Download - designing Customer Experience
Procedia Economics and Finance 11 ( 2014 ) 289 – 305
Available online at www.sciencedirect.com
2212-5671 © 2014 Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).Selection and/or peer-review under responsibility of Symbiosis Institute of Management Studies.doi: 10.1016/S2212-5671(14)00197-X
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Symbiosis Institute of Management Studies Annual Research Conference (SIMSARC13)
Enhancing Customer Experience using Business Intelligence Tools
with Specific Emphasis on the Indian DTH Industry Prof. Sujata Joshia *, Arnab Majumdarb, Archit Malhotrac
aAssistant Professor, Symbiosis Institute of Telecom Management, Pune bcStudent, Symbiosis Institute of Telecom Management, Pune
Abstract
The Direct to Home industry has emerged as the key driver for the Indian entertainment industry. In October 2011 the
Government announced implementation of a phase-wise digitization programme of pay TV services throughout the country. The
Indian Direct to Home industry is expected to grow by 50% in 2016. A few challenges faced by the Direct to Home Industry are
low Average Revenue per user (ARPU), high customer acquisition costs and high churn rate.
DTH Service Providers consider superior service experience as the key differentiator that will help them acquire new customers
and manage churn as well. Currently there is no standard available in the India market for DTH service providers to quantify and
improve its customer experience. Hence the objective of this paper is to formulate various constructs that helps to understand the
impact of different service attributes on customer experience for Direct to home customers using business intelligence tools.
© 2013 The Authors. Published by Elsevier B.V. Selection and/or peer-review under responsibility of Symbiosis Institute of Management Studies.
Keywords: Customer Experience, KANO’s quadrants, Hub & Spoke, Satisfaction Loyalty Grid., BI tools
* Corresponding author.
E-mail address:[email protected]
© 2014 Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).Selection and/or peer-review under responsibility of Symbiosis Institute of Management Studies.
290 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
1. Introduction
India is the third largest TV market after the US and China with 155 million subscriber households in 2012, TV
signals in India are currently distributed in analogue as well as in digital and terrestrial formats. Most cable
operators in the country are providing analogue TV service while all DTH operators are providing a digital TV
service. The government of India amended the Cable Television Networks (Regulation) Act in October 2011 to
announce implementation of a phase-wise digitization programme of pay TV services throughout the country and
hope for complete digitalization by end of 2014. The main reasons driving the growth of Direct to Home services
are the progress in technology, increased overall value proposition, and simplified yet enhanced consumer's
television viewing experience. Another important catalyst for growth of DTH is customer service since it is a key
differentiator between the DTH players and the unorganized service providers. A few challenges faced by the Direct
to Home Industry are low Average Revenue per user (ARPU), high customer acquisition costs and high churn rate.
DTH Service Providers consider superior service experience as the key differentiator that will help them acquire
new customers and manage churn as well. Currently the rate of churn for the DTH industry is 14-16%. Thus, it is
essential to develop effective methods to retain the existing customers which include two major steps. One is to
manage the customer experience and second is to generate service value for the customers. Customer experience is
defined as the sum of all experiences that a customer has at every touch-point of the customer-company relationship.
It is an intentional effort on the part of the company to develop and maintain good experience which is differentiated
from the competition, consistent at every touch point and most importantly valued by the customer. Currently there
is no standard available in the India market for DTH service providers to quantify and improve its customer
experience. Hence the objective of this paper is to formulate various constructs that help to understand the impact of
different service attributes on customer experience for Direct to home customers using business intelligence tools.
This solution can be used to enhance the quality of service, deliver better service experience to the customers. This
in turn will influence customers’ loyalty for their brands as well as have a positive impact on their intent to spend
and recommend the brand.
2. Methodology
Exploratory interviews were conducted on 440 customers in order to define the important attributes that affect the
customer experience for Direct to Home Service customers.
Statistical tests like crosstabs, correlations, binary logistic regression and cluster analysis were performed to help
carry out the analysis. This analysis helped to model the KANO’s quadrants, Hub & Spoke. A descriptive analysis
on the intent to spend, recommend and overall experience was carried out to compute a loyalty score for the
customers.
291 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
3. Contribution to the body of knowledge
The research adds to the body of knowledge by analysing the constructs that help understand churn, complaint
handling, & customer behavioural patterns for DTH services. It also gives insights on how better customer
experience impacts customer behavioural patterns: intent to spend, recommend the brand, analyse churn behaviour
and increase customer loyalty.
