition would be
rewarded with a bag of prizes.
Other
The theme talks about tweets that cannot be categorized and has 9 entries. These
tweets do not fit in the other themes or the tweets just don’t make any sense or talk
about completely different things.
"@user wel.
https://Twitter.com/messages/compose?recipient_id=56377143“
4.3 Conclusion The analysis of the findings has been discussed to give us a background into the type
of tweets that have been collected and sampled. The need to engage the tweets is just
to lay a foundation of the information contained in the tweets and how the themes of the
code have satisfied the results of the tweets. The full text of coded tweets is available in
the data store provided by the University of Sheffield.
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CHAPTER FIVE: DISCUSSIONS
5.1 Introduction After an in-depth analysis of the results chapter, the discussions will take a look at the
research questions in a view of understanding the literature on how KLM has fared with
their Social Media strategy so far. This will be done by paying attention to the research
questions that have been given in the introductory chapter.
5.1.1 Discussion 1 KLM’s achievement from its social media strategy adoption
From the 2012 social media strategy adoption, KLM decided on three strategies to be
adopted to achieve excellence in their social media strategy. These include reputation,
service and commerce (van Drimmelen, Nobbe, van Houwelingen, van der Zee, Filippo,
Spruijt, Parren, et al., 2012). The results broke down the coding of the tweets found
according to each strategy objective mentioned, to have an in-depth understanding as
with the literature that was uncovered for each objective.
Reputation
Reputation means delivering values to customers to ensure they derive satisfaction and
the image of KLM remains protected. The determinant for reputation stems from the
success of discussions they have had with customers which presents their reputation in
good faith or which jeopardizes that reputation. Here we identify KLM’s positive and
negative reputations and try to correlate it with the present occurrence of the way things
have worked with them. The themes that give insight into their reputation include
compliments, baggage handling, complaints and flight status. These themes have been
selected as they point out how KLM is able to deal with customers on a personal basis.
Compliments show that customers are happy about the services they receive and which
show that KLM shows thoughts towards their customers. Baggage Handling shows that
KLM receives information about how they handle customer’s baggage which is mostly
filled with complaints. Complaints which show that customers detest the services being
offered and bare their minds and Flight status which show how they respond to
changes or disruptions in flights.
Theme
Percentage
Response
33
Compliments 11.6
Baggage
Handling 11.4
Complaints 8.4
Flight Status 2.3
Figure 5.1: Combination of themes showing Reputation
From the table above, it is observed that almost about 12% of coded tweets show that
KLM receives compliments from their customers. Happiness is a major measurement of
customer service (Scout, 2016). The insight shows that they are committed to delivering
quality customer service at all times. This is also reflective in their “Happy to help”
campaign (Carter, 2014).
The response for baggage claims is also quite high as it shows that they need to adopt
strategies to ensure they meet up with delivering customer baggage. It will be a
disappointment when customers take a trip and anticipate receiving their luggage only
to find out the luggage in question cannot be found. This will undermine their objective
to keep their reputation. KLM has received bad publicity for the consequences of their
actions in terms of handling customer luggage (Charlton, 2015). Baggage loss is
usually a problem for all the Airlines and has been a major concern for the Aviation
industry (Mayerowitz, 2016).
The response derived from complaints stem from the fact that they are working to have
as few as possible complaints and also show resolve in solving customer complaints.
This can be shown in some of the responses the customers gave in the sample tweets
collected where they thank KLM for solving their problems in a professional way and
making sure they helped. While complaints are a bad measurement for customer
service, it sometimes cannot be averted and the best way to deal with it is by helping to
solve the problem before it gets out of hand. Sometimes, really bad customer service
means very bad publicity for KLM (Hutchinson, 2016).
Keeping up with on schedule flights is usually a nightmare in the Aviation Industry as it
only doesn’t affect particular Airlines but all Airlines that operate in the industry.
Disappointments in flight scheduling always occur for a couple of reasons including bad
weather conditions, the state of the aircraft, issues arriving from the point of takeoff or
the destination among other issues (Cirrus, 2016). Through constant communication,
34
KLM has been able to help customers with their travel plans when there is the fear that
there might be a flight disruption or cancellation that will hamper their travel experience.
