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longtermagonizingInternet and Web Development

Dec 13, 2013 (3 years and 5 months ago)

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Writer’s Choice

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Name:

Professor’s Name:

Subject or Discipline:

300958 Social Web Analytics

University:



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Writer’s Choice

Introduction

The company that is chosen for this analysis is Starbucks. Starbucks has a Twitter
account with around 5 million followers while the number of tweets is more than sixteen
thousand at present.
Therefore, it is a good example as well as makes an effective s
ource to
collect data from.
(YFS Magazine, 2013).
The analysis depicts how companies use social media
for their marketing and promotion, targeting Starbucks in particular.

The following report is divided into three sections; each section shows how informa
tion
displayed on the Twitter handle of Twitter can be used for promotional purposes. These sections
also throw light at how OSB can also utilize the same patterns to get a successful social media
outlet.









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Section 1

What to Tweet

Starbucks has a
number of Twitter handles at its disposal. Each of these accounts is used to
provide information regarding different aspect of Starbucks. However, the main Starbucks
handle on Twitter deals with all these sections of the company as a wh
ole. From a sample o
f a set
of thousand tweets, different clusters are formed. Each cluster is made by first downloading the
data from Twitter API using R, then clustering it with the help of multi
-
dimensional scaling.
Multi
-
dimensional scaling is used for two or more dimensi
ons using metric or non
-
metric
measurements. In this case, appropriate metrics are used. Each of the clusters depicts a separate
theme on which the information is based. There are ten clusters in total for information available
in the thousand tweets at St
arbucks Twitter account. These clusters along with their themes are
as follows:

1.

Schemes
/Offers
:

Starbucks devotes its major share of tweets to let readers know about

the offers or schemes it

offers them. The company, to increase its total number of
customers, uses these offers as incentives. An example of such an offer is “pay it
forward”, whereby Starbucks encourages its consumers to buy one coffee for a needy
person and get one for them all

free.
Similarly, particular types of drinks or beverages are
available at a discounted rate for a limited period. These offers, in a sample of 100
tweets, are equal to or more than 20.


2.

Products:

The greatest amount of tweets consists of the informati
on on the product
Starbucks creates. In our set of last 1000 tweets, the company talked about its Pumpkin
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Spice Latte, Espresso, Salted Caramel Coffee, Cappuccino, Frappuccino, Mocha etc.
These tweets described the taste, smell and quality of these product
s in an interesting
manner to create a need for them amongst the readers. Out of 100 tweets, the product
tweets were 25 or more.

3.

Rules
/News
:

Starbucks has a limited tweets section for news or rules, as they are already
available on different forums, inc
luding the website itself. Therefore, only 4 out of 100
tweets were about rules and regulations.

4.

Season/Weather:

In order to make the Twitter account an interesting
page, Starbucks
social media managers ensure that tweets regarding fall or summer season ar
e present on
regular intervals. This theme is also relevant to the varied products that are sold out in
different seasons or weathers. For instance, an iced coffee or orange flavored coffee are
refreshers for summers while the caramel chocolate coffee or h
ot drinks are the beverages
for fall. These tweets are 6 to 7 out of a set of 100 tweets.

5.

General:

Not all tweets on the page are coffee related, the account posts tweets of general
character or value to attract all kind of users. An example of this can

be the awareness
created by Starbucks about voting during recent elections in US. These tweets range from
political to religious and all types of social topics and made for around eight tweets in a
set of 100 tweets.

6.

Starbucks Hangout:

Starbucks Hangout

is a part of initiatives undertaken by the company
to improve its relationship with the communities.
A hangout with Maroon 5 is an apt
example of this.
These tweets are 4 to 5 in a computed sample of 100 tweets.

7.

Charity Programs
/Volunteer Works
:

The Comp
any is a keen promoter of social causes.
Fundraisers are held or executed online to help people through charity. These volunteer
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works are updated on the Twitter as well to enhance goodwill related to the company and
increase its line of customers. These t
weets are 3 out of 100
-
tweet sample.

8.

Holidays:

Starbucks wishes its followers every holiday without any negligence. There are
tweets about all the national holidays along with the Mothers day, Fathers day etc. Such
tweets were 7 out of 100 tweets used as a

sample in this analysis.

9.

Petition Signatures:

Starbucks initiated a campaign of signing petitions these days in US.
These petitions started from Washington D.C. and a huge number of people took part.
Tweets related to these petitions were 10 in a 100
-
twe
et sample by far. The number of
tweets is high because the company aims to promote this campaign through Twitter
majorly.

10.

Ethiopia Single Origin: On the national coffee day, the company decided to pay a tribute
to Ethiopia as it is the country from where c
offee originated. This topic covered major
section of last week’s tweets and in the sample of last 100 tweets; the “Ethiopia Single
Origin” tweets were around 10.

(Moth, 2013).







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Section 2

Who to Follow

In order to examine whether a company (OSB) should follow those who tweet about the
topics similar to that of the company, ten friends of Starbucks were located. The latest 100 tweets
of these ten friends were downloaded through the same procedure of Twitt
er API and R. The
most frequently used terms in these 100 tweets for each Twitter handle (Starbucks’ friend) were
taken and their frequency and cumulative frequency was tabulated. Frequency tables of words
for the ten chosen friends along with the Starbuck
s are given below:

STARBUCKS

Words

F
requency

Cumulative frequency




Company

2

2

Coffee

4

6

Shop

5

11

Week

6

17

Fall

4

21

Pumpkin

5

26

Happy

2

28

Now

4

32

Petition

6

38

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Beverage

3

41



TEN FRIENDS

KATE EARL

W
ords

F
requency

cumulative frequency




S
eason

2

2

W
arm

5

7

L
ove

4

11

D
ress

3

14

T
hanks

2

16

D
ay

6

20

S
ong

3

23

S
weet

5

28

M
otor

2

30


JACK DORSEY

Words

F
requency

cumulative frequency




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Hello

3

3

Square

4

7

Free

5

12

Here

6

18

Good

3

21

Impressive

2

23

New

5

28

Clean

6

34

Inspiring

5

39

Water

3

42


STARBUCKS PARTNERS

Words

F
requency

cumulative frequency




Our

2

2

Partner

4

6

Petitions

3

9

You

6

12

Heard

3

15

Voice

2

17

Difference

6

21

Share

4

25

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I
nspiring

3

28

L
eader

2

30


MASHABLE

W
ords

F
requency

Cumulative frequency




W
ith

4

4

O
ffline

3

7

T
witter

2

9

A
mazon

6

15

T
o

5

20

F
or

3

23

A
pple

2

25

Google

5

30

Facebook

6

36

P
ictures

2

38


MAROON 5

W
ords

F
requency

cumulative frequency




P
hotos

3

3

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R
eleased

5

8

C
heck

3

11

P
laying

4

15

N
ight

2

17

W
riter

6

23

producer

4

27

S
igned

6

33

M
usic

2

35

interview

3

38


FRAPPUCCINO

W
ords

F
requency

cumulative frequency




pumpkin

6

6

S
pice

4

10

Frappuccino

5

15

C
aramel

3

18

S
ipface

2

20

G
rande

3

23

C
ream

6

26

M
ocha

2

28

H
appy

5

33

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F
all

4

37


STARBUCKS NEWS

W
ords

F
requency

Cumulative frequency




company

2

2

N
ews

4

6

S
tores

5

11

C
offee

6

17

anniversary

4

21

customers

5

26

community

2

28

I
ced

4

32

webcast

6

38

announce

3

41


MY STARBUCKS IDEA

W
ords

F
requency

cumulative
frequency




I
dea

3


S
weet

2


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T
aste

5


P
each

4


R
oasted

6


S
tory

4


Christmas

5


beverage

3


flavored

2


espresso

4




STARBUCKS STORE

W
ords

F
requency

Cumulative frequency




F
lavor

6

6

T
reat

5

11

N
ow

3

14

B
lend

5

19

V
erismo

6

25

refreshers

3

28

O
nline

4

32

C
ard

2

34

G
ift

5

39

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F
ree

3

42



TEAVANA

W
ords

F
requency

Cumulative frequency




W
inner

4

4

T
weet

5

9

T
ea

3

12

W
eek

6

18

C
ider

2

20

M
essage

3

23

P
rize

5

28

C
up

6

34

L
abor

2

36

S
hop

3

29


These frequency tables helped evaluate the degree of difference between words used by the
chosen Twitter handle and each of its friends. The results showed that 6 out of 10 friends used
almost the same words as
Starbucks;

in
fact,

most of the tweets were s
hared by them. However,
the rest of chosen friends tweeted about the company or related topics only
occasionally
.

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Section 3

Following Friends

The analysis utilizes
graph to determine whether following or friending followers
helps,

a
company increase its customers or not. The effect on popularity is measured with the
help of an
egocentric graph. The egocentric graph used in this case is of 1.5 degree. 1.5 degree egocentric
graphs are mostly used for the
social networks where level 1 is the inclusion of ten most pouplar
friends and followers of Starbucks on Twitter while level 1.5 shows how these friends are
connected with the followers.

Ten chosen friends:

1.

Kate Earl

2.

My Starbucks Idea

3.

Starbucks Store

4.

Star
bucks News

5.

Frappuccino

6.

Teavana

7.

Maroon 5

8.

Mashable

9.

Starbucks Partners

10.

Jack Dorsey


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Top ten
followers:

1.

KChenoweth

2.

Chrisbrogan

3.

MCHammer

4.

El_Universal_Mx

5.

Adage

6.

Lizstrauss

7.

MandyJiroux

8.

MarketingProfs

9.

RayWJ

10.

Barefoot_exec

(Solis, 2011).

The centrality score for this

egocentric graph was obtained applying R
-
code. Starbucks was the
centre of the graph while one side was taken by the friends and the other side covered the
followers. The edges denoted these ten friends and followers
, while

the nodes or the connecting
lin
es were the linkage between these entities.
The centrality score or degree of centrality is the
number of nodes or vectors pointing at the centre i
-
e Starbucks. In this case, the degree of
centrality is 8.

The Twitter handles that had friended the followe
rs are My Starbucks Idea, Starbucks Store,
Frappuccino, Jack Dorsey, Starbucks Partners and Starbucks News.


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The remaining 12 loops were linked with the centre through these 8 loops which shows that they
were connected amongst each other. Therefore the cen
trality score is dependent on the number of
followers a company has friended. It is higher if the
number of followers that are friended is less
and vice versa
.















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Reference List:

Moth, D. (2013). How Starbucks Uses Pininterest, Facebook,
Twitter and Google+. Retrieved

from:
http://econsultancy.com/pk/blog/62281
-
how
-
starbucks
-
uses
-
pinterest
-
facebook
-
twitter
-
and
-
google

Starbucks. Tw
itter Account. Official. Retrieved from:

https://twitter.com/Starbucks

Solis, B. (2011) The Interest Graph on Twitter is Alive: Studying Starbucks Top Followers
.

Retrieved from:
http://www.briansolis.com/2011/02/the
-
interest
-
graph
-
on
-
twitter
-
is
-
alive
-
studying
-
starbucks
-
top
-
followers/

YFS Magazine. (2013). 10 Bra
nds that do Social Media really well. Retrieved from:

http://yfsentrepreneur.com/2013/09/20/10
-
brands
-
that
-
do
-
social
-
media
-
really
-
well/#axz
z2i5SxT7gy