Hello readers,
Twitter
is a popular social medium to popularize a brand and is therefore an apt place
to measure a brand’s impactful presence. In this analysis, we have analyzed and
ranked the brand presence of 11 automobile manufacturing firms and their
operations in India. Latest 1000 tweets as on 24.01.2016 have been analyzed.
Brand rankings
Sl. No.
|
Automobile
Mfg. firms |
Sample set
|
very.pos.
count |
very.neg.
count |
very.tot
|
Brand Score
|
1
|
@MahindraRise
|
928
|
81
|
3
|
84
|
96
|
2
|
@TataMotors
|
804
|
163
|
11
|
174
|
94
|
3
|
@Maruti_Corp
|
796
|
129
|
21
|
150
|
86
|
4
|
@DatsunIndia
|
1000
|
94
|
18
|
112
|
84
|
5
|
@RenaultIndia
|
351
|
36
|
11
|
47
|
77
|
6
|
@FordIndia
|
1000
|
68
|
36
|
104
|
65
|
7
|
@HyundaiIndia
|
524
|
52
|
28
|
80
|
65
|
8
|
@volkswagenindia
|
965
|
39
|
22
|
61
|
64
|
9
|
@Toyota_India
|
185
|
9
|
10
|
19
|
47
|
10
|
@HondaCarIndia
|
1000
|
52
|
194
|
246
|
21
|
11
|
@Chevrolet_India
|
27
|
0
|
2
|
2
|
0
|
Observations
1.
The
surprising entry in top ranks is undoubtedly Datsun India and more so because
their car models had been labelled as unsafe for driving on roads. Surprising
losers are Honda who despite having good cars, affordable servicing and
international repute have scored pretty low.
2.
Also,
despite being a new entrant to Indian car scene, Datsun has managed to put more
than 1000 tweets on its twitter handle. This shows that they are managing their
social media strategy very well. Chevrolet India on the other hand has 27
tweets on their main handle. Please note that some car manufacturers have
individual handles for their car brands which have not been parsed in this
analysis. However, if those handles included an attribution to parent twitter
handle, then those tweets have been collected in this analysis.
Mahindra @MahindraRise (Rank 1 of 11)
Word
frequency table (Top 10)
word
|
frequency
|
kuv
|
408
|
mahindrakuv
|
190
|
mahindra
|
181
|
anandmahindra
|
158
|
new
|
146
|
diesel
|
138
|
engine
|
117
|
odmag
|
113
|
delhi
|
107
|
launches
|
95
|
Wordcloud (“mahindrarise” dropped for
excessive repetition)
The wordclouds are heavy image files. To check them out, download the complete report here:
Tata Motors @TataMotors (Rank 2 of 11)
Word
frequency table (Top 10)
word
|
frequency
|
new
|
174
|
ceo
|
169
|
butschek
|
165
|
guenter
|
140
|
tata
|
125
|
welcome
|
88
|
join
|
80
|
extending
|
79
|
warm
|
79
|
httpstcoxvnwadbf
|
78
|
Wordcloud ("tatamotors"
dropped for excessive repetition)
The wordclouds are heavy image files. To check them out, download the complete report here:
Maruti @Maruti_Corp (Rank 3 of 11)
Word
frequency table (Top 10)
word
|
frequency
|
maruti
|
143
|
contest
|
129
|
enter
|
127
|
win
|
127
|
rideofrenzy
|
121
|
brezza
|
96
|
car
|
89
|
vitara
|
89
|
vitarabrezza
|
88
|
nexa
|
84
|
Wordcloud
("maruticorp" dropped for excessive repetition)
The wordclouds are heavy image files. To check them out, download the complete report here:
Datsun @DatsunIndia (Rank 4 of 11)
Word
frequency table (Top 10)
word
|
frequency
|
dream
|
327
|
yes
|
266
|
dreams
|
232
|
say
|
210
|
join
|
131
|
life
|
131
|
conversation
|
115
|
work
|
113
|
just
|
104
|
take
|
95
|
Wordcloud ("datsunindia","datsun","isayyes"
dropped for excessive repetition)
The wordclouds are heavy image files. To check them out, download the complete report here:
Apparently, Datsun has successfully attracted the social media users by leveraging their emotions using words like dreams.
