customer satisfaction of mobile phone subscribers

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TABLE OF CONTENTS

Introduction ........................................ Error! Bookmark not defined.

Prerequisites ..............................................................................................

Objectives ............................................ Error! Bookmark not defined.

Methodology .............................................................................................

Analysis Of Data ......................................................................................

4.1: Graphical Representation ......... Error! Bookmark not defined.

4.2: Cross Tabulation ........................ Error! Bookmark not defined.

4.3: Pareto analysis ................................................................................

4.4: Factor Analysis .......................... Error! Bookmark not defined.

Conclusion ................................................................................................

Appendix ...................................................................................................

6.1: Questionnaire ................................ Error! Bookmark not defined.

6.2: R and Sas Program ....................... Error! Bookmark not defined.

Bibliography ........................................ Error! Bookmark not defined.

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ACKNOWLEDGEMENT

I am indebted to all who have directly and indirectly been of great help to me in doing and

writing this project report.

I am pleased to say that the whole report is just the presentation of the facts that have been

found during the projects through different sources and its each sentence is an exact

representation of the information obtained and the analysis thereof.

I hope that I have manifested my sincere attempts to represent all the information and other

things to the best of ability.

ABSTRACT Mobile phones have over the years have become something we just increased the use of on

a daily basis that we feel we are in need of this type of technology to remain in contact with

each other. Although some may say this is a basic method of communication. It has

developed over the past 30 years as has our need to use this means of communication.

Although the easiest form of communication it would appear that it is also one of the

methods we can no longer live without as part of our everyday lives.

The present study is undertaken to understand the customer satisfaction of Mobile Phone

Subscribers

The study was done to find out the customer satisfaction level in mobile service provider

players in the market and to know the customer perception towards other mobile service

providers, this survey was done in Mumbai cities.

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Introduction

Subscriber Identification Module (SIM) is an integrated circuit that securely stores

the international mobile subscriber identity (IMSI).

The first SIM card was made in 1991 by Munich smart-card maker Giesecke &

Devrient.

The SIM was initially specified by the European Telecommunications Standards

Institute.

India is the world’s fastest growing industry in the world in terms of number of

wireless connections after China, with 811.59 million mobile phone subscribers.

According to the world telecommunications industry, India will have 1.500 billion

mobile subscribers by 2016.

Theoretical Background of the Topic

Customer Satisfaction

According to Philip Kotler, “Satisfaction is a person’s feelings of pressure or

disappointment resulting from product’s perceived performance (outcome) in relation to his

or her expectations. Customer satisfaction is the level of a person’s felt state resulting from

comparing a product’s perceived performance (outcome) in relation to the person’s

expectations”.

This satisfaction level is a function of difference between perceived performance and

expectations. If the product’s performance, exceed expectation the customer highly satisfied

or delighted. If the performance matches the expectations the customer is satisfied. If the

products performance fall shorts of expectations the customer is dissatisfied.

1 Many companies are aiming for high satisfaction because customers who are just satisfied

still find it easy to switch when a better offer comes along. High satisfaction or delight

creates an emotional affinity with brand.

2 Variety of factors that affect customer satisfaction includes product quality, product

availability and after sales support such as warranties and services. Customer satisfaction

is seen as a proof of delivering a quality product or service. It is believed that customer

satisfaction brings sales growth, and market share. A company can always increase

customer satisfaction by lowering its price or increasing its services but this may result in

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e5 lower profits. Thus the purpose of marketing is to generate customer value profitability.

3 India is on the threshold of a new millennium. India chose for global economy, exposing

her to winds of change in the market place, which has expanded vastly and become

fiercely competitive. In the changed environment, decision makers view the marketing

concept as the key to success. Marketing in practice has to manage products, pricing,

promotion and distribution.

4 A successful product can be developed by exploding these opportunities. While

delivering the value of the consumer we make use of marketing support. This support is

based on the knowledge of consumers and distribution. Marketing support both at the

introduction of products and maturing is considered

5 Marketing, as suggested by the American Marketing Association is "an organizational

function and a set of processes for creating, communicating and delivering value to

customers and for managing customer relationships in ways that benefit the organization

and its stakeholders".

6 The two major factors of marketing are the recruitment of new customers (acquisition)

and the retention and expansion of relationships with existing customers (base

management). Marketing methods are informed by many of the social, particularly

psychology, sociology, and economics. Anthropology is also a small, but growing,

influence. Market research underpins these activities. Through advertising, it is also

related to many of the creative arts.

7 For a marketing plan to be successful, the mix of the four "Ps"1 i.e. product, price, place,

promotion must reflect the wants and desires of the consumers in the target market.

