India-Current Trends in Mobile Apps

7/29/2019 India-Current Trends in Mobile Apps

1/30

Presented by:-

Rinky Sachdeva (146)

Rohit Jain (147)

Presented To: Atul Mathur (149)

Prof. Shivani Bali Noufal Ahmed (150)

Munish Mittal (151)


2/30

FLOW OF PRESENTATION

Introduction to Mobile World

Top Mobile Phone Brands and their Market

Share in India

Current Scenario of Mobile Market in India

Brief Introduction to Mobile Applications

Categorization of Mobile Applications


3/30

INTRODUCTION TO MOBILE WORLD

A decade back, having mobile phone was

considered a luxury but now its common productwith increased utility over time.

Mobile was first introduced by Motorola in India. With advent of new technology and new market

players, the price has reduced greatly.

Today, we have intense competition in mobile

markets with different companies such as Nokia,

Samsung, Sony, Htc, Lg , Micromax , Apple etc.

Launched their products in India.


4/30

Rank Mobile Phone Company Market Share Revenue FY 2013

( Cr.)

1 Samsung 31.5% 11328

2 Nokia 27.2% 9780

3 Micromax 8.7% 3138

4 Karbonn 6.4% 2297

5 Apple Inc 3.6% 1293

6 HTC 3.3% 1180

7 BlackBerry 3.1% 1123

8 Lava 2.8% 1001

9 LG 2.3% 819

10 Sony 2.2% 797

TOP MOBILE PHONE BRANDS AND

THEIR MARKET SHARE IN INDIA


5/30

Population of India - 1.22 billion

No. of Mobile phone users in India - 861.66 million

No. of mobile phones as percentage of population -

70.42%

Global ranking in number of mobile phone user - 2.

CURRENT SCENARIO OF MOBILE

MARKET IN INDIA


6/30

Mobile Application is a software application designed to run on

Smartphones, tablet computers and other mobile devices.

Available through distribution platform which are operated by owner ofoperating system such Apples app store, Google play, Windows Phone Store

,Blackberry app world, Samsung Apps etc.

Mobile Applications(or Mobile apps) were originally offered for general

information such as email, calendar, contacts, stopwatch etc. but with

developed technological tools there are numerous apps in various categories

not limited to gaming, location based, travel, shopping and banking.

BRIEF INTRODUCTION TO

MOBILE APPLICATIONS


7/30

Category Applications

Social Media apps Facebook, Google+, Viber, Whatsapp

Email Communication Yahoo! Mail 2.6, Gmail 4.5.2, Hotmail 7.8.2.8.47

Banking apps iMobile, State Bank Freedom, HSBC Mobile

Banking

News & Weather updates Pulse, Weather condition online 2.7, CNN app

1.3.0

Travel &Shopping Trip it, Trip case, Kayak, Makemytrip,

Location Information GPS travelling Pro, Tracker, Phone Tracker,

Google Maps

Job Alert Indeed, Monster Job, Naukri.com Job Search

Gaming Apps Modern Combat4, Fruit Slice, Temple Run

CATEGORIZATION OF MOBILE

APPLICATIONS


8/30

To study the market share of leading Smartphone brands.

To study market segmentation of Smartphone brands

according to consumers Income.

To study market segmentation of Smartphone applications

according to consumers Income, Age and Profession.

To study difference in usage of Smartphone applications

according to consumers Income, Age and Profession.

OBJECTIVE


9/30

We have used Convenience sampling technique where the

research is conducted in New Delhi.

Market research was conducted and the responses were

collected with help of the questionnaire.

Sample Size-170

The research outcome is limited as the sample is collected

from a particular region and hence it cannot be generalized

for entire population.

RESEARCH CONDUCTED


10/30

Age Income Profession

45 years

FACTORS CONSIDERED FOR

RESEARCH


11/30

8 8 10 6

2

12

44

40

16

0

5

10

15

20

25

3035

40

45

50

Brands

CONSUMERS USING LEADING

SMARTPHONES


12/30

2 2 48

2

6

22

2

2

28

4

4

12

22

6

4

8

16

122

8

6

0

10

20

30

40

50

60

70

80

< 2 lacs 2- 5 lacs 5- 8 lacs > 8 lacs

Sony

Samsung

Nokia

Micromax

LG

Karbonn

HTC

BlackBerry

Apple

SMARTPHONE BUYING BEHAVIOR

ACCORDING TO DIFFERENT

INCOME GROUPS


13/30

00.5

1

1.5

2

2.5

3

3.5

4

4.5

UsageFrequency

USAGE FOR DIFFERENT

CATEGORY OF APPLICATION


14/30

Respondents were asked to rate their usage of different applications

on a scale of 1 to 5 ,where usage of a particular application

decreases from Most frequently used to Not at all used when

we move from 1 to 5.

It is clear from the graph that:

Social media, E-mail and Gaming applications are frequently used.

GPS, News & weather, Travel/Shopping and Job alert applications

are least used.

CONTD...


