Indian Mobile

7/30/2019 Indian Mobile

1/15

ePROCEEDINGS FOR 2011 INTERNATIONAL RESEARCH CONFERENCE AND COLLOQUIUMContemporary Research Issues and Challenges in Emerging Economies

259

DETERMINANTS OF CUSTOMER CHURN BEHAVIOR ON

TELECOM MOBILE

Ms. Rajewari, P.S

Asst. Prof., School of Management, SRM University, [email protected]

Dr. Ravilochanan, PProfessor, School of Management, SRM University, Kattankulathur

[email protected]

ABSTRACT

Mobile telecommunications customers are becoming more mobile every day, cancelling contracts

and switching providers at the first sign of discontent. Customer churn happens to be the most

challenging issue for mobile industry irrespective of their rapid growth. The rate of attrition with

regard to the subscribers are also growing vibrantly and the churn rate (i.e. the rate at which a

subscriber switches his/her operator) is expected to exceed 59% in 2013 from the current rate of53%.Churn rate increases pungently in parallel to the growth of mobile subscribers. As churn cuts

across all areas of an organization, the key to successfully reducing customer churn lies in

adopting holistic, modular approach. Customer retention, therefore, is becoming critical to retain

customer base. In this regard it is essential to infiltrate the basis for switching of the mobile users

in India.

KEYWORDS- Churn management ,Telecom analytics, Customer value, customer lifecycle

analysis, Market Basket analysis, Customer profiling, Data mining, customer focus groups, Mind

mapping, up selling, cross selling, switching cost

INTRODUCTION

Back ground :

The Indian telecommunications Industry is one of the fastest proliferating sectors in the World and

India is projected to be the second largest telecom market globally by 2011. Indicators are clearly

representing the increased competition and that induced the customers to hop for low cost

options1. This in turn entangled with disloyalty and as the industry saturates, it become imperative

for the mobile operators to shift their focus from rapid acquisition strategies to strategies which

helps to maintain and enhance margins from existing customer base.

The highly competitive scenario is characterised by mobile users switching cellularproviders. While teenagers are attracted by goodies such as free SMS, for executives it is the

free long distance minutes and value-adds. Though gaining new customers is good news for anytelecommunications, the flip side is the loss of customers or churn, in industry parlance. Somobile companies are putting churn management systems in place, which helps to predict thebehaviour of fickle customers. In simple terms churn refers to customers cancelling their existing

1http://www.destinationcrm.com/Articles/Web-Exclusives/Viewpoints/The-Secret-to-

Successful-Customer-Analytics-43814.aspx
http://www.destinationcrm.com/Articles/Web-Exclusives/Viewpoints/The-Secret-to-Successful-Customer-Analytics-43814.aspxhttp://www.destinationcrm.com/Articles/Web-Exclusives/Viewpoints/The-Secret-to-Successful-Customer-Analytics-43814.aspxhttp://www.destinationcrm.com/Articles/Web-Exclusives/Viewpoints/The-Secret-to-Successful-Customer-Analytics-43814.aspxhttp://www.destinationcrm.com/Articles/Web-Exclusives/Viewpoints/The-Secret-to-Successful-Customer-Analytics-43814.aspx


2/15


260

contract only to embark on a relationship with a competing mobile service provider. Cut-throatcompetition has ensured that there is not much difference between the tariff plans offered bydifferent mobile operators. This is where customer service and value-added services come intoplay. If an operator doesnt anticipate market needs or does not provide value -added servicesoffered by the competitor, then the customer is likely to churn. It is highly critical for every telecommarketer to reckon customer profile, customer lifecycle and customer values through properCustomer Analytics and to sustain their Data warehouse.

Impact of the problem

Though many service industries are affected by the churn phenomenon, the problem is extremelyacute in the telecom industry, with customers joining and quitting in short periods. According toresearch firm Gartner, Indias churn rate is anywhere between 3.5 percent to 6 percent permonth, one of the highest in the Asia-Pacific region. Considering that the cost of acquiring a newcustomer is as high as Rs 3,000, the losses are immense.