4. Literature Review
Experience has been increasingly discussed since the beginning of 2000 (Caru and Cova 2007), but it is rarely
defined. Sundbo and Hagedorn- Rasmussens (2008) defined Customer Experience as the customer’s direct and
indirect experience of the service process, the organization, and the facilities and how the customer interacts with
the service firm’s representatives and other customers. According to them, Customer experience is one of the major
factors influencing the consumer’s process for purchase decision. In the opinion of Davidson (1992) customer
experience is a method of creating a differential advantage for establishing customer’s loyalty.
Barlow and Maul (2000) have suggested that as per the experience economy philosophy, customers expect a
positive, emotional and memorable experience at every touch-point or transaction with an organization. The
customer experience economy as per O’Sullivan and Spangler (1998, p. 326) refers to individuals or firms whose
main purpose is to create such an experience that it will result in differential advantage and benefit for the
customers. According to Hongxiang (2011) quality of experience is one of the most important factors that will result
in satisfaction of the customers. Statistics has proven that about 82% of the users churn to another network because
they are not satisfied with the service quality given by the service provider, and 90% of them leave without
complaining to the customer care department. At the same time, one customer can convey the dissatisfaction to 13
other customers, which may have a bad effect on the service provider’s brand.
The research done by Belk et al.’s (1989) stresses on the importance of understanding the factors affecting
experience of the modern consumer. Similarly, Thompson et al. (1990) have also reiterated the fact that researchers
should do a study on customer experiences. Michela Addis (2005) have defined consumption as a result of the
experience which the customer gets after having a series of interactions of the product or service provided by the
organization. Van Der Wagen (1994) and Katz (1968) are of the opinion that different customers may have different
perception of experiences for a given product or service because each customer is unique in his understanding and
analysis given the fact that each one of them comes from a different educational, cultural background. Blythe (1997)
reiterates a similar opinion by saying that consumers analyze purchase decisions as a result of their previous positive
experiences.
From the literature review as stated above, customer experience has been studied across various sectors but very few
studies have been done with respect to customer experience in the Direct to Home services especially in India as this
sector is in the nascent stage.
292 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
Thus the present study adds to the body of knowledge by analysing the constructs that help understand churn,
complaint handling, & customer behavioural patterns for DTH services. The research helps to analyse service
attributes that enhance customer experience for DTH services. It also gives insights on how better experience
impacts customer behavioural patterns: intent to spend, recommend the brand and analyze churn behaviour. Finally
it was observed from the research that vulnerable customers do become loyal after receiving better service
experience.
5. Conceptual framework and Analytical Constructs:
Three major analytical constructs were considered for the purpose of this study, the Kano’s model, Hub & Spoke
Analysis, Satisfaction-Loyalty Grid:
The analytical constructs i.e. KANO’s model & Satisfaction Loyalty Grid has been implemented with reference to
an article, “Adding Value to CSM: The Kano Model” by Michael Lieberman for the World Advertising Research
Centre.
They are explained as below.
5.1. KANO’s model implementation:
Kano analysis is, in principle, a measure of the importance of the features to the customer, and the performance
of the business. The KANO’s Grid is formulated taking into consideration the stated importance of service
attribute as responded by the customer & the derived importance that is the correlation between overall
experience of the customer & the service statements.
It defines the service parameters in the following way:-
Must be’s:- The service attributes without which the experience is incomplete
Satisfiers: - The attributes of high stated importance formulating the key drivers of service experience.
Indifference: - The attributes of least importance to customer can form minor areas of opportunity
Exciters: - The unexpected parameters which invariably increase the service experience
5.2. Hub & Spoke Analysis:
This area of analysis helps to quantify the customer behavioural patterns with respect to a unit increase in the
customer experience index score. The statistical technique used is Binary Logistic regression which indicates
the exponential increase or decrease in the key business drivers.
5.3. Formulating the Satisfaction-Loyalty Grid:
293 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
e The grid segregates the customers into four major segments based on Individual satisfaction levels i.e. the
measure of customer experience index & Loyalty score i.e. defined as the average score of overall experience,
intent to recommend & intent to purchase more. It demarcates the following customer segments:-
• Champions: - Highly satisfied & loyal customers of the service provider
• nSwitchers: - Customers having high satisfaction scores but are equally likely to churn
• Captives: - Customers are loyal to the have low satisfaction levels
• Antagonists: - This segment probably has had bad experience with the DTH provider
The shift in customer behavioural pattern i.e. a shift towards brand loyalty is observed by carrying out Cluster
analysis. The predictors to observe customer movement were customer experience score, overall experience,
monthly spend, recharges per year & people referred.