Trying to convince a market segment to buy something they don't want is extremely

expensive and seldom successful. Marketers depend on marketing research, both formal

and informal, to determine what consumers want and what they are willing to pay for.

Marketers hope that this process will give them a sustainable competitive advantage.

Marketing management is the practical application of this process. The offer is also an

important addition to the 4P's theory.

Skills of Marketers

Marketers have 4 main skill sets that they bring to an enterprise:

1) Opportunity Identification: Marketing begins before there is a product to sell.

Many people think marketing is just selling whatever comes out of the manufacturing

plant. It's the job of marketing to decide WHAT comes out of the manufacturing

plant in the first place. Before a business can make money there must be

opportunities for money to be made and it's marketing's job to define what those

opportunities are. Marketers analyze markets, market gaps, trends, products,

competition, and distribution channels to come up with opportunities to make money.

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e6 2) Competitive strategy/positioning:

Markets consist of groups of competitors competing for a customer's business. The job of

marketing is to decide how to create a defensible sustainable competitive advantage

against competitors. Marketers conceive strategies, tactics, and business models to make

it hard if not impossible for competition to take away customers from their business.

3) Demand generation/management

It's the job of marketing to create and sustain demand for a company's products.

Marketers manage demand for a company's products by influencing the probability and

frequency of their customer's purchase behavior.

4 ) Sales:

The ultimate goal of marketing is to make money for a business. In most company’s

sales are a different discipline and department from marketing. But in order for

salespeople to have any long term success in a company they must be led by marketing.

The better job a company does of identifying opportunities, creating a differential

sustainable competitive advantage, and generating demand for their products the easier it

will be for salespeople to make sales.

Brief introduction

Indian Telecom Industry is the fastest growing and 5th largest in the world at 110.01

million connections. The subscriber base has grown by 40% in 2005 and has reached the

expectations of 250 million in 2007. Over the years, two out of every three new telephone

connections are wireless. Consequently, wireless now accounts for 54.6% of the total

telephone subscriber base, as compared to only 40% in 2003. Wireless subscriber has

grown to 2.5 million new subscribers every month from 2007.

The wireless subscriber base skyrocketed from 33.69 million in 2004 to 62.57 million in

2005. The wireless technologies currently in use in the Indian Telecom Industry are Global

System for Mobile Communications (GSM) and Code Division Multiple Access (CDMA).

The industry presently has 9 GSM and 5 CDMA operators providing mobile services in 19

telecommunication circles and 4 metro cities, covering more than 2000 towns across the

country and the connectivity numbers are still growing for Indian Telecom Industry.

Telecom Industry in India is regulated by the Telecom Regulatory Authority of India

(TRAI). It has been able to earn a good reputation for its transparency and competence.

Telecom Industry community has three types of players.

State owned companies like - BSNL and MTNL.

Privately owned Indian companies like - Reliance Infocomm and Tata Teleservices.

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Companies like - Hutchison-Essar, BPL Mobile, Bharti Tele-Ventures, Idea Cellular,

Escotel Spice Communications, etc were done with foreign investments.

INDIAN TELECOM INDUSTRY AT A GLANCE IN 2012 - 2013

The telecom sector has been one of the fastest growing sectors in recent years in India. It is

now the second largest telephone network in the world, after China. Tele-density, which

shows the number of telephones per 100 persons, was 76.75 per cent at the end of October

2012. However with the growth of mobile telephony the number of landline telephones has

declined from 32.17 million as on end March 2012 to 30.95 million as on 31 October 2012.

Wireless telephones now account for 96.7 per cent of all telephones. After the Broadband

Policy came into force in 2004, several measures have been taken to promote broadband

penetration in the country. As a result, there were 22.86 million internet subscribers

including 13.79 million broadband subscribers at the end of March 2012.

Broadband subscribers increased to 14.81 million by the end of this financial year. India is

expected to have around 130.6 million mobile internet users by March 2014, according to a

joint study by the Internet and Mobile Association of India (IAMAI) and Indian Market

Research Bureau (IMRB). The number of users accessing internet through mobile devices

was 87.1 million in December 2012.

India's internet industry can contribute up to US$ 100 billion to India's gross domestic

product (GDP) and generate about 22 million jobs by 2015. The Indian telecom industry's

contribution is likely to increase upto 3.3 per cent of the country's GDP by 2015. The

telecommunications industry in India attracted foreign direct investments (FDI) worth

US$ 12,623 million between April 2000 to December 2012, an increase of 7 per cent to

the total FDI inflows in terms of US$, according to the latest data published by

Department of Industrial Policy and Promotion (DIPP)

Top leading Companies in Mumbai

1. AirTel (404 092) : Airtel,(2G & 3G) started its operations in Mumbai in 2002-2003.

Airtel has the advantage of being a national player. Airtel is owned by Bharti Group.