Other dimension of the problem, the mobile operators have to update their technology to remainin the market, which warrants continuous investments. Investments in turn depend on therevenue from the business. If the customer churn keep on going at an alarming rate, then themobile operators will be constrained to limit their expansion plans and advancement of

technology. Over a period of two years, it will pose a threat to the business itself.

Customer churn and i ts sign i f icance

Research is all about Customer churn analytics focusing on Indian cellular market, is a processby which data from customer behaviour is aggregated and analysed to gain customer mind map,enabling each business to help make better and quicker business decisions. This information isused by the cellular businesses for direct marketing and customer relationship management.

Recent statistics depicts very high churn in this Industry, is mainly rooted by the Youth segmentHence this study of customer analytics is mainly focusing on Youth segment. It facilitates toassess the Customer profitability index and Customer lifecycle. Customer analytics enables anoperator to gain a better understanding of the variables that influence customer churn. It enables

the mobile operators to understand which customer is likely to leave and why, which in turn canhelp the company take the necessary measures to counter it.

Extract of customer analytics provides the telecom company with a sliced and diced view of thecustomer base, thereby empowering it to treat each customer differently as per needs. Thecustomer attributes typically considered in a churn analysis can be broadly categorised intocustomer demographics, contractual data, technical quality data, billing and usage data andevents-type data. The Predictive information enhances the cross selling and upselling processand also for Hybrid channels.

Subject Area

As the main focus is to ident i fy the determinants of churn behaviour of the custo mers,

data relating tocustomer profile, level of satisfaction, customer loyalty and their buying behaviorwith regard to mobile telecom providers are used.

RESEARCH METHODOLOGY

ProblemFocus

Mobile operators are constrained by the customer churn. This is inspite of introducing variousnew schemes with customer-friendly features which assure customer benefits. With the cost of


3/15


261

operations becoming a challenge, the increasing role of TRAI enforcing discipline among theoperators in terms of rates and regulation on operation, each mobile operator need to evolvestrategies to arrest churn rate. For this purpose, the operators have to understand and identifyfactors which influence the customer churn. As is always said the primary task of every businessis not only to find new customers, but most important is to retain the existing customers. Hence,study of churn rate will enable the mobile operators to design and implement strategies toachieve a higher rate of customer retention.

Research purpo se

The purpose of this research is to perform customer analytics for churn behavior by identifyingthe operational factors that are influencing customer buying behavior, level of satisfaction andloyalty with regard to Indian Mobile telecommunications.

Research Objective

Recent trend line shows the growth and prospects of youth marketing2 and especially in the fieldof Telecommunications, they are marking tremendous development. In any business, thefundamental rule is to retain the young customers, as that will ensure continuous business. When

indicators are highlighting very high churn rate in this Youth segment, the mobile operators haveto regularly assess the situation to protect their business. Hence this Research focuses on Youthsegment to help the operators to evolve suitable strategies to maintain a healthy customerretention. Hence this research has the following objectives :

1. To analyze the behavior pattern of Mobile users with respect to Youth segment.

2. To identify the factors influencing the customer churn with respect to Indian mobileoperators.

3. To determine the level of customer satisfaction with regard to their perceived productquality, services and values.

Research Design

Research design adopted for this study is Exploratory type of research.

Data col lection

The research uses both Primary and Secondary data.

Primary Data

Survey method was adopted for collecting the primary data. Questionnaire was designed in thestructured objective pattern, focusing on the Research objectives. Findings of the survey werealso cross verified through informal interviews with the mobile users.

Secondary Data

The secondary data had been collected from the earlier Research findings, scholarly reports,telecommunication reports, respective marketing departments of mobile operators and throughthe different sources of literature such as journals, , articles etc.

Sampling plan

2 http://www.mobileyouth.org/post/mobileyouth-tv-4/


4/15


262

Simple Random sampling has been adopted by the researcher

Sample size

To get a cross section scenario, the targeted respondents were classified in to three age groupsegments, Totally 200 respondents are selected within the age group of 18 to 34. (Of this 113

belonged to the age group 18- 23, 81 respondents were from the age group 23 to 25 andremaining 6 were above the age of 25). The sample distribution indicated that majority of therespondents belong to the youth segment [18 -25 yrs].