Figure 1: Satisfaction-Loyalty Grid
6. Formation of Hypothesis
The review of literature gave deeper insights into the attributes or parameters affecting customer experience for
DTH services. For hypotheses formulation in this study researcher has considered:
• H1 = Parameters like Advertisements, regular payment alerts, trustworthiness, variety of channels packages
have different levels of impact on the overall customer experience
• H2 = Better customer experience impacts customer behavioural patterns
• H3 = Customer Experience drives customer loyalty
294 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
7. Research Methodology:
7.1. Research Design
This study aims to build an outline to enhance customer experience for the DTH service providers. The study takes
into account certain analytical constructs, implemented with the help of business intelligence tools, SPSS &
Microsoft Excel.
Figure 2: (Hypothesis: Input-Statistical Constructs; Output-Enhancement of CE)
7.2. Primary research and sample size
Primary research was conducted on a sample size of 440 DTH customers in City of Pune, Maharashtra. The
respondents were administered a structured questionnaire.
The responses were recorded using a set of 25 service attributes measured on an importance & performance scale in
addition to other relevant information required for segmentation analysis. These attributes considered were extracted
from literature review and with specific reference to DTH customer life cycle. The importance measure is the degree
to which a service attribute is essentially critical to the customer. The performance measure indicated the experience
the customer receives at service delivery by the DTH provider.
For the primary data collection, a questionnaire was formed consisting of two sections
295 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
• Section A: consisted of questions related to service attributes. The importance and performance of these
attributes were determined on a scale of 1-7. An additional question was asked to be able to quantify the
overall experience of the customer on the same scale.
• Section B: consisted of questions used for the segmentation analysis of the customers. Data on their
monthly spend, intent to spend, intent to recommend and intent to churn was captured. Additional
information related to the use of additional services and interactive services were also captured.
Figure 3: Research Steps
8. Statistical Analysis
Descriptive, Predictive and Prescriptive analysis of the data obtained was carried out. Statistical analysis tool SPSS
was used to help construct the above mentioned objectives. Several statistical tests like crosstabs, correlations,
binary logistic regression and cluster analysis were performed to help carry out the analysis. This analysis helped to
model the KANO’s quadrants, Hub & Spoke. A descriptive analysis on the intent to spend, recommend and overall
experience was carried out to compute a loyalty score for the customers. These customers were then segmented in
the satisfaction loyalty grid to understand their behavioural patterns.
e The objective with which the research analysis was carried out was to enhance the DTH customer experience. The
following opinions were kept into picture:
1) t Classify service attributes & determine what it takes to positively impact customer satisfaction. The construct
used was KANO’s model.
296 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
2) Understand the impact of a better experience on customer behavioural patterns. The construct used was Hub &
Spoke analysis.
3) Observe customer behaviour: A shift towards brand loyalty. The construct used was formulating a Satisfaction
Loyalty Grid.
The analytical tools and techniques involved, give various predictive measures to formulate business strategies &
& decisions such as improving customer delight, enriching the customer experience most of all retaining customers &
improving loyalty & customer base.
Note: -The analytical constructs i.e. KANO’s model & Satisfaction Loyalty Grid has been implemented with
reference to an article, “Adding Value to CSM: The Kano Model” by Michael Lieberman for the World Advertising
Research Centre.
Bad Experience18
19%
For BetterServices/Offers
4546%
Price22
23%
Moving to OtherLocation
55%
Others6
6%
Blanks1
1%
REASONS TO CHANGE
Figure 5: % & No. of people planning to switch
Yes9799999997979797979797
22%22%22%22%22%22%22%22%22%22%22%22%22%22%22%22%22%22%22%22%22%22%22%22%22%22%22%22%22%
Noo34378%
PLANNING TO CHANGE
Figure 4: Reasons to switch (% & No.)
297 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
OUTCOME OF ANALYSIS: Part 1
The analytical constructs help understand churn, complaint handling, & customer behavioural patterns
Analysis related to churn:Analysis related to churn:
After carrying out the sample survey, the first objective was to observe the sample behaviour. The major focus was
to observe the churn behaviour. This study shows that 22% of the sample wants to churn from their current service
pprovider. The top reasons were: to receive better service and pricing issues.
