Marketing Strategies: Red Bull Energy Drink Twitter Analysis

This report presents an analysis of Red Bull's marketing strategy on Twitter, examining the content and consumer responses to their tweets. The research categorizes tweets into various types, including commercial, non-commercial, and promotional content, and assesses the overall sentiment expressed by consumers. The study focuses on the Australian market, analyzing data from Red Bull's Twitter account in 2017. The methodology involves categorizing and analyzing 100 recent tweets and their corresponding consumer interactions, utilizing both qualitative and quantitative data analysis techniques. The findings reveal the types of content Red Bull promotes, highlighting the emphasis on event promotion rather than direct brand marketing. The report concludes with managerial implications, suggesting improvements for Red Bull's Twitter strategy to increase engagement and brand awareness. The study also categorizes consumer tweet responses to give the company a better understanding of its consumers' opinions.

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Table of Contents
INTRODUCTION.........................................................................................................................3
RESEARCH PROBLEM..............................................................................................................3
RESEARCH OBJECTIVE AND SCOPE...................................................................................3
METHODOLOGY........................................................................................................................3
DATA ANALYSIS.........................................................................................................................3
LITERATURE REVIEW.............................................................................................................4
Categorizing Criteria.................................................................................................................4
RESULTS.......................................................................................................................................4
REFERENCES..............................................................................................................................5
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CASE STUDY SHORT REPORT
INTRODUCTION
Market research via electronic means has become the most common way for businesses to
handle consumers and customers airing out their varying opinions (Libaiet al, 2013). Apparently,
the social media platform has becomes one of the most used advertising resources that are being
used by business. In that case, a research should be done on how the platform is fairing
especially when it comes to dealing with products which are not very popular to the consumers
because of their health effects like energy drinks(Attila et al, 2011).
Red bull energy drink Australia is a beverage that contains high concentrations of caffeine but no
contents of alcohol. Red bull Australia has recently become one of the main beverages being
used by people in Australia and therefore becoming popular and famous. However, the
marketing trends and methods of the businesses producing the drink are currently limited (Cha et
al, 2010). To earn some profit, the businesses have been focusing on advertising and promoting
the drinkin tweeter platform through videos, tweet statements, links etc. This report gives an
account of the research that was conducted.
RESEARCH PROBLEM
The research problems for this report were:
Interpreting the marketing strategy of Red bull Australia and providing managerial implications.
RESEARCH OBJECTIVE AND SCOPE
The objective for the research included:
To identify the type of tweets or information that the red bull energy drink posted in their tweeter
account.
The scope of the study was limited to the Red bull energy drink only. The study revolved around
what the drink’s information posted on its twitter account and the responses that the consumers
gave. The study also focused just on the marketing of the drink and the consumers around
Australia only.
METHODOLOGY
The study concentrated on the latest 100 tweets only out of all the total number of tweets that
were received in Red bull’stwitter account in the year 2017. These tweets represented the direct
replies, retweets, referral linksand hashtags among other things. The tweets were downloaded
from the account and presented for the study.
DATA ANALYSIS
The analysis of the tweets was done by first categorizing the tweets into six main categories and
two other categories. The data gotten from the categories was certainly in form of qualitative
data. It was analyzed by use of graphs which ended up showing the percentage of each category
out the total number of tweets.
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LITERATURE REVIEW
As mentioned earlier, the marketing of energy drink is becoming a popular norm in the state of
Australia simply because of the limitations accompanying advertising responsibility and
increased close competition from other energy producing companies (Australian Beverages,
2017). According to Chambers, 2014,Red bull being one of the most uprising and popular energy
drinks in Australia, seemed to be working its way up the market because of the positive vs
negative effects of twitter advertising platform. The responses that t received from the customers
represented different ideas, feeling and opinions in regard with the drink itself and other related
aspects of the drink (Yunusa et al, 2011).
According to Cotelo et al, 2016, the following tweets are some of the tweet categories: the
commercial tweets which are those tweets that contain messages to do with business
development or growth verses non-commercial tweets which are those tweets contain messages
that are beyond business dealings and promotions. Cessation tweets (tweets that contain
messages with a final decision), embedded tweets (tweets that bring out one’s own content or
idea to a twitter account. This is according to Tare et al, 2014), promotional tweets which are
those that are used in promoting or reaching a certain market or consumer group and pro-energy
tweets which are the tweets that represent the real time message or idea of an individual.
However, there are many other ways of classifying consumer response tweets, e.g.: positive vs
negative tweets, emotional tweets, factual tweets, positive vs negative verses negative and
emotional tweets among other aspects. The categories that were used in the research study were
the six main categories and the other classification which was whether the tweet was negatively,
positively or emotionally tweeted.
Categorizing Criteria
Another criteria for categorizing some of the tweets that were listed in the study was the positive
vs negative verses negative and emotional tweets. The positive vs negative tweets are those
tweets that are said to be agreeing with the main tweet. Positive tweets support the main tweet in
the website while the negative tweets go against the main tweet’s message. Also, they were
mostly the tweets that always made sense when read. The emotional are meant to express the
customer’s emotional feelings about the topic or the message in the main tweet. Emotional tweet
can be either joyous, exciting, sad or motivational (Jansen et al, 2009).
RESULTS
The analysis showed that the product promotional tweets represented 22% and 78% represented
the other aspects.Commercial tweets was represented by 18% product commercial, 10% event
commercial, 12% news commercial and completely 60% different commercial aspects. Non-
commercial tweets were represented by8% event, 11% news, 32% othersand 60% different non-
commercial aspects. Embedded tweets were represented by 17% hashtags, 8% company web link
and 75% other aspects. Cessation tweets were represented by 71% neutral, 24% positive and 5%
other aspects. Pro-energy tweets were represented by 10% actual pro-energy tweets and 90%
other aspects.Positive vs negative tweets were represented by 76% and 24% respectively.
Emotional tweetswere represented by 5% joyous, 5% sadistic, 5% excitement, 8% motivational
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and the emotionless tweets took 77%. These results are certainly derived from the raw data in the
twitter account and graphs below.
prdct promo event others news none
0
10
20
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60
70
commercial Vs non-commercial
Commercial non-commercial
Axis Title
% representation
hashtags none company weblink
0
10
20
30
40
50
60
70
80
embedded tweets
Axis Title
% representation
5