Airtel Numbers: 9004,9165,9665,9867,9892,9967,9987,7738.

2. Vodafone (404 020) : Vodafone (formerly Hutch/Orange/MaxTouch). It provide (2G

& 3G)network. Vodafone numbers: 9619,9769,9819,9820,9833,9920,9930,9169,

9167

3. IDEA: (405 799) Idea (2G & 3G) is the GSM branch of Aditya Birla Group started

service in Mumbai circle in 2008 & provide 2G & 3G service in Mumbai. Idea is

main beneficiary of MNP in Mumbai Circle with 71% subscriber base is from MNP

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

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

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

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and subscriber are satisfied with Idea service as it is providing better competitions to

Airtel and Vodafone with respect to cheaper call rate and best service with best

network .Idea numbers: 9702,9594,8108,8419,8424,8691,8692.

4. Reliance: (405 15) Reliance launched its GSM operations on 30 December 2008.

Reliance Numbers: 9022,9699,8080,8767,7303,7666. (2G & 3G)

5. Aircel (405 805): Aircel (2G only) is the latest entrant to Mumbai circle. It has

launched its operations in the month of April 2009. Aircel Number: 9768,8898.

6. DOLPHIN (404 069) : Dolphin is the GSM branch of MTNL. The Postpaid mobile

service brand is Dolphin while in Prepaid GSM service the Brand name is Trump.

MTNL GSM service Dolphin along with Trump is operator of Mumbai which

provide 2G and 3G both Mobile service. Dolphin Numbers: 9757,9869,9969.

7. TATA DOCOMO (405 039): Tata Docomo (2G only) It has launched its operations

in the month of November 2008 tata Docomo Number: 9029,8097.

Cross Tabulation

Chi_Square Test of Independence:

The Chi-square test of independence (also known as the Pearson Chi-square test, or simply the Chi-square)

is one of the most useful statistics for testing hypotheses when the variables are nominal, as often happens

in clinical research. Unlike most statistics, the Chi-square (χ2) can provide information not only on the

significance of any observed differences, but also provides detailed information on exactly which

categories account for any differences found. Thus, the amount and detail of information this statistic can

provide renders it one of the most useful tools in the researcher’s array of available analysis tools. As with

any statistic, there are requirements for its appropriate use, which are called “assumptions” of the statistic.

Additionally, the χ2 is a significance test, and should always be coupled with an appropriate test of

strength.

The Chi-square test is a non-parametric statistic, also called a distribution free test. Non-parametric tests

should be used when any one of the following conditions pertains to the data:

1. The level of measurement of all the variables is nominal or ordinal.

2. The sample sizes of the study groups are unequal; for the χ2 the groups may be of equal size or

unequal size whereas some parametric tests require groups of equal or approximately equal size.

3. The original data were measured at an interval or ratio level, but violate one of the following

assumptions of a parametric test:

a) The distribution of the data was seriously skewed or kurtotic (parametric tests assume

approximately normal distribution of the dependent variable), and thus the researcher must use a

distribution free statistic rather than a parametric statistic.

b) The data violate the assumptions of equal variance or homoscedasticity.

c) For any of a number of reasons (1), the continuous data were collapsed into a small number of

categories, and thus the data are no longer interval or ratio.

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

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

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

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

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Assumptions of the Chi-square

As with parametric tests, the non-parametric tests, including the χ2 assume the data were obtained through

random selection. However, it is not uncommon to find inferential statistics used when data are from

convenience samples rather than random samples. (To have confidence in the results when the random

sampling assumption is violated, several replication studies should be performed with essentially the same

result obtained). Each non-parametric test has its own specific assumptions as well. The assumptions of the

Chi-square include:

1. The data in the cells should be frequencies, or counts of cases rather than percentages or some other

transformation of the data.

2. The levels (or categories) of the variables are mutually exclusive. That is, a particular subject fits into

one and only one level of each of the variables.

3. Each subject may contribute data to one and only one cell in the χ2. If, for example, the same subjects

are tested over time such that the comparisons are of the same subjects at Time 1, Time 2, Time 3,

etc., then χ2 may not be used.