Analysis related to complaint handling:Analysis related to complaint handling:
In this study complaint analysis was carried out. fFrom the sample of 440 customers a big sample of population of
approx. 260 customers were facing issues in these areas. The graph indicated top six reasons for complaints. It was
observed that maximum customers had issues regarding signal, the second most important complaint was related to
bbilling followed by and service activation/deactivation, relocation on service issues and then payment related issues.
Complaints and churn go hand in hand.
y Customer dissatisfaction leading to churn has become a very major issue for the DTH service providers. The study
uses business intelligence to work out on these loop-holes, chalk out on strategies and identify the potential of the
market.
Figure 6: Major areas of complaints
SignalIssues
Billing/Rechar
geIssues
Service Activati
on/Deactivation …
Product/Offers Issue
Relocation
ServiceIssues
Payment
Issues
Series1 111 39 34 28 24 2339 34 28 24
111
3939 3434 2828 24 23
020406080
100120
Cust
omer
s
ISSUE OF COMPLAINTS
298 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
Analysis related to increase customer spending and impact on DTH services:Analysis related to increase customer spending and impact on DTH services:
The research shows the impact of customer experience on reducing churn and influencing customers to increase
spending. It also builds up customer loyalty. It has been observed in the sample behaviour that customers in the
monthly income group of 50K-80K have received the highest experience and thus having the highest intent to spend.
Figure 7: CEI v/s Customer Behaviour; Segment: Various Income Groups
The dive into the study also provides deeper insights on exploring the cross-sell and up-sell opportunities. There is a
r huge demand for internet in TV. Other observations show an immense potential for the digital video recorder
market. 20.7% of the customers use interactive DTH services. This is a huge business opportunity.
Figure 8: % of sample using add-on services Figure 9: % of sample using additional services
This study thus provides a solution not only to manage customer’s trust for their brand, but also provide insights on
Less than Rs.
3000
Rs. 3000-6000
Rs. 6000-15000
Rs. 15K-30K
Rs. 30K-50K
Rs. 50K-80K
More than Rs. 80000
CEI 7.13 7.03 7.36 7.17 7.08 7.71 7.497.03 7.36 7.17 7.08 7.71
Average CEI 7.35 7.35 7.35 7.35 7.35 7.35 7.35
Ready to Spend More% 59.38% 59.09% 59.09% 35.00% 43.75% 75.25% 61.54%59.09% 59.09% 35.00% 43.75% 75.25%
Planning to Change% 12.50% 27.27% 18.18% 23.33% 23.96% 18.81% 25.00%
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Income v/s Behaviour
Internet, 3III tI tI tI tInterInterInterInteInteInteInteInteInteInteInteInteInteInteInteInteInteInteInteInte2.05%222222E-EEEEEEEEEE-----
Commercrcccccccce, 7.27%
Social Networkinnnnnnnnnnnnnnnnnninining, 11.82%2%2%2%2%2%2%2%2%2%2%2%2%2%2%2%2%2%2%2%2%2%2%2%2%2%%
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ADDITIONAL SERVICESI ii Parental Lock, 7.
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DemandDDDDDDDDDeDeDeDeDeDeDeDeDeDeDeDeDeDeDeDeDeDeDeDe, 9.55%999999999999999999999, 9, 9, 9, 9, 9, 9, 9, 9,,,,,
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Active iA iA iA tiA tiA tiA tiActi eActiveActiveActiveActivectivectivectivetivetivetiveiveveveeContent, 1.14%
3D Channels, 4.09%
DVR, 19.09%
ADD-ON SERVICES
299 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
which other opportunities to explore and enhance upon the quality of service.
Part 2: OUTCOME OF STATISTICAL ANALYSIS (Part 2)
1) KANO’s Analysis
The distribution of various parameters into various segments of the grid is arrived at by creating a plot between (X-
axis as Stated Importance; Y-axis as Derived Importance). The following table indicates the Stated Importance &
the Derived Importance values. The derived importance is arrived at by performing a cross-tab correlation between
the overall experiences of the customer with the 25 service attributes considered.