RELIABILITY & VALIDITY

Reliabi l i ty

Reliability is the consistency of a measurement. Through SPSS package, reliability was tested.The value of Cronbach alpha was 0.782 indicated the reliability of the questionnaire wassatisfactory.

Val idi ty

Internal and external validity were checked with the respective sources and every hypothesis isbacked by questions in the questionnaire so that they could be tested and measured.

Pi lo t stud y

The questionnaires were distributed to 30 of the samples to determine the research directives.

Process of d ata analysis

SPSS 18.0 for basic statistical analysis combined with Excel was used. Chi square method wasapplied for testing the hypothesis. For determining the level of satisfaction of the respondents,weighted average method was used. Multiple regression technique was also used to identify the

factors influencing the customer loyalty and churn behaviour.

In linear regression, the model specification is that the dependent variable, yi is a linearcombination of the parameters (but need not be linear in the independent variables)., n datapoints there is one independent variable: xi, and two parameters, 0and 1:

List of Variab les taken for the determin ing the factors in f luencing c ustomer loya l ty and

churn behavior :

Totally 9 Dependent variables and 13 Independent variables are taken for the analysis and theyare3,

Dependent variables:-1. Service quality-quality of phone calls(Y1)2. Service quality-quality of SMS (Y2)3. Service quality-quality of network(Y3)4. Service quality-quality of convenience & reliability(Y4)5. Service quality-quality of service centre and hotline(Y5)

3 www.bth.se/.../How%20to%20Promote%20Customer%20Loyalty
http://en.wikipedia.org/wiki/Linear_combinationhttp://en.wikipedia.org/wiki/Linear_combinationhttp://en.wikipedia.org/wiki/Linear_combinationhttp://en.wikipedia.org/wiki/Linear_combination


5/15


263

6. Service quality-Advertisement(Y6)

Independent Variables:-1. Satisfactory level over performance-in general(x1)2. Satisfactory level over performance-customer services(x2)3. Satisfactory level over performance-billing system /RCV(x3)4. Satisfactory level over performance-tariff rates(x4)5. Satisfactory level over performance-call connectivity(x5)6. Satisfactory level over performance-network coverage(x6)7. Satisfactory level over performance-subscription easiness(x7)8. Satisfactory level over performance-SMS, MMS, VAS(x8)9. Satisfactory level over performance-offers, discounts(x9)10. Satisfactory level over performance-internet services(x10)11. Satisfactory level over performance-ringtones, caller tones(x11)12. Satisfactory level over performance-social responsibility(x12)13. Satisfactory level over performance-ad and other promotional activities(x13)

In accordance with the extensive analysis on review of literature, the factors are listed below fortesting the hypothesis to identify their association. The operational definitions and variables are

summarized and represented below for the validation of research hypotheses.

Table-1 Operational defini t ion and measurement of variables

Variable Operational definition

(Research hypotheses)

Measurement Variables

Customer

Satisfaction

Perceived product

quality(H1)

Call quality

Coverage of area

SMS quality

Network quality

Perceived servicequality(H2)

The convenience and reliability of Inquiringphone fee system

Service quality of service center andhotline

Perceived customervalue(H3)

Rating price of given quality

Advertisements about corporate image

social responsibility


6/15


264

Defin i t ion and test ing of research h ypotheses

Operational variables are conceived as per the earlier research findings. Perceived productquality (H1) that can be measured by Call quality, Coverage of area, SMS quality and Networkquality . Perceived service quality (H2) can be measured by the convenience and reliability ofInquiring phone fee system and Service quality of service center and hotline. Perceived customervalue can be measured through Rating price of given quality, the Advertisements about corporate

image and their involvement on social responsibility.

H0 1: There is no significant relationship between customer loyalty and perceived productquality.

H0 2: There is no significant relationship between customer loyalty and perceived servicequality.

H0 3: There is no significant relationship between customer loyalty and perceivedcustomer value.

H0 4: There is no significant relationship between customer loyalty and demographicprofile of the respondents.

Statist ical tools

Descriptive statistics, data reduction tools, hypothesis testing tools, association and variationdetection techniques.

DATA ANALYSIS

Find ings

Data analysis was performed using SPSS 18.0 .The hypotheses formed above were tested usingChi square method and results are summarized below.