15/30

0

0.5

1

1.5

22.5

3

3.5

4

4.5

5

< 2 Lacs

2-5 lacs

5- 8 Lacs

>8 lacs

USAGE OF MOBILE APPS

ACCORDING TO FAMILY INCOME


16/30

25%

46%

14%

10%5%

Willingness to pay for Paid Applications

Nil

< Rs 100

Rs 100-200

Rs 200-400> Rs 400

HOW MANY CONSUMERS ARE

WILLING TO PAY FOR PAID

APPLICATIONS


17/30

Application usedDifference in highest and

lowest mean values

P- valueSocial Media 0.33 0.444Location app (GPS) 1.23 0.072E- mail App. 1.09 0.0Banking 1.0 0.311News and weather 0.83 0.175Travel and Shopping 0.77 0.074Games 0.75 0.413Job Alert 0.81 0.071

ANALYSIS OF SMARTPHONE

APPLICATIONS WITH AGE

FACTOR USING ANOVA

O t d i t d t i h th diff b t hi h t d l t


18/30

Our study is to determine whether difference between highest and lowest mean

values for each mobile application used is large enough to say that there exists a

significant difference in the their usage among different age groups.

Null Hypothesis Ho: 1=2=3=4= 5(Means of all age groups are equal)

Alternative Hypothesis Ha: 12345 (Means of all age groups are

unequal or means of any two groups are significantly different. )

Significance level taken = 5%

For, E-mail Communication app,

Difference in the two extreme values of mean = 1.50

P- value from ANNOVA test = 0

P < .05

Therefore, Null Hypothesis must be rejected.

It means that there exists a significant difference in the preference of people

towards the usage of E-mail communication app. in their smartphones among

various age groups.


19/30

In Homogeneity of Variance, Sig. Value=0.0 Since, Sig (p) value of 0.0 < 0.05(=.05)

We conclude that there exists a significant difference in the groups

variances.

Games Howell Post Hoc method. We found the following groups to have a(p-value < =.05) and thus these groups differ in their usage behaviour of E -

mail communication application.

Age Groups P value18-25 and 26-35 .01518-25 and 36-45 018-25 and >45 0

E-mail Apps

CONTD


20/30

Application usedDifference in highest

and lowest mean

values

P- value

Social Media 0.54 0.103Location app (GPS) 1.74 0.0E- mail App. 1.14 0.0Banking 0.92 0.055News and weather 1.51 0.0Travel and Shopping 2.05 0.0Games 0.55 0.104Job Alert 1.14 0.04


APPLICATIONS WITH INCOME

FACTOR USING ANOVA


21/30

Null Hypothesis Ho: 1=2=3=4= 5(Means of all Income groups are

equal)

Alternative Hypothesis Ha: 12345 (Means of all Income groups

are unequal or means of any two groups are significantly different. )


For, GPS app p-value from ANNOVA test =0.0

E-mail Communication app p-value from ANNOVA test =0.0

News and weather app p value from ANNOVA test =0.0

Travel & shopping app p-value from ANNOVA test =0.0

P < .05

Therefore, Null Hypothesis must be rejected.

It means that there exists a significant difference in the preference of people

towards the usage of these applications in their smartphones among various

income groups.


22/30

Income Groups P value8 lacs 0.048

Income Groups P value


23/30

Income Groups P value8 lacs .0322-5 lacs and >8 lacs .015-8 lacs and >8 lacs 0

Income Groups P value8 lacs 0.0

E-mail Apps

GPS Apps


24/30

Application usedDifference in highest and

lowest mean values

P- valueSocial Media 0.27 0.152Location app (GPS) 0.55 0.203E- mail App. 0.55 0.107Banking 0.22 0.801News and weather 0.37 0.363Travel and Shopping 1.09 0.001Games 0.45 0.163Job Alert 0.13 0.836


APPLICATIONS WITH PROFESSION

USING ANOVA


25/30

Null Hypothesis Ho: 1=2=3(Means of all profession groups areequal)

Alternative Hypothesis Ha: 123 (Means of all profession

groups are unequal or means of any two groups are significantlydifferent. )


For Travel & shopping app,

Difference in the two extreme values of mean = 1.09

P- value from ANNOVA test = 0.001

P < .05

Therefore, Null Hypothesis must be rejected. It means that there exists a significant difference in the preference

of people towards the usage of these applications in theirsmartphones among various income groups


26/30

Profession Groups P valueBusiness and Service .026

Travel / Shopping


27/30

Nokia, Samsung and Sony are the leading market smartphone brands withdecreasing share.

Social media, E-mail and Gaming apps are frequently used while News &

weather, Travel/Shopping, Job Alerts and GPS apps are least used.

Majority of the population prefer free apps over paid one.

A significant difference in usage of E-mail apps in age group18-25 & 26-35,18-

25 & 36-45 and18-25 & >45.

A significant difference in usage of Travel/Shopping apps in income group 8lacs.

A significant difference in usage of News/ weather apps in income group


28/30

A significant difference in usage of E-mail apps in income group

8 lacs, 2-5 lacs & >8 lacs, and 5-8 lacs & >8 lacs.

A significant difference in usage of GPS apps in income group

8 lacs.

A significant difference in usage of Travel/Shopping apps

between Business and Service class customers.

CONTD


29/30

http://www.voicendata.com/voice-data/analysis/194498/see-you-again

http://www.cybermedia.co.in/corporate/media-room/194385/voice-data-

survey-indian-mobile-handsets-market-2012

http://en.wikipedia.org/wiki/Mobile_app

REFERENCES


30/30

India-Current Trends in Mobile Apps

Documents

Transcript of India-Current Trends in Mobile Apps