Calculating Chi-square With the data in table form, the researcher can proceed with calculating the χ2 statistic to find out if the

vaccination program made any difference in the health outcomes of the employees. The formula for

calculating a Chi-Square is:

Where:

O = Observed (the actual count of cases in each cell of the table)

E = Expected value (calculated below)

χ2=The cell Chi-square value

χ2=Formula instruction to sum all the cell Chi-square values

∑ χ2i-j= i-j is the correct notation to represent all the cells, from the first cell (i) to the last cell (j);

The first step in calculating a χ2 is to calculate the sum of each row, and the sum of each column. These

sums are called the “marginals” and there are row marginal values and column marginal values.

The second step is to calculate the expected values for each cell. In the Chi-square statistic, the “expected”

values represent an estimate of how the cases would be distributed if there were NO vaccine effect.

Expected values must reflect both the incidence of cases in each category and the unbiased distribution of

cases if there is no vaccine effect. This means the statistic cannot just count the total N and divide by 6 for

the expected number in each cell. That would not take account of the fact that more subjects stayed healthy

regardless of whether they were vaccinated or not. Chi-Square expecteds are calculated as follows:

Where:

E = represents the cell expected value,

MR = represents the row marginal for that cell,

MC = represents the column marginal for that cell, and

n = represents the total sample size.

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e10 Measure of strength of association between variables

Cramer’s V is used to measure the strength of the association between one nominal variable with

either another nominal variable, or with an ordinal variable. Both of the variables can have more than 2

levels. (It applies to either nominal X nominal crosstabs, or ordinal X nominal crosstabs, with no restriction

on the number of levels.)

V = √χ2

nt

n = Total sample size

t = min(r-1, c-1)

Where-

r = number of levels of variable one

c = number of levels of variable two

Pareto analysis

Pareto analysis is a formal technique useful where many possible courses of action are competing for

attention. In essence, the problem-solver estimates the benefit delivered by each action, then selects a

number of the most effective actions that deliver a total benefit reasonably close to the maximal possible

one.

Pareto analysis is a creative way of looking at causes of problems because it helps stimulate thinking and

organize thoughts. However, it can be limited by its exclusion of possibly important problems which may

be small initially, but which grow with time. It should be combined with other analytical tools such as

failure mode and effects analysis and fault tree analysis for example

This technique helps to identify the top portion of causes that need to be addressed to resolve the majority

of problems. Once the predominant causes are identified, then tools like the Ishikawa diagram or Fish-bone

Analysis can be used to identify the root causes of the problems. While it is common to refer to pareto as

"80/20" rule, under the assumption that, in all situations, 20% of causes determine 80% of problems, this

ratio is merely a convenient rule of thumb and is not nor should it be considered immutable law of nature.

Steps to identify the important causes using 80/20 rule:

1. Form an explicit table listing the causes and their frequency as a percentage.

2. Arrange the rows in the decreasing order of importance of the causes (i.e., the most important cause

first)

3. Add a cumulative percentage column to the table

4. Plot with causes on x- and cumulative percentage on y-axis

5. Join the above points to form a curve

6. Plot (on the same graph) a bar graph with causes on x- and percent frequency on y-axis

7. Draw a line at 80% on y-axis parallel to x-axis. Then drop the line at the point of intersection with

the curve on x-axis. This point on the x-axis separates the important causes (on the left) and trivial

causes (on the right)

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8. Explicitly review the chart to ensure that at least 80% of the causes are captured

AAIIMM && OOBBJJEECCTTIIVVEESS Scope of study: scope is limited to Mumbai region only.

Aim of the study: This project aims at studying the present market scenario.

The major players in the market today are Airtel, Vodafone, Mtnl, Tata

Docomo, Reliance, Idea, Aircel. All The companies want to capture the market

study concerns with evaluating fast developing area and so all the service

providers were taken to measure the satisfaction of customer.

Objectives of the study: To check whether there is any relationship between

Age group V/S monthly expenditure on the mobile connection.

Occupation V/S monthly expenditure on the mobile

connection .

Service Providers V/S monthly expenditure on the mobile

connection .

3G Connection V/S monthly expenditure on the mobile

connection .

To study and identify how the customers are benefitted.

To evaluate the major service provider satisfied the customer .

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e12 To assess the factors influencing the person’s in selecting a mobile phone

service operator.

To Understand the performance of different service providers in the

market on various parameters like Product quality, Performance of the

Customer Care Executive(CCE),Service quality, Range and selection of

products available

Customer Satisfaction of mobile phone subscribers

Gender: 1) Male 2) Female Q2. Age: - ________

Occupaton: 1) Salaried 2) Self-employed 3) Retired

4) Student 5) Housewife

If student then present education level.

