Evading Customer Benefits of CRM in Nigerian Telecoms

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Evading Customer Benefits: Irony of Customer Relationship Management (CRM)
Applications in the Nigerian Mobile Telecommunications Industry
Monsuru Babatunde Shittu
Student Number: 149053375
Subject Area: Management of Information Systems
Supervisor: Dr. Colin Price
Submitted: 30 June 2017
Dissertation submitted to the University of Leicester in partial fulfilment of the requirements of
the degree of Master of Business Administration

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TABLE OF CONTENTS
Page
ACKNOWLEDGEMENTS ............................................................................................................4
EXECUTIVE SUMMARY .............................................................................................................5
1. INTRODUCTION...................................................................................................................6
1.1. Chapter overview............................................................................................................6
1.2. Background.....................................................................................................................6
1.3. Existing literature ............................................................................................................7
1.4. Approach and contributions ............................................................................................8
1.5. Chapter summary ...........................................................................................................8
2. LITERATURE REVIEW.........................................................................................................9
2.1. Chapter Overview ...........................................................................................................9
2.2. CRM and its supporting technology ................................................................................9
2.2.1. Definition of CRM ........................................................................................................9
2.2.2. Role of Technology in CRM.......................................................................................11
2.2.3. CRM Applications in Telecoms..................................................................................12
2.2.4. Summary of CRM and its supporting technology.......................................................12
2.3. Objectives of CRM Applications....................................................................................13
2.3.1. Profit Advancement as priority objective....................................................................13
2.3.2. Customer satisfaction as priority objective.................................................................14
2.3.3. Equal priority for profit advancement and customer satisfaction objectives...............14
2.3.4. Summary of CRM Objectives ....................................................................................15
2.4. Structures Supporting CRM Applications......................................................................15
2.4.1. Success factors to the implementation of CRM applications .....................................15
2.4.2. Barriers to the implementation of CRM applications..................................................17
2.4.3. Summary of structures supporting CRM applications................................................18
2.5. Realisation of CRM applications’ benefits.....................................................................18
2.5.1. Benefits of CRM applications.....................................................................................19
2.5.2. Measurement of CRM applications’ benefits .............................................................19
2.5.3. Summary of CRM benefits realisation .......................................................................21
2.6. Chapter summary and theoretical framework ...............................................................21
3. DATA AND METHODS .......................................................................................................23
3.1. Chapter overview..........................................................................................................23
3.2. Research methodology.................................................................................................23
3.3. Design of research instrument ......................................................................................23
3.4. Data collection approach ..............................................................................................25
3.5. Data analysis approach ................................................................................................26
3.6. Chapter summary .........................................................................................................27

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4. ANALYSIS AND RESULTS.................................................................................................28
4.2. Broad analysis of responses.........................................................................................28
4.2.1. Background information.............................................................................................28
4.2.2. Participants consent ..................................................................................................30
4.2.3. Coding of responses..................................................................................................31
4.3. Priority objectives of CRM applications.........................................................................32
4.4. Effectiveness of CRM applications’ supporting structures ............................................35
4.4.1. Effectiveness of business factors ..............................................................................35
4.4.2. Effectiveness of implementation project factors.........................................................38
4.4.3. Effectiveness of technology factors ...........................................................................38
4.4.4. Effectiveness of people factors..................................................................................40
4.4.5. Effectiveness of data factors......................................................................................41
4.4.6. Summary of CRM applications’ supporting structures ...............................................41
4.5. Evaluation of CRM applications’ benefits......................................................................42
4.5.1. CRM applications benefits realisation........................................................................42
4.5.2. Extrapolation of responses ........................................................................................44
4.5.3. Summary of CRM applications’ benefits....................................................................45
4.6. Chapter summary .........................................................................................................46
5. DISCUSSION AND CONCLUSIONS ..................................................................................47
5.2. Research summary and conclusions ............................................................................47
5.3. Theoretical Implications ................................................................................................49
5.4. Practical Implications and recommendations................................................................50
5.5. Limitations.....................................................................................................................51
5.6. Directions for Future Research .....................................................................................51
5.7. Reflections....................................................................................................................52
5.8. Chapter summary .........................................................................................................53
REFERENCES ..........................................................................................................................54
APPENDIX A: THE PROJECT PROPOSAL..............................................................................62
APPENDIX B: RESEARCH ETHICS APPROVAL .....................................................................72
APPENDIX C: RESEARCH ACCESS........................................................................................74
APPENDIX D: PARTICIPANT INFORMATION SHEET.............................................................77
APPENDIX E: SAMPLE INVITATION TO PARTICIPATE IN MBA QUESTIONNAIRE..............79
APPENDIX F: QUESTIONNAIRE ..............................................................................................80
APPENDIX G: CRM IMPLEMENTATION INDEX BY CHINJE...................................................88
APPENDIX H: LIST OF FIGURES.............................................................................................90
APPENDIX I: LIST OF TABLES.................................................................................................91