Service
Service here looks at how value has been created for the company in terms of pursuing
their wider goals. Communication is key in terms of delivering quality service.
Customers gain trust in the businesses that serve them when the businesses approach
them with respect and treat them like they are part of the business. This can be
reflected in the way KLM interacts with their customers where they try to keep up
conversations in interpersonal ways, respond as soon as possible to customer requests
and in a very friendly manner and also engage customers in different ways. The themes
to prove service include Enquiries, Feedback, KLM Blog, KLM Quiz and Travel Guide.
Theme
Percentage
Response
Enquiries 30.3
Feedback 8.2
KLM Blog 1.2
KLMQuiz 1
Travel Guide 3.9
44.6
Figure 5.2: Combination of Themes showing Service
The total representation from the selected themes stands at 44.6%. This goes to show
KLM’s commitment to service for its customers. By making customers feel more
welcome to the brand, the business not only keeps the customers but also use them to
win more customers. They recently introduced the addition of a reviews system to foster
customer relations and improve customer service (May, 2016).
KLM treats customer enquiries like conversations and try to engage the customers as
much as possible. They turn “Good Mornings” to “Are you satisfied with our services so
far” and always make sure to let the customer know that they can be reached anytime
they have any issues that need resolution. Dedicating their Twitter capacity to serving
customers, they made efforts to personalize the services and the results of the
personalization have benefitted them thus far.
35
Feedback is usually about receiving and acknowledging reaction from customers. They
also use it to communicate with customers to inform them about the receipt of their
enquiries. Customer feedback presents the company with a way to track and improve
their performance (Beard, 2014) and KLM adhering to their customer feedback goes to
show that they are committed to working with their customers to build their brand.
Using their blog, KLM posts news to get their customers interested in what they are
about. The blogs are a source of information for the customers to gain insight into
KLM’s story and have been used as a tool for customer engagement.
Another way they engage with their customers is through their Quiz where they post
questions on their Twitter pages and woo their customers to provide correct answers
and win different accolades. The attempt also draws them close to their customers.
The travel guide theme contains tweets that talk about travel experiences in different
places around the World and why customers need to enjoy such experiences. The
underlying idea here is that customers engage with the idea of travel thereby making
bookings to visit the places that have been highlighted or make plans to visit such
places.
It can be concluded that the company has its focus right in the service objective of its
social media strategy. The level of success can be said to be overwhelming in this
regard as they try to engage and win customer interests.
Commerce
Commerce speaks to how KLM has been able to monetize their social media strategy
so far. It was said that in 2014, a profit of 25 million Dollars was declared by the
company from their social media platform (Koetsier, 2015), here the strategy is looked
into as to how they fared in that regard and what communications have prompted them
to do even more.
Using Twitter as a tool for social media commerce, KLM always offers to help their
customers with booking flights or changing flight details and booking upgrades. These
activities can be classified as social media commerce activities. The reservations theme
carries on most of the commercial activities that take place with the Airline and contains
about 15.9% of coded tweets.
36
Recently, they launched their social commerce page on Facebook where customers
can pay for their tickets and get their boarding passes, a strong resolve to show that
they are serious with their social media commerce strategy (A. Hutchinson, 2016).
5.1.2 Discussion 2 Underlying activities facilitated by KLM’s engagement with its customers
From the thematic index given for the content analysis, it can be observed that KLM has
been able to focus on the pain points of their customers by tailoring the tweets to suit
their needs. This can be explored in the insights derived from the tweets pre and post
categorization. The comparison was done by comparing the themes utilized with the
customer feedback page of the company’s website (KLM Help, 2016). Categorization
was quite easy as there was a clear context from replies they furnished their customers.
Also in setting the strategy for their customers, they engage in 24 hours’ customer
service online on Twitter and serve customers in 13 languages which show that they
are accessible everywhere around the globe. Their Twitter homepage also shows
updates about how long it would take to get responses to questions asked of them, all
these pointers to engaging with customers the right way.