Below SSC (10th) SSC HSC (12th) Graduation

Post Graduation Other: Questionnairs:-

1 .What type of connection it is?* Prepaid Postpaid

2 .Do you use more than 1 SIM Yes No 3 . Which all SIMs do you use currently?*

Airtel Vodafone Idea Reliance Aircel

MTNL Tata Indicom/Docomo Other:

4 .Which is your Main/Primary SIM or Service provider*?

Airtel Vodafone Idea Reliance Aircel

MTNL Tata Indicom/Docomo Other:

5 .Is it a 3G connection?* Yes No

6 .Have you exercised Number Portability (MNP)?* Yes No

7 .How much do you spend monthly on the mobile connection?*

< than 100 101-200 201-500 > than 500 8 .How often do you use these services on your mobile phone?*

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Never Rarely Sometimes Often Always

Local Voice calls

STD Calls

ISD Calls

SMS

MMS General internet

usage/browsing/GPRS

Specially for Facebook,

Twitter,Whatsapp,Wechat,BBM,etc

CRBT (Hello Tunes,Dialler Tunes, etc)

9 .How important are these factors for you in selecting a mobile phone service operator?*

Extremely Unim

portant Not Very Important

Somewhat Important

Important Very Importa

nt Extremely Im

portant

Data services/ Internet

Transparency in billing

Advertisements

Innovations/New Services

Network Coverage where ever I go

Tariff/pricing Retailer Recommendations

10 .Please rate "Your service provider" for the factors given below*

Strongly Disagree

Somewhat

Disagree Disagree Somewhat Agree

Strongly

Agree Agree

Customer care

executives are

helpful

Customer care

executives have

complete knowledge

of tariffs & plans

It is easy to lodge

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Strongly Disagree

Somewhat


Strongly

Agree Agree

complaints with

your mobile

phone service

operator

Billing system is

accurate &

transparent

Customer service

executive performs

the right service the

first time

Service resolution is

delivered within

promised time

*

Strongly Disagree

Somewhat


Strongly

Agree Agree

My mobile phone

operator provides

sufficient network

coverage

Incidence of call

drops are least

Voice clarity on my

mobile network is

good

It is easy to activate

a VAS service

(Value

Added Service)

It is easy to de-

activate a VAS

service (Value

Added Service)

I get good internet

speed (GPRS) on

my phone

----------------------------------------x----------------------------------------x-----------------------------------

Collection Method

Population: All the people in Mumbai who uses Smartphones

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Sampling procedure: Convenient sampling.

Pilot survey: We conducted a pilot survey of 50 individuals. This helped us to improve our

questionnaire.

Survey: Our sample size (n) for the survey is 573 and after cleaning it reduces to 527.

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Statistical Software used for the analysis.

ANALYSIS OF DATA

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DEMOGRAPHICS

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12%

37%

24%

10%

17%

<=18

19 to 23

24 to 29

30 to 34

>=35

Age group

Conclusion:

The largest group of respondents was youth aged 19-23 yrs old, followed by 24-

29 yrs old and the least was 30-34 yrs old.

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33

107 108

23

5137

168

Aircel Airtel Idea MTNL Reliance Tata Docomo Vodafone

Mobile Phone Subscribers

Conclusion:

As the area of the study is in Mumbai, where the market leader is “Vodafone”, That’s why

majority of the questionary I got filled by Vodafone.

Above data analysis shows that majority of the market that is approximately 73% is covered

by three market leaders Vidafone, Airtel and Idea. Minor is MTNL

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0

10

20

30

40

50

60

70

80

90

100

Aircel Airtel Idea MTNL Reliance Tata Docomo

Vodafone

76.74 78.67 81.8188.46

78.4668.51

85.71

23.25 21.32 18.1811.53

21.5331.48

14.28

Main% 0ptional%

4444

3

43 136 132 26 65 54 196

Main sim V/s Optional sim

Conclusion:

The above percentage graph show that from the total sample 31% people use Tata Docomo

as an Optional sim and 87% people preferred Vodafone as a Main sim

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Conclusion:

Vodafone saw the highest number of port-in requests for any service provider

It means Vodafone, has captured the first position in MNP whereas Idea stood at number

two and Airtel at 3rd position.

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Conclusion:

The above graph shows that the majority of the customers regularly uses local call, Internet

& FB Whatsapp etc. So there is a need for the service providers to be focused on these

services so that the customer can easily avail the benefits.