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ACKNOWLEDGEMENTS
I will like to appreciate my supervisor, Dr. Colin Price, for providing apt and timely guidance to
me from the research planning stage till date.
I will also be forever grateful to my family for their understanding and support throughout the
MBA programme. Hameedat Shittu, thank you for listening to all my complaints and rantings on
the stress of the programme; Roqeebah Shittu, thank you for always asking me about how
many words are remaining in the dissertation; Raheemah and Yusrah Shittu, thank you for
being peaceful while I turned the home to school.
To my professional colleagues in the telecoms industry, especially Osayi, the dissertation work
could not have been completed without your input and I also say a big thank you for all your
support.
Monsur Shittu
June 2017

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EXECUTIVE SUMMARY
The objective of the research work is to understand the reasons why implementation of
customer relationship management (CRM) applications in Nigeria’s telecoms industry did not
translate to better benefits for organisations and their customers. This is with the view that only
clear understanding of the problem can lead to practical solutions. Motivation for this
dissertation is the negative customer perception of telecoms companies in Nigeria despite the
huge investment in CRM applications which are supposedly implemented to create a positive
customer impact. The research therefore sought to understand the priority objectives for
implementing CRM applications, the effectiveness of the application supporting structure and
the extent of benefits realisation from the implementation of the applications. This is with the
theoretical believe that with the right objective, effective supporting structure, periodic benefits
measurement and implementation of corrective actions, organisations can realise better
benefits from the implementation of CRM applications.
The research collected experience-based data from the employees of the mobile telecoms
operators in Nigeria via online questionnaire and analysed the data using frequency distribution.
Based on the analysis, meeting customers’ needs is the priority objective for implementing CRM
applications in Nigeria’s mobile telecoms industry while revenue improvement and cost
reduction are respectively the second and third objectives. The research also found CRM
application supporting structures such as customer vision, communication mechanisms, change
management, system integration, personnel training and data processing to be relatively
effective in achieving the CRM applications’ objectives. However, the research concludes that
improvement areas identified in order of criticality as CRM supporting processes, data storage
and mining, and CRM vision and strategy, need to be addressed by the mobile telecoms
operators in Nigeria to ensure realisation of better benefits from the implementation of CRM
applications.
The findings above present a clear understanding that the non-realisation of customer benefits
from CRM applications is not necessarily due to the lack of customer objectives for
implementing the applications. Another theoretical and practical implication is that the CRM
Implementation Index (Chinje 2013) validated in the research can now be used at the pre and
post implementation stages of CRM applications to minimise the evasiveness of customer
benefits in the implementation of CRM applications in Nigeria’s telecoms industry and beyond.

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1. INTRODUCTION
1.1. Chapter overview
This chapter sets the tone for the research on benefits realisation of customer relationship
management (CRM) applications by providing the basis and context for the research. The
chapter also provides an overview of the existing literature in the research area and the
proposed approach and expected contributions from the research.
1.2. Background
According to Ledingham and Rigby (2004), the main essence of implementing CRM
applications in organisations is to provide efficient and quick response to ever dynamic
customer needs. This implies that successful implementation of CRM application should
translate to better services for customers, and by extension, the organisations will benefit from
increased revenue from loyal customers. One will then expect that this logic will apply to
customers of mobile telecommunications (telecoms) operators in Nigeria, as the operators have
implemented CRM applications in order to serve their customers better. Contrary to this
expectation however, Nigeria Consumer Satisfaction Survey (NCC and CTO, 2012) revealed
that only 59% of customers are satisfied with the mobile operators’ services despite the
implementation of CRM applications. Unfortunately for the customers, 99.7% of telecoms
customers in Nigeria, translating to 148million subscribers in the country, are serviced by the
mobile operators (NCC 2017). Given that I work with one of the mobile telecoms operators in
Nigeria and interact daily with colleagues, friends and family members that are users of
telecoms services, I feel compelled to research the following questions with a view to gaining
insight as to how benefits can be further realised from the implementation of CRM applications
in Nigeria’s mobile telecoms sector.
1. What are the priority objectives and expected benefits of telecoms organisations for
implementing CRM applications?
2. How effective are the structures in place to ensure the success of CRM applications?
3. To what extent do telecoms organisations believe the expected benefits of CRM