Sadistic joyous motivational exciting none
0
10
20
30
40
50
60
70
80
90
emotional tweets
Axis Title
% representation
6

negative positive
0
10
20
30
40
50
60
70
80
Positive Vs negative tweets
Axis Title
% representation
neutral positive none
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60
70
80
Cessation tweets
Axis Title
% representation
7

product Promotion others
0
10
20
30
40
50
60
70
80
90
Promotional tweets
Axis Title
% representation
8

product Promotion others
0
10
20
30
40
50
60
70
80
90
promotional tweets
Axis Title
% presentation
1
0
10
20
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60
70
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90
100
Pro enrgy tweets
pro energy nonrpo energy
Axis Title
% representation
Managerial Implications
Through Redbull Australia’s twitter account, it can be concluded that they are mostly promoting
sports or music events rather than focusing on the brand as an energy drink. The account is active
in terms of responding to their customers and by re-tweeting, however they are not engaging in a
dialogue or generating any buzz. The content posted as tweets is mostly about promoting their
website and gaming events. The internal team at Redbull Australia should be advised to improve
their account page by creating more buzz around the brand and engaging with followers(Saxton
and Waters, 2014). They should be thorough with their research.
CONCLUSION
It is clear that tweets can be divided into six main different categories. Also, the study showed
that one can categorize consumer tweets responses in many different ways. This helps the drink
to know what its’ consumers think about drink. However, most of the above categorized tweets
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hadpositive and negativereactions to the study that was conducted byredbull energy drink. The
information in this report also concluded that the drink isgrowing its market and that its
marketing management is becoming effective and efficient.
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Attila, S. and Çakir, B., 2011. Energy-drink consumption in college students and associated
factors. Nutrition, 27(3), pp.316-322.
Yunusa, I. and Ahmad, I.M., 2011. Energy-drinks: composition and health benefits. Bayero
journal of pure and applied sciences, 4(2), pp.186-191.
Cha, M., Haddadi, H., Benevenuto, F. and Gummadi, P.K., 2010. Measuring user influence in
twitter: The million follower fallacy. Icwsm, 10(10-17), p.30.
Gunja, N. and Brown, J.A., 2012. Energy drinks: health risks and toxicity. Med J Aust, 196(1),
pp.46-49.
Jansen, B.J., Zhang, M., Sobel, K. and Chowdury, A., 2009. Twitter power: Tweets as electronic
word of mouth. Journal of the Association for Information Science and Technology, 60(11),
pp.2169-2188.
Australian Beverages, 2017. Energy Drinks. [Online] Australian Beverages. Available at:
<http://www.australianbeverages.org/media-centre/energy-drinks/> [Accessed 26 Aug. 2017].
Libai, B., Muller, E. and Peres, R., 2013. Decomposing the value of word-of-mouth seeding
programs: Acceleration versus expansion. Journal of marketing research, 50(2), pp.161-176.
Palmatier, R.W., 2017. Marketing research centers: community, productivity, and
relevance. Journal of the Academy of Marketing Science, 45(4), pp.465-466.
Chambers, R. (2014). Red Bull doesn't give you wings, settles misleading ads case - AdNews.
[Online] Adnews.com.au. Available at: http://www.adnews.com.au/news/red-bull-doesn-t-give-
you-wings-settles-misleading-ads-case [Accessed 28 Aug. 2017].
Stephen, A.T. and Lamberton, C., 2016. A thematic exploration of digital, social media, and
mobile marketing research's evolution from 2000 to 2015 and an agenda for future
research. Journal of Marketing.
Tare, M., Gohokar, I., Sable, J., Paratwar, D. and Wajgi, R., 2014. Multi-class tweet
categorization using map reduce paradigm. International Journal of Computer Trends and
Technology (IJCTT), 9(2), pp.78-81.
Cotelo, J.M., Cruz, F.L., Enríquez, F. and Troyano, J.A., 2016. Tweet categorization by
combining content and structural knowledge. Information Fusion, 31, pp.54-64.
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Saxton, G.D. and Waters, R.D., 2014. What do stakeholders like on Facebook? Examining
public reactions to nonprofit organizations’ informational, promotional, and community-building
messages. Journal of Public Relations Research, 26(3), pp.280-299.
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