Table 2

Results of Hypoth eses tested

Null Hypotheses Chi square value Result

H0 1: There is no significant relationship between

DemographicsDemographic profile(H4) Gender

Income

Mobile Experience


7/15


265

customer loyalty and perceived product quality

H01

Call quality 255.800* All null hypothesesrejected

Coverage of area 160.550*

SMS quality 196.300*

Network quality 114.000*

H0 2: There is no significant relationship betweencustomer loyalty and perceived service quality

H02

The convenience and reliability of Inquiringphone fee system

106.700* Ho Rejected

Service quality of service center and hotline 104.350*

*at 0.05 significance level Source: Primary data

From the above table it is very clear that all the null hypotheses are rejected and so alternativehypotheses are accepted. It has been proved that customer perception on quality, services andvalues of the mobile service are influencing their buying behavior and creating impact oncustomer loyalty. Moreover gender, income, customization of the respondents also foundsignificant in sustaining the loyalty. So Marketers need to closely monitor youth attitudes towardsmedia, products, shopping, health, career, relationships and technology. Hence the option isparticipative marketing campaign to understand their perception on product attributes. Marketing

H0 3: There is no significant relationshipbetween customer loyalty and perceived

customer value.

H03 Rating price of given quality

Advertisements about corporate image

Social responsibility

167.950*

Ho Rejected117.500*

132.200*

H0 4: There is no significant relationship

between customer loyalty and demographic

profile of the respondents.

HO4

Gender 32.000*

Ho RejectedIncome level 39.050*

Mobile Experience 667.550*


8/15


266

campaigns should have functional, educational and emotional components built-in to successfullyto persuade the youth.

Having clarified the relationship among the selected variable the next was to ascertain the level ofsatisfaction of customers over the mobile service provided for mapping their mind. The followingtable portrays the level of satisfaction of the respondents.

Table 3

Frequency table represents the level of satisfaction of the respondents with respect to thevarious aspects of the Mobile telecommunications.

FactorsHighly

satisfied Satisfiedsomewhatsatisfied Dissatisfied

HighlyDissatisfied

Customerservices

13.0% 37.0% 36.5% 10.5% 3.0%

In General 16.5% 55% 25.5% 1.5% 1.5%

Billing-Rechargevouchers 21% 56.5% 18.5% 2.5% 1.5%

AD &Promotional

activities 15% 43% 29.5% 8.5% 4%

social

Responsibility 13.5% 40.5% 31% 12.5% 2.5%

Tariff plans 9% 36% 42.5% 9% 3.5%

callconnectivity 18.5% 45% 30.5% 6% 0%

Networkcoverage 18.5% 48% 24.5% 7% 2%

SubscriptionEasiness 9.5% 44.5% 36.5% 6.5% 3%

Value addedservices 17.5% 56% 19% 5.5% 2%

Offers anddiscounts 15% 43% 29.5% 10.5% 2%

Ringtones andcaller tones 4% 10.5% 26.5% 41% 18%

Internetservices 14% 38% 38% 9.5% 0.5%

Source: Primary data


9/15


267

From the above it is inferred that majority of the respondents have not been satisfied with theabove mentioned features of operators and it is imperative that the Telecom Operators have todesign the innovative promotional strategies for persuading the youth segment to attain thehigher level of satisfaction

The next step was to identify the determinants of customer churn in the mobile industry. For this

purpose first a basic study of the churn rate over the past five years was undertaken. Thedetailed are furnished in Table 4

Table 4

Circle wise Churn b ase of Mobi le segment f rom 2011 to 2007

Circle wise

Operators

Churn in2011( in

Crs)

Churn in2010( in

Crs)

Churn in2009( in

Crs)

Churn in2008( in

Crs)