Renault @RenaultIndia (Rank 5 of 11)
Word
frequency table (Top 10)
word
|
frequency
|
kwid
|
57
|
win
|
41
|
contest
|
39
|
renault
|
39
|
autoexpo
|
38
|
car
|
37
|
know
|
27
|
get
|
26
|
sale
|
23
|
bbfinalewithsalman
|
21
|
Wordcloud ("renaultindia"
dropped for excessive repetition)
The wordclouds are heavy image files. To check them out, download the complete report here:
Ford @FordIndia (Rank 6 of 11)
Word
frequency table (Top 10)
word
|
frequency
|
new
|
188
|
launched
|
147
|
ford
|
125
|
live
|
117
|
launch
|
110
|
lakh
|
87
|
suv
|
77
|
httpst
|
71
|
watch
|
71
|
will
|
61
|
Wordcloud ("endeavour",
"fordindia", "allnewfordendeavour" dropped for excessive
repetition)
The wordclouds are heavy image files. To check them out, download the complete report here:
Hyundai @HyundaiIndia (Rank 7 of 11)
Word
frequency table (Top 10)
word
|
frequency
|
car
|
63
|
creta
|
50
|
contest
|
37
|
enter
|
37
|
baleno
|
36
|
compact
|
35
|
iamsrk
|
31
|
part
|
31
|
timesofindia
|
31
|
autoexpo
|
30
|
Wordcloud
("hyundaiindia", "hyundai" dropped for
excessive repetition)
The wordclouds are heavy image files. To check them out, download the complete report here:
Volkswagen @volkswagenindia (Rank 8 of 11)
Word
frequency table (Top 10)
word
|
frequency
|
polo
|
412
|
cars
|
391
|
accident
|
390
|
features
|
389
|
safety
|
387
|
due
|
385
|
damage
|
384
|
recounts
|
384
|
rushikesh
|
384
|
averted
|
383
|
Wordcloud ("volkswagenindia","volkswagen"
dropped for excessive repetition)
The wordclouds are heavy image files. To check them out, download the complete report here:
Toyota @Toyota_India (Rank 9 of 11)
Word
frequency table (Top 10)
word
|
frequency
|
safety
|
38
|
india
|
37
|
toyotaatautoexpo
|
37
|
fortuner
|
34
|
new
|
34
|
expo
|
33
|
mascot
|
31
|
thums
|
31
|
fordindia
|
30
|
endeavour
|
29
|
Wordcloud ("toyotaindia"
dropped for excessive repetition)
The wordclouds are heavy image files. To check them out, download the complete report here:
https://goo.gl/tV4Yk6
[UPDATE]
This analysis deserves some more observations.
We found that the twitter dump obtained from using Toyota handle had references to its rival fordindia and endeavor. Toyota's Fortuner is a rival of Ford Endeavour and therefore, it is interesting to note that the comparison of them on official Twitter handle suggests a larger number of fence sitters. In such a situation, the rival providing an attractive price point will attract potential buyers. However, product homogeneity is also an important factor to be considered before arriving at conclusions. It has not been checked here.
[UPDATE]
This analysis deserves some more observations.
We found that the twitter dump obtained from using Toyota handle had references to its rival fordindia and endeavor. Toyota's Fortuner is a rival of Ford Endeavour and therefore, it is interesting to note that the comparison of them on official Twitter handle suggests a larger number of fence sitters. In such a situation, the rival providing an attractive price point will attract potential buyers. However, product homogeneity is also an important factor to be considered before arriving at conclusions. It has not been checked here.
Honda @HondaCarIndia (Rank 10 of 11)
Word
frequency table (Top 10)
word
|
frequency
|
health
|
234
|
vehicle
|
228
|
monitoring
|
152
|
honda
|
140
|
risk
|
126
|
can
|
124
|
engine
|
119
|
car
|
112
|
service
|
110
|
breaking
|
109
|
Wordcloud ("hondacarindia","hangoutwithhonda","hondaconnect"
dropped for excessive repetition)
The wordclouds are heavy image files. To check them out, download the complete report here:
Chevrolet @Chevrolet_India (Rank 11 of 11)
Word
frequency table (Top 10)
word
|
frequency
|
autoexpo
|
17
|
aetms
|
9
|
chevrolet
|
9
|
gtgt
|
9
|
beat
|
7
|
cruze
|
7
|
india
|
7
|
corvette
|
6
|
new
|
6
|
spin
|
6
|
Wordcloud ("chevroletindia" dropped
for excessive repetition)
The wordclouds are heavy image files. To check them out, download the complete report here:
We have not followed the individual product twitter hash tags for the firms and that is, apparently, the major reason of low number of tweets coming from Cherolet's official handle. But, if a tweet from its product handle, say Chevrolet Beat, also has a hash tag of Chevrolet India, then those tweets have been read and parsed in this analysis.
FAQs
Q) What is a
Brand Score?
For
the discerning readers, the brand score has been arrived at using the formula:
Brand
Score= 100 *(very.pos.count/very.tot)
where
very.pos.count
is the count of tweets found very positive, vice versa for very.neg.count
very.tot=
very.pos.count + very.neg.count
The
positive tweets have score more than +2 and negative have less than -2.
Q) How is
tweet scored?
To
cluster tweets into very positive or negative, we have parsed through the
tweets and calculated the scores as under:
Score=
(sum of positive words) – (sum of negative words)
Q) How did
you identify positive and negative words?
Independent
researchers Bing Liu and Minqing Hu of University of Illinois at Chicago have
created a lexicon of 6800 words under the heading of positive and negative
sentiments. We have used their lexicon as a reference to parse through the
tweet contents.
Visit
their work at:
https://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html
Q) How do I
know more about this field of study?
Q) What is the business value impact of Brand Score ?
Watch out for the future posts/ follow up story on this blog directdelta.blogspot.com !
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