Values are

in %

Aircel Airtel Idea MTNL Reliance Tata Docomo Vodafone

LOCAL

25.11 24.96 25.89 30.26 25.48 25.67 26.49

STD

13.82 15.19 17.47 14.94 15.45 13.98 14.72

SMS

20.04 15.99 13.9 13.40 15.18 15.7 14.18

INTERNET

20.04 22.02 21.49 21.07 22.28 22.22 21.77

Fb_Wa

20.96 21.82 21.23 20.3 21.58 22.41 22.81

Services V/s Service Providers

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Conclusion:

The above analysis shows that the most of the local call is being preferred by MTNL &

STD call by Idea. Most of the respondents use Aircel for SMS service and Reliance for

Internet pack and lastly Vodafone is being preferred for facebook and whatsapp.

Cross Tabulation

# To check association between 3G Connection and Monthly Expenditure on the

Mobile Connection

H0: There is no association between 3G Connection and Monthly expenditure on the

mobile connection

H1: There is an association

Statistic DF Value Prob

Chi-Square 3 28.42 <.0001

Likelihood Ratio Chi-Square 3 28.505 <.0001

Cramer's V 0.2322

Conclusion:

Since p-value is significantly low (i.e. <0.05).We reject H0 and concluding that there is an

association between Spectrum and Monthly expenditure on the mobile connection. Since

Cramer’s V value is between 0.2 and 0.25, there is a moderate association between Service

Providers and Monthly expenditure on the mobile connection.

# To check association between Age and Monthly Expenditure on the Mobile

Connection

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SPSS OUTPUT

Age * rs Cross tabulation

rs

Total < than 100 101 to 200 201 to 500 > than 500

Age <=18 Count 23 34 5 2 64

% within Age 35.9% 53.1% 7.8% 3.1% 100.0%

19 to 23 Count 48 108 36 4 196

% within Age 24.5% 55.1% 18.4% 2.0% 100.0%

24 to 29 Count 16 58 41 13 128

% within Age 12.5% 45.3% 32.0% 10.2% 100.0%

30 to 34 Count 6 12 19 13 50

% within Age 12.0% 24.0% 38.0% 26.0% 100.0%

>=35 Count 18 25 25 21 89

% within Age 20.2% 28.1% 28.1% 23.6% 100.0%

Total Count 111 237 126 53 527

% within Age 21.1% 45.0% 23.9% 10.1% 100.0%

H0: There is no association between Age and Monthly expenditure on the mobile

connection


Chi-Square Tests

Value df

Asymp. Sig.

(2-sided)

Pearson Chi-Square 92.432a 12 .000

Likelihood Ratio 94.436 12 .000

Cramer's V 0.242

Conclusion:


association between Age and Monthly expenditure on the mobile connection. Since

Cramer’s V value is between 0.2 and 0.25, there is a Moderate association between Age and

Monthly expenditure on the mobile connection.

# To check association between Service Providers and Monthly Expenditure on the

Mobile Connection

SAS OUTPUT

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H0: There is no association between Service Providers and Monthly expenditure on the

mobile connection



Chi-Square 18 46.8657 0.0002

Likelihood Ratio Chi-Square 18 47.0402 0.0002

Cramer's V 0.1722

Conclusion:


association between Service Providers and Monthly expenditure on the mobile connection.

Since Cramer’s V value is between 0.15 and 0.2, there is a weak association between

Service Providers and Monthly expenditure on the mobile connection

# To check association between Occupation and Monthly Expenditure on the Mobile

Connection

H0: There is no association between between Occupation and Monthly expenditure on

the mobile connection



Chi-Square 12 91.5331 0.0001

Likelihood Ratio Chi-Square 12 95.5830 0.0001

Cramer's V 0.2406

Conclusion:

Since p-value is significantly low (i.e. <0.05). We reject H0 and concluding that there is an

association between Occupation and Monthly expenditure. Since Cramer’s V value is

between 0.2 and 0.25, there is a moderate association between Service Providers and

Monthly expenditure on the mobile connection.

Pareto analysis

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e26 The Pareto Analysis is used to determine which of the given factors influencing the

person’s in selecting a mobile phone service operator

The first five factors shows more than 75% of the variation.

Conclusion:

Hence, the most important factors influencing the person’s in selecting a mobile phone

service operator are:

Network Coverage where ever I go.

Data services/Internet.

Tariff/Pricing.

Transparency in billing.