Churn in 2007

( in Crs)AndhraPradesh 0.11 0.10 0.04 0.04 0.02

Assam 0.005 0.003 0.002 0.001 0.001

Bihar 0.03 0.03 0.01 0.04 0.00

Delhi 0.08 0.07 0.05 0.03 0.02

Gujarat 0.15 0.13 0.04 0.06 0.04

HimachalPradesh 0.01 0.01 0.02 0.02 0.00

Haryana 0.09 0.08 0.03 0.15 0.02

J&K 0.005 0.003 0.002 0.001 0.001

Karnataka 0.11 0.07 0.06 0.06 0.03

Kerala 0.06 0.04 0.003 0.002 0.01

Kolkotta 0.04 0.08 0.003 0.002 0.001

MadhyaPradesh 0.10 0.08 0.14 0.13 0.02

Maharashtra 0.10 0.09 0.07 0.06 0.02

Mumbai 0.07 0.06 0.003 0.002 0.02

North East 0.005 0.003 0.002 0.001 0.001

Orissa 0.03 0.03 0.06 0.05 0.00

Punjab 0.07 0.06 0.03 0.03 0.02

Rajasthan 0.12 0.11 0.11 0.10 0.02

Tamil Nadu 0.12 0.11 0.03 0.03 0.02

UP East 0.11 0.10 0.13 0.12 0.02

UP West 0.05 0.05 0.04 0.04 0.01

WestBengal 0.04 0.04 0.03 0.03 0.01

Source: Secondary data, Extracted from TRAI report 2011 to 2007


10/15


268

From the above table it is clear that the mobile churn is increasing along with the growth ofsubscription. In 2010-2011, the churn base is very crucial because of the implementation ofMobile Number Portability4. According to an estimate in2011, one in five of the worlds mobileowning youth will live in India a market that if considered as a standalone country would belarger than the entire population of the US. The growth curve in revenues, however, takes adifferent shape; youth mobile spend will plateau in 2012 as the market becomes saturated in the20-29 age group5.

Coupled with the knowledge on churn rate behaviour, a number of key facts have emerged fromthe analysis of churn rate in the past studies. These are summarized as under.

1. India is the worlds biggest mobile youth market (based on activations) with 281 millionaccounts (compared to China with 255 million)

2. The Indian youth mobile market is valued at $21 billion.

3.1 in 5 mobile owning youth will live in India by 2011

4.. The mobile youth market in India has reached saturation. Mobile penetration among 20-24year olds in India crosses 100% in 2010. Penetration rates among 25-29 year olds will cross100% in 2011. Indian Operators lose $6 Billion from Youth Churn and in 2010 as a result ofswitching, inactivity and secondary accounts. Nearly 145 million mobile youth accounts will bechurned in 2010 and Indian Mobile Youth Revenues Plateau at $24 Billion.

6 . Indian Youth mobile spend will plateau in 2012 as the market becomes saturated in the 20-29age group. ARPU of $6.5 for mobile youth in India is well below China's $10 figure. About 281Million Mobile Youth are in India; Mobile Youth in India will spend $7.7 billion on data in 2010 asper an estimate.

7. In 2010, operators will earn $7.7 billion from data usage by mobile youth in India. By 2012,youth in India will spend more than $9 billion on mobile internet usage 6.

Table 5

Critical Decelerators Influencing Customer Churn

Rank Decelerators

I Rington es and cal ler tones

II Social Respons ibi l i ty

III Customer s erv ices

IV AD & Prom otion al activi t ies, Tari ff plans, Offers anddiscounts

V Internet services

VI Subscr ip t ion Easiness

VII Network coverage

4http://en.wikipedia.org/wiki/Telecommunications_Statistics_in_India"

5http://www.mobileyouth.org/post/281-million-mobile-youth-india/6 ibid
http://en.wikipedia.org/wiki/Telecommunications_Statistics_in_Indiahttp://en.wikipedia.org/wiki/Telecommunications_Statistics_in_India


11/15


269

IX Value added s ervices

X cal l con nectivi ty

XI Bil l ing-Recharge vouc hers

XII In General

Source: Primary data

As the topic of the research is focusing on customer churn, the list of factors involved in customerdissatisfaction are percolated and ranked as per their percentage of influence. Hence the abovementioned table has been developed and extracted from Table 3. Respondents expressed theirhigher level of dissatisfaction on one particular factor called Caller and ring tones. As this surveyis on Youth segment, Mobile service providers have to concentrate this factor for tapping thissegment .They can come out with varieties of ringtones with promotional schemes as likeRecharge vouchers to impress with the youth segments. Telecom operators have to improvecustomer relationship design in a better way to establish their interest on social responsibility andto render robust customer care services. It is better to implement social awareness program and