Due to the types of engagements they have, they have been able to keep the
customers interest as can be seen by the Enquiries theme where about 30% of tweets
sampled were from engagements between KLM and its customers. KLM also shows
awareness of their customer’s privacy and are quick to point that to customers who
share private and personal information on Twitter’s public timeline. The customers are
asked to politely delete the tweets with sensitive information so that it would not be
stolen or wrongly used.
At the end, the strategy employed by the company to engage with their customers is
warm and welcoming, ensuring that the customer feels appreciated from the tone of the
tweets that are published by the company.
37
CHAPTER SIX: CONCLUSIONS AND
RECOMMENDATION FOR FURTHER STUDY
6.1 Conclusion The dissertation set out to analyze the factors that have contributed to the success of
KLM Airlines social media adoption and draw inferences on how other airlines can learn
from the success stories and adopt the right processes in social media usage.
The objectives of the research included carrying out an extensive literature review to
understand the background of the topic and build a context for the framework which
was used to back up the research questions, thus understanding the key impacts of
social media adoption for Airlines.
The activities carried out on KLM’s Twitter platform were also looked into with relation to
achieving its social media strategy and collecting data for analysis on the official Twitter
account which was used to provide insights into how the company relates with their
customers. Once the data was collected, a content analysis was carried out using
thematic coding to classify the tweets into categories where a ranking of the various
categorical themes was obtained and insights derived.
The study shows that KLM’s overall strategy is hinged on customer engagement and
satisfaction. The overall priority for the company is being customer centric hence,
hinged on their social media strategy.
The limitation of the research however is that there is almost no existing literature in the
field and most sources of information were informal. Also, the representativeness of the
data collected could not be validated due to the scope of work and restriction of time for
the research to take place.
6.2 Recommendation for further study A suggestion for further study will include critically analyzing KLM’s Twitter account over
a period of time where large data could be collected and processed to gain valuable
insights into the company’s and its customer’s behaviors.
Recommendations based on this research would be for KLM to make necessary
adjustments to help its reputation objective especially with reducing the amount of
complaints received especially with baggage loss/ claims. The adoption of new
38
technologies in this regard which has been discussed previously would be a benefit to
the company (Paton, 2016).
Also, the study of other social media that KLM has adopted would be able to give the
research the necessary insights that can be used to strengthen the research.
The research is limited in scope as it is an area that has not been thoroughly
researched also.
39
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APPENDIX
Appendix 1 KLM Thematic Code Frame.
Code Theme of Code Category Description Response
1 Flight Status
Flight Status, Disruptions, Cancellations
These include updates on Flight status, disruptions and cancellations that is tweeted/ responded to, for customer’s benefits. E.g.: @c***** May we know from where you got to know this information since according to our system your flight is on schedule. 23
2 Enquiries
General Enquiries, Clarification, Engagements
Responding to Enquiries made by Customers on varying topics. Also clarifying discussions with customers and engaging customers in discussions that help the customer feel appreciated. e.g.: @1***** In order to have a better understanding, could you please elaborate the details of your experience?; @P**** Great! see we are on the know. :) Will you be travelling these year? 303
3 Baggage Handling
Lost Luggage, Excess Luggage, Luggage Complaints
Tweets signifying steps to resolving customer complaints on baggage handling, including lost, damaged, forgotten or tampered baggage. Tweets containing property irregularity number or report usually suggests baggage related issues.. Eg: @A***** We understand where you're coming from. Kindly send us the Property Irregularity Report number and booking code via dm 114
4 Compliments