Innovation/New services

Factor Analysis

To Understand the performance of different brands in the market on various

parameters like Product quality, Performance of the Customer Care

Executive(CCE),Service quality, Range and selection of products available we

consider following 12 variables:-

12 variables are:-

cc_hp = 'Customer care executives are helpful '

cc_kn_trif =' Customer care executives have complete knowledge of tariffs

& plans '

lodge_c = 'It is easy to lodge complaints with your mobile phone service

operator '

bill_acc = 'Billing system is accurate & transparent '

rghtser_1stt = 'Customer service executive performs the right service the

first time'

ser_res_pt= 'Service resolution is delivered within promised time '

Pag

e27 suf_net = 'My mobile phone operator provides sufficient network

coverage'

cdrop_less = 'Incidence of call drops are least '

vcliraty_gud = 'Voice clarity on my mobile network is good'

e_actvas = 'It is easy to activate a VAS service (Value Added Service)'

e_dactvas = 'It is easy to de-activate a VAS service (Value Added Service)'

intspd_gud= 'I get good internet speed (GPRS) on my phone '

Correlation matrix:

Original Eigen values and Proportion of Variance Explained:

Eigen values of the Correlation Matrix: Total = 12 Average = 1

Eigen value

Difference Proportion Cumulative

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e28

Original Rotated Component Matrix:

We remove the Variable with loadings less than 0.5.

Reduced Variables are:

cc_hp = 'Customer care executives are helpful '

cc_kn_trif =' Customer care executives have complete knowledge of tariffs & plans '

lodge_c = 'It is easy to lodge complaints with your mobile phone service operator '


rghtser_1stt = 'Customer service executive performs the right service the first time'


suf_net = 'My mobile phone operator provides sufficient network coverage'




KMO Statistics:

Since, Overall KMO value is 0.80443139 the sample size is adequate. Also, KMO value for

each variable is greater than 0.5, therefore the sample size is adequate.

1 3.4991 2.33885 0.2916 0.2916

2 1.1603 0.05301 0.0967 0.3883

3 1.1073 0.11763 0.0923 0.4806

4 0.9897 0.09926 0.0825 0.563

5 0.8904 0.06015 0.0742 0.6372

6 0.8302 0.14074 0.0692 0.7064

7 0.6895 0.05439 0.0575 0.7639

8 0.6351 0.05233 0.0529 0.8168

9 0.5828 0.01495 0.0486 0.8654

10 0.5678 0.03627 0.0473 0.9127

11 0.5316 0.01537 0.0443 0.957

12 0.5162 0.043 1

Since 1st 3 Eigen values are

greater than 1,we consider

only 3 factors for further

analysis. The 3 factors

together explains 48.06%

Pag

e29 Bartlett’s Test of Spherisity

Significance Tests Based on 527 Observations

Test DF Chi-Square

Pr >

ChiSq

H0: No common factors 66 1060.2 <.0001

HA: At least one common factor

Since, p-value is significantly low (i.e. <0.05). We reject H0 and conclude that there is at

least one common factor (i.e. Correlation Matrix is not an Identity Matrix)

Eigen values and Proportion of Variance Explained:


Eigen value Difference Proportion Cumulative

1 2.97021446 1.81091682 0.2970 0.2970

2 1.15929763 0.08386411 0.1159 0.4130

3 1.07543352 0.21278604 0.1075 0.5205

4 0.86264748 0.02359982 0.0863 0.6068

5 0.83904766 0.12096343 0.0839 0.6907

6 0.71808423 0.08164487 0.0718 0.7625

7 0.63643935 0.00373368 0.0636 0.8261

8 0.63270567 0.07172367 0.0633 0.8894

9 0.56098200 0.01583401 0.0561 0.9455

Since 1st 3 Eigen values

are greater than 1,we

consider only 3 factors for

further analysis. The 3

factors together explains

52.05%

Pag

e30


Eigen value Difference Proportion Cumulative

10 0.54514799 0.0545 1.0000

Scree Plot:-

Since 1st 3 Eigen values

are greater than 1,we

consider only 3 factors for

further analysis. The 3

factors together explains

52.05%

Pag

e31

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

1 2 3 4 5 6 7 8 9 10

Scree Plot

The scree plot shows that the graph starts to decrease after first 5 factors. This also

supports the analysis regarding numbers of factors

Unrotated Component Matrix:-

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e32

Factor Pattern

Factor1 Factor2 Factor3

cc_kn_trif Customer care executives have complete knowledge of tariffs & plans

0.68487 0.06996 -0.14609

lodge_c It is easy to lodge complaints with your mobile phone service operator

0.65248 -0.09633 -0.31636

ser_res_pt Service resolution is delivered within promised time

0.60597 -0.00494 -0.31166

cc_hp Customer care executives are helpfull 0.57725 -0.44895 -0.10650

rghtser_1stt Customer service executive performs the right service the first time