rural welfare campaigns for building Corporate Telecom marketers have to improvise theirperformance in the areas of Internet services, and in promoting the Tariff plans effectively throughcertain offers. They can mind map their customers and based on that they can come out withdifferentiated marketing strategies in designing their tariff plans. They have to strengthen theirportfolio on customer services. Recent market survey indicates 97.3% of customer churnhappens due to poor customer services7. They have to strengthen them to enhance their Networkconnectivity. The secondary data had been collected from the previous Research findings,scholarly reports, telecommunication reports, respective marketing departments and through thedifferent sources of literature such as journals, articles etc.

Multiple Regression

Step 1:-Performed correlation, by taking each one of the dependent variables with all theIndependent variables and list of Independent variables extracted from the correlation matrix

whose value was below 0.5. This is mainly due to avoid multi-collinearity among the predictorvariables, as these extracted Independent variables are subjected to Multiple Regressionanalysis.Step 2:-By performing Multiple Regression for each Dependent variable, the list of Independentvariables are selected as per their statistical significance

Regression Equation 1

Y1 = 3.355 - 0.172*X1 (t =2.618) - 0.120NS

X2 (t=-1.945) + .028NS

X3( t = .402) + 0.044NS

X4 ( t =

.663) + 0.103NS X5 (t = 1.405) +. 0169* X6 (t = 2.557) - 0.101NS

X7( t = - 1.615) + 0.055X8 (t =

0.898) + 0.091NS

X9 (t = 1.504) - 0.009NS

X10 (t = - 0.150) + 0.110* X11 (t = 2.069) + - 0.012NS

X12 (t = - 0.184) + 0.050NSX13 (T = 0.855) + 0.363 F=2.933** ,R

2=0.170

Interpretation:-It is very Clear that service quality of Phone calls is influenced by three independent variablesnamely Satisfactory level on Overall performance (X1), Network coverage (X6) and on Ringtones(X11). Thus For every unit of change in Satisfactory level on Overall performance, Networkcoverage and on Ringtones influences, the service quality of phone calls by 0.172,0.169 and0.110 units respectively. Obviously when the service quality improves, the customers would

7 www.mobileyouth.org


12/15


270

prefer to retain the connection. When a customer buys a connection his minimum expectation isthat network coverage should be good and he also considers the type of ringtones should also benovel. By attending to these expectations of the customer, it is possible for the operators toimprove their customer loyalty rate.


Y2=2.417+0.096NS

X1 (t=1.357) - 0.075NS

X2 (t=-1.127) + 0.056NS

X3 (t=0.750) +

0.169*X4(t=2.381) - 0.020NS

X5 (t=-0.253) + 0.019NS

X6 (t=0.261) - 0.161* X7 (t=-2.394) + 0.245**

X8 (t=3.720) + 0.029NS

X9 (t=0.436) + 0.070NS

X10 (t=1.028) - 0.075NS

X11 (t=-1.306) + 0.099NS

X12 (t=-1.445) + 0.010NS

X13 (t=0.152) + 0.393 F=3.307**,R2=0.188

Interpretation:-The above regression equation captures the statistically significant factors which togetherinfluence the service quality of sms [Y2] Among the variables included for the analysis only 3turned out to be statistically significant viz., tariff rates(X4) subscription easiness(X7) SMS, MMS,VAS(X8) It is interesting to note that X 4 has a positive coefficient. The expected coefficient isnegative implying that the customers would not favour increase in tariff rate for getting servicequality. But in the current equation, the positive coefficient clearly indicate that the customers areprepared to accept even higher tariff rate if the service quality is good. So with every unitincrease in tariff rate improves the service quality of sms by 0.169 unit. Another way in which thiscould be understood is that if the operators enjoy the customer approval for higher tariff rate, theycan improve the service quality. One more observation is that as the operators make thesubscription payment easy, the service quality of sms goes down. Actually the expected symbolfor the coefficient is positive, but it is negative and statistically significant in the current equation.This means, when the payment of subscription becomes easy, more customers enrol but ifcorrespondingly the network coverage does not improve the service quality of sms goes down.Hence the operators should not merely address the subscription related issues, but also theprimary factor like network coverage. It could also be noted with every unit increase in the SMS.MMS and VAS offer, the service quality of sms improves by 0.245 units which helps to retain thecustomers.