Giving or making Response to: Regards to KLM Crew, Excitement about service, complimenting customer
Responses to compliments that have been made by customers, also giving compliments or showering praises on customers. Eg: @d***** Always at your service! Have a great day ahead. :) 116
5 Complaints
Response to: Bad service experience, Complaints about flights or personnel
Responses to complaints that are not related to baggage claims. Other complaints pertaining to flight experience, distasteful service and ill treatment from personnel etc. Eg: @ay3829%#$ We regret to hear this, Chris. However, this matter is at the discretion of the lounge staffs at the local airport. 84
6 Reservations
Booking Requests, Ticket Confirmation/ Cancellation, Seat Reservation, Changes in Flight Reservation
Tweets that suggest customers are being helped with booking enquiries, flight reschedules, seat reservations and changes, flight reservations and cancellations, and booking refunds. Eg: @5**** and would you mind sending us your booking code via Direct Message? Also, please confirm which flight you would like us to 159
48
7 Feedback
Suggestions, Feedback, Hints
Responses to suggestions and feedback that has been given by customers about specific or varying information. Also giving Customers hints that their messages have been responded to in direct messages. Eg: @%**** Please accept our apologies for any nuisance, Megan. We appreciate your feedback,and hope to be of help should you need us;@k**** We've received and replied to your Direct Message. 82
8 Observations
Removal of Personal Information
KLM advising Customers on deleting their personal information or information contained in their Tickets from their public Twitter timelines. Eg: @7***** We request you to kindly delete the tweets, as it contains your personal information. Please get back to us via Direct Message. 27
9 Travel Guide
Promotions, Campaigns, News
Campaigns, Promotions etc, usually geared at selling the KLM brand to customers and getting their interests. that is tweeted by KLM. Eg: Thinking about a trip to South Africa? Where would you start? 39
10 KLM Blog Blog
The KLM Blog contains tweets that KLM promotes through its blog posts. Eg: "RT @KLM: Find out why KLM is bidding farewell to this aviation legend. #KLMblog https://blog.klm.com/4-good-reasons-to-love-the-boeing-747/?WT.mc_id=C_WW_SocialCampaign_Twitter_Editorial_BlogOde747MAY16_blog_null_&WT.tsrc=SocialCampaign http://twitter.com/KLM/status/737463626290724864/photo/1" 12
11 KLMQuiz Competitions
KLM engagements using competitions and quizzes. Eg: Test your uniform knowledge. #KLMquiz https://blog.klm.com/quiz-recognize-the- 10
12 Third Party
Mentions, Retweets, Comments from third parties
Third parties posting/ retweeting KLM posts or mentioning KLM in their posts. Eg: RT @AeroMundoMag: #OrangePride in #Guayaquil @KLM @GYE_AAG greetings @hectoreliam @KLM_press @KLM_ES @SandroRotaEAP @iLove_Aviation https:? 22
20 Other
Tweets generated from KLM twitter handle that are not associated with the topics listed or that are unclear. Eg: @418787 Oops! Alright, here's how to send it. Click on the "Messages" tab from the menu bar on top of your Twitter home page, click 9
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Appendix 2 Intercoder Reliability using Recal
FILENAME intercoder.csv
filesize 725 bytes
n coders 3
n cases 100
n decisions 300
average pairwise percent agreement 92%
pairwise agreement cols 1 & 3 0.94
pairwise agreement cols 1 & 2 0.93
pairwise agreement cols 2 & 3 0.89
fleiss' kappa 0.906820241
FK observed agreement 0.92
FK expected agreement 0.141444444
average pairwise cohen's kappa 0.906873158
pairwise CK cols 1 & 3 0.930329772
pairwise CK cols 1 & 2 0.918166939
pairwise CK cols 2 & 3 0.872122762
krippendorff's alpha 0.90713084
Σcocc 276
Σcnc(nc - 1) 12430
* * *
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Appendix 3 Percentages of Samples from code frame
Theme of Code Response Percentage Response
Flight Status 23 2.3
Enquiries 303 30.3
Baggage Handling
114 11.4
Compliments 116 11.6
Complaints 84 8.4
Reservations 159 15.9
Feedback 82 8.2
Observations 27 2.7
Travel Guide 39 3.9
KLM Blog 12 1.2
KLMQuiz 10 1
Third Party 22 2.2
Other 9 0.9
1000 100
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Appendix 4
![AN INVESTIGATION INTO QUERIES SUBMITTED TO THE EUROPEANA …dagda.shef.ac.uk/dispub/dissertations/2011-12/External/SilveyE.pdf · (Europeana, [2012?]d), excluding the top-ranked Text](https://img.pdfslide.us/doc/110x75/5f63e4a8a0990e0224047a06/an-investigation-into-queries-submitted-to-the-europeana-dagdashefacukdispubdissertations2011-12external.jpg)