Parameters Stated Importance Derived ImportanceAdvertisements 0.71 0.15 Promotions 0.74 0.22 Plans & offers 0.81 0.20 Pricing is value 0.81 0.27 Trustworthy operator 0.81 0.31 Variety of Channel Packages f 0.83 0.01 I feel valued customer 0.74 0.25 First time installation 0.79 0.12 Activation of first time services 0.82 0.20 Behaviour of installation staff 0.80 0.23 Picture & Audio Quality 0.84 0.31 Continued Service in heavy rains 0.79 0.26 User Friendly equipment 0.79 0.23 Experience of change in service 0.77 0.22 Experience in Relocation of services 0.77 0.17 Dealers are widely spread 0.78 0.31 Experience at Outlets 0.74 0.20 Interactive website 0.77 0.18 Customer Helpline easy Access 0.79 0.15 Helpline staff are polite & courteous 0.81 0.26 Queries solved efficiently & quickly 0.80 0.21 Maintenance & Repair Options 0.81 0.27 Accurate (Fair) Charge deduction 0.81 0.22 Regular payment alerts 0.78 0.27 Recharge Flexibility 0.82 0.30
Table 1: Service Parameters with corresponding Values of Stated & Derived Importance
300 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
Figure 10: Kano's Grid; Ref: Paper by Michael Lieberman
9. Hypothesis Testing & Inferences
H1 = Parameters like Advertisements, regular payment alerts, trustworthiness, variety of channels packages have
different levels of impact on the overall customer experience
The hypothesis H1 is thus evidenced by the following findings indicating the impact of service level attributes on
customer experience:
•• The Performance Attributes i.e. trustworthy operator, picture & audio quality, recharge flexibility,trustworthy operator, picture & audio quality, recharge flexibility,
bbehaviour of customer care staff has a concentrated impact on customer experience & business
performance.performance.
•• Parameters like promotions; value to the customers ®ular payment alerts provide additional satisfaction
& add to the surprise factor to the customers & make the customers more loyal to the brand.
•• The Must Be Attributes, like Accurate billing, plans and offers, channel packages are the compulsory
requirements of customers. They must provide a higher level of experience or else would result into
dissatisfaction & thus churn in the system.
•• Interactive website, Relocation of service, Advertisements may have an impact on decision making but do
not add up the experience.
301 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
Managerial Implications:
Customer experience can be enhanced by winning customer trust & providing value for services. 2) Hub & Spoke Analysis
This analysis helps to study the impact of enhancing the customer experience by 1 unit onto the key business
drivers. The statistical technique, Binary Logistic Regression, is used to evaluate relationships between a
dichotomous dependent variable and metric or dichotomous independent variables. It is used to estimate the
probability that an event, forming part of the defined groups, will occur in accordance to the change in the
independent variable.
Hence the following table depicts the incidence of change in the behavioural patterns by enriching the customer
experience by 1 unit. The positive sign indicates an increase in intention to recommend, purchase & spend, while the
negative sign indicates a decrease in intent to churn & reduced complaints.
Hypothesis Testing &Inferences:
H2 = Better customer experience impacts customer behavioural patterns
The hypothesis H2 is ascertained by following insights
The key business drivers as depicted are positively impacted if the customer experience is increased by a unit level.
Areas of opportunity, positive word of mouth, saving costs are some factors that every service provider looks for
today. This analysis gives a clear insight on the changes in customer behavioural patterns & quantifies the same.
Table 2: Business driver with Statistic Value exp(B)
Business Driver Impact: Value of exp(B) Intent to Recommend +1.050 times Intent to Purchase +1.217 times Intent to Change operator -1.023 times Intent to Send More +1.254 times No. of Complaints raised -0.068 times
302 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
Figure 11: Hub & Spoke (Behaviour & Corresponding Changes)
Managerial Implications: Enhancement in customer experience will result into following:-
Unit Increase in CEI Effects on business
Table 3: Business effect of Enhancement in CE
3) Satisfaction-Loyalty Grid
The grid divides the customers into various segments & is arrived at by a plot between (X-axis being loyalty score &
Y-axis being the individual experience index scores). The Loyalty score is the simple average of responses to three
major questions, the overall experience, the intention to recommend, & the intent to purchase more. The satisfaction
scores are arrived at by applying the weighted average technique on the importance & performance scores obtained
on the 25 service statements.