0.56763 -0.32749 -0.23358

cdrop_less Incidence of call drops are least 0.47116 0.38640 0.08402

e_actvas It is easy to activate a VAS service (Value Added Service)

0.47001 0.43502 0.11542

bill_acc Billing system is accurate & transparent 0.43185 0.62999 0.06106

suf_net My mobile phone operator provides sufficient network coverage

0.45734 -0.28416 0.64468

vcliraty_gud Voice clarity on my mobile network is good 0.46290 -0.14181 0.59266

To avoid cross loading we rotate the original component matrix using Varimax

rotation

Orthogonal Transformation Matrix:-

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e33

The SAS System

The FACTOR Procedure

Rotation Method: Varimax

Orthogonal Transformation Matrix

1 2 3

1 0.75765 0.52402 0.38906

2 -0.40755 0.84546 -0.34509

3 -0.50977 0.10290 0.85413

Rotated Component Matrix:-

Rotated Factor Pattern

Factor1 Factor2 Factor3

lodge_c It is easy to lodge complaints with your mobile phone service operator

0.69488 0.22792 0.01688

rghtser_1stt Customer service executive performs the right service the first time

0.68261 -0.00347 0.13435

cc_hp Customer care executives are helpfull 0.67461 -0.08803 0.28855

ser_res_pt Service resolution is delivered within promised time

0.62000 0.28129 -0.02874

cc_kn_trif Customer care executives have complete knowledge of tariffs & plans

0.56485 0.40301 0.11753

bill_acc Billing system is accurate & transparent 0.03931 0.76522 0.00276

e_actvas It is easy to activate a VAS service (Value Added Service)

0.11997 0.62597 0.13132

cdrop_less Incidence of call drops are least 0.15666 0.58223 0.12172

suf_net My mobile phone operator provides sufficient network coverage

0.13367 0.06574 0.82664

vcliraty_gud Voice clarity on my mobile network is good 0.10639 0.18366 0.73525

Pag

e34 The rotated component matrix helps to clearly segregate the factors among three different

components. As shown in the matrix, following three components can be formed

Conclusion & Recommendation

Age group, Occupation, Service providers, 3G connection all are

associated with Monthly Expenditure

Local call and Internet are the main services that should be focused by

service providers so that customers get benefited

The major service providers that satisfied the customers are Vodafone,

Airtel and Idea

The factors influencing the person’s in selecting a mobile phone service

operator are :

o Network Coverage

o Data services/Internet

o Tarif/Pricing

o Transparency in billing

Pag

e35

o Innovation/New services

The performance of service providers are depend on

o Customer care executive

o Comfort services

o Network services

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e36

R codes for association check and chi-square test.

Require(foreign); /*for adding package*/

sonu=read.spss("C:\\Documents and Settings\\chaurasiya\\Desktop\\project\\final.sav");

attach(sonu);

x= table(Occu,rs);

y= chisq.test(x);

SAS codes for association check and chi-square test.

ods html file="ChiSq1";

proc freq data=sonu.s;

tables _3g*rs / chisq;

tables mn_sim*rs / chisq;

run;

ods html close;

SAS code for Correlation Matrix

ods html file ='Matrix.htm';

PROC CORR DATA=sonu.s OUTP=sonucorr;

VAR cc_hp--intspd_gud;

RUN;

ods html close;

SAS and R Program Syntax

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e37 SAS code for Factor Analysis

ods html file ='Factor.htm';

Proc Factor data=sonu.factor METHOD=ml nobs=527 REORDER msa heywood res ;

var cc_hp cc_kn_trif lodge_c bill_acc rghtser_1stt ser_res_pt suf_net

cdrop_less vcliraty_gud e_actvas;

label

cc_hp = 'Customer care executives are helpfull '

cc_kn_trif =' Customer care executives have complete knowledge of tariffs &

plans '


operator '



first time'







intspd_gud= 'I get good internet speed (GPRS) on my phone ';

run;

ods html close;

ods html file ='Factor1.htm';

Proc Factor data=sonu.factor METHOD=principal nobs=527 REORDER rotate=varimax

scree res ;

var cc_hp cc_kn_trif lodge_c bill_acc rghtser_1stt ser_res_pt suf_net

cdrop_less vcliraty_gud e_actvas;

label

cc_hp = 'Customer care executives are helpfull '

cc_kn_trif =' Customer care executives have complete knowledge of tariffs &

plans '


operator '



first time'







intspd_gud= 'I get good internet speed (GPRS) on my phone ';

run;

ods html close;