Y3=2.055-0.108NS

X1 (t=-1..332) - 0.072NS

X2 (t= -0.944) + 0.066NS

X3 (t=0.790) + 0.0269** X4

(t=3.331) + 0.065NS X5 (t=0.728) - 0.042NS

X6 (t=-0..521) - 0.079*X7 (t=-1.030) - 0.006NS

X8 (t= -

0.080) - 1.41NS X9 (t=-1.896) + 0.469** X10 (t=6.094) - 0.044NS

X11 (t=-0.667) + 0.043NS

X12

(t=0.551) + 0.095NS

X13 (t=1.340) + 0.446

F=5.488**, R2=0.277

Interpretation:-Service quality of Network is influenced by satisfactory level on Internet services by the tariffrates, since for every unit of change in the satisfactory level of internet services inducing 0.4 units

of change in the service quality of network. As has been already stated, the customers would notmind paying more tariff for improving the service quality of network. Hassle free connection,uninterrupted connectivity, high speed downloading support, etc., would go a long way improvethe service quality of internet services, though this can happen only at a higher tariff rate.

It could be noted that with every unit increase in the subscription easiness, the service quality ofthe network goes down by 0.079 units. This is because, the easiness of subscription motivatesmore customers to buy the connection, but if the operators do not correspondingly improve thenetwork delivery, the service quality of network would go down. Similarly the service providershave to focus on the extent and range of internet services so as to exploit the advantage of


13/15


271

improving the service quality of the internet services. The equation indicates that every unitincrease in the satisfaction level of internet service adds to the service quality of the network by0.469 units.


Y4=1.648 -0.016

NS

X1(t=-0.170) +0.048

NS

X2(t=0.547) +0.354**X3(t=3.673) -0.001

NS

X4(t=0.014) -0.032NSX5(t=-0.307) -0.013

NSX6(t=-0.139) -0.038

NSX7(t=-0.428) -0.034**X8(t=-0.401) +

0.072NSX9(t=0.850) +0.215*X10(t=2.443) -0.047NS

X11(t=-0.622) +0.145NS

X12(t=1.625) -

0.060NSX13(t=-0.737) +0.511

F=3.244**, R2=0.184

Interpretation:-From the Equation it is clear that every unit increase in the satisfaction level of billing service willimprove the Service quality of convenience and reliability by 0.354 units. This clearlyunderscores the customers expectation about the accuracy, timely delivery, break up of all detailsconnected with the usage, realization of the earlier bills paid by the customer, etc By addressing

these aspects in billing service it is possible for every service provider to improve the servicequality of convenience and reliability. The billing system should also provide for redressal ofcustomer grievances and complaints so that the satisfied customers would retain theirconnection. Provision of support like sms, mms, vas, etc. help every customer to get the bestfrom the mobile connection. But if the service quality of this service is poor, the service quality ofconvenience and reliability suffers, as is evidenced by this equation. With every unit increase insatisfaction level of sms, mms, vas cause a 0.401 unit decline in the service quality ofconvenience and quality, as the operators do not improve their network coverage and relatedfactors along with the improvement in the offer of sms, mms, vas. This is only confirming thefinding earlier. The next statistically significant factor is satisfaction level of internet services[X10] This variable has a positive impact on the service quality of convenience and reliability asevery unit increase in it adds to service quality of convenience and reliability by 0.215 unit.


Y5=1.559 -.120NS

X1(t=- 0. 235) + .325**X2 (t=3.626) + 0.116NS

X3 (t=1.162) + 0.038NS X4

(t=0.395) +0.108NSX5(t=1.015) -0.199NS

X6(t=-2.078) -0..039*X7(t=-0.435) + 0.084NS

X8(t=0.945) -

0.009NSX9(t=-0.105) +0.079NS

X10(t=0.865) +0.034NS

X11(t=0.434) +0.014NS

X12(t=0.150) +

0.141NSX13(t=1.678) +0.528

F=3.920**, R2=0.215

Interpretation:-One of the essential requirements to achieve a higher service quality level of the service centersand hotline support is customer service. It is well known that in products like mobile operation anumber of customer contact point exists. Right from the sale of connection, sale of mobile

phones, complaint redressal, customer counselling, etc, customer contact is crucial. Customersin India expect that the service centre of the mobile operator should be available nearby theirresidence or office. Mere availability of the service centre is not sufficient. To what extent thepeople manning the counters in these service centres and the type and quality of customerservice offered there will determine the ultimate customer retention or churn. In the aboveequation, every unit increase in satisfaction level related to customer service improve the servicequality of service centres and hotline by 0.325 units. Once an operator realizes this, he / sheshould be careful in training the customer service personnel and improve the breadth and depthof service offering. Added to this, the quality of service centre is also impacted by subscription


14/15


272

easiness as shown by this equation. Though a positive sign is expected, the presence ofnegative coefficient indicates that any poor satisfaction level in subscription easiness, will cause adecline in service quality of service centre and hotline support. Hence, the operators need toaddress the issues connected with the satisfaction of subscription easiness so as to fully exploitthe vantage location of service centres and hotline.*at 0.05significance level ** at 0.01 significance level NS-Not Significant

Interpretation with results:

Customer analytics indicate the path way for the Indian Mobile for increasing the customer loyaltyand to turn around the churn rate. For that Indian mobile operators should:

(1) Keep their good performance on quality of phone call, coverage, quality of SMS and payattention on these three areas because they are in the first level ofcustomer rating which meansthey have great importance on customer loyalty.

(2) Improve their performance on customer service, advertisements about corporate image,inquiring phone fee system and corporate social responsibility and pay more attention oncustomer service.

(3) Develop the effective Customer Retention strategy to reduce the churn and to sustain thecustomer base.

CONCLUSION

The telecom industry, especially the mobile industry of India is undergoing a transformation andthe number portability is bringing about imperatives worthy enough to carry out high-endresearch. This study is one such attempt to enhance the exposure on customer analytics and it isalso expected to facilitate the marketers to design the essential operational parameters fordesigning the retention strategies and to enhance Customer Experience management.

REFERENCES

Fornell, C., & Johnson, M. D. (1996). The American customer satisfaction index: Nature, purpose,and findings. Journal of Marketing, 60, 7-19

Ahn, J. H., Han, S. P., & Lee Y. S. (2006). Customer churn analysis: Churn determinants andmediation effects of partial defection in the Korean mobile telecommunications serviceindustry, Telecommunications Policy, 30, 552-569.

Amine, A. (1998). Consumers true brand loyalty: the central role of commitment, Journal ofStrategic Marketing. 6, 305-319.

Anderson, E. W., & Sullivan, M. W. (1993). The antecedent and consequences of customersatisfaction for firms. Marketing Science, 12, 125-144.

Andreasen, A., & Drumwright, M. (2001). In: Andreasen, A. (Ed.), Alliances and Ethics in SocialMarketing in Ethical Issues in Social Marketing. Washington, DC: Georgetown UniversityPress.

Andres K. (2007). Affecting customer loyalty: do different factors have various influences indifferent loyalty levels? University of Tartu - Faculty of Economics & BusinessAdministration Working Paper Series. 58. 3-30.


15/15


273

Aydin, S. Ozer, & G. Arasil, O. (2005). Customer loyalty and the effect of switching costs as amoderator variable: A case in the Turkish mobile phone market. Marketing Intelligence &Planning.23. 89-103.

Bandyopadhyay, S. Martell, M. (2007). Does attitudinal loyalty influence behavioral loyalty. Journal of Retailing & Consumer Services, 14. 35-45.

Barich, H.,& Kotler, P. (1991). A framework for marketing image management, SloanManagement Review, 32, 94-104.

Bitner, M. J., & Hubbert, A. R. (1994). Encounter Satisfaction versus Overall Satisfaction versusQuality, Service Quality New Directions in Theory and Practices. London: SagePublications. 72-95.

Blodgett, J.G., Hill, D.J.,& Tax, S.S. (1997). The effects of distributive, procedural, andinteractional justice on post-complaint behavior, Journal of Retailing. 31. 185-210.

Documents

Indian Mobile