Chances of RecommendationLess Customer ChurnSpend More for better servicesLess complaints raisedPurchase more services
Increase in Positive PublicityHigher Satisfaction ScoresMore Revenue OpportunitiesLess Customer Care CostMore Cross-Sale; Up-Sale
303 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
Hypothesis Testing &Inferences:
H3 = Customer Experience drives customer loyalty
The need of the hour is customer segmentation, so that strategies can be focused on enhancing customer experience.
This analysis gives an insight on similar lines, Champions being the most loyal & most satisfied segment is the
desired category. 42.05% of the surveyed sample is highly satisfied and loyal. 35.23% of the customers are
vulnerable. After running through Cluster analysis it was observed in the satisfaction loyalty grid that the size of
champions category increased by 2.75%.A shift in customer behavioural pattern has been observed. On receiving
better experience customers migrate from the vulnerable category to the loyal and satisfied category.
Managerial Implications:
The vulnerable segment i.e. approx. 9% (Switchers)& 26% (Antagonists).Needs to be catered so as to increase their
experience levels &win their loyalty to make them more valuable to the business, increase the customer base, spread
a positive word of mouth, & in turn enhance business performance. The intent is to move the captives to the
champion’s category & win the confidence of antagonists.
Antagonists11326%
CaptivesCCC tC tCCCapCapCapCapCapCapCapCapCapCapCapCapCapCapCapCaCaCaCaCaCaCa10023%
Switchersi hS i hS i hi hit hit hit hit hitcherswitcherswitcherswitcherswitcherswitchersitchersitchersitcherstcherstcherstcherstcherscherscherscherscherschershershershershers429%
Champions18542%
CUSTOMER CATEGORIES
Figure 12: Customer segments; Ref: Paper by Michael Lieberman)
304 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
10. Limitations of the Research:
•• Sample size -- The number of the units of analysis was small. Open to more advanced & wider data
collection.
•• Availability of data -- Reliable & sufficient data from the DTH service providers will give a more clear
understanding of the trends in the services & experiences.
•• Limited Demographics -- The study was limited to students, professional & employees, only in Pune area.
An increase in sample size & varied demographics would provide a more heterogeneous sample.
•• Rural coverage -- The rural areas have not been covered & would formulate a wider scope for future
research.
11. Findings and Conclusions:
The research findings can be used by Direct to Home service providers while formulating their churn management
strategy, customer experience strategy, while formulating their marketing strategy as well as their customer retention
strategy. The findings of this research convey a strong message to Direct to Home service providers that
Customer experience can be enhanced by winning customer trust & providing value for services. Performance
attributes like. Trustworthy operator, picture & audio quality, recharge flexibility, behaviour of customer care staff
has a concentrated impact on customer experience & business performance. Parameters like promotions; value to the
customers & regular payment alerts provide additional satisfaction & add to the surprise factor, and make the
customers more loyal to the brand. The Must Be Attributes, like Accurate billing, plans and offers, channel packages
are the compulsory requirements of customers. They must provide a higher level of experience or else would result
into dissatisfaction & thus churn in the system. Interactive website, Relocation of service, Advertisements may have
an impact on decision making but do not add up the experience.
The research findings also show theta unit increase in customer experience will lead to 1.05 times increase in the
intent to spend, 1.21 times increase in the intent to purchase, and 1.25 times increase the intent to spend more.
This will help the managers to enhance their business as the chances of recommendation will increase leading to
increase in positive publicity. Secondly, Customer churn will be reduced leading to higher satisfaction scores
leading to customer retention. Thirdly, increase in customer spending will lead to more revenue opportunities. Also
as customers are willing to spend more, chances of cross-selling and up-selling will be more. Lastly, lesser number
of complaints will lead to lesser spend on customer care cost.
The research findings based on the satisfaction loyalty grid show that on receiving better experience customers
migrate from the vulnerable category to the loyal and satisfied category. This conveys a strong message to the
managers that the vulnerable segment i.e. approx. 9% (Switchers) & 26% (Antagonists) needs to be catered so as to
increase their experience levels & win their loyalty to make them more valuable to the business, increase the
customer base, spread a positive word of mouth, & in turn enhance business performance. The intent is to move the
305 Sujata Joshi et al. / Procedia Economics and Finance 11 ( 2014 ) 289 – 305
captives to the champion’s category & win the confidence of antagonists.
12. Scope for Future Research:
• The survey & analysis can be completed on a larger scale to include more customer & industry insights.
• This tested study can further be applied to other telecom verticals such as broadband & mobile.
• Can be used as a consulting solution for service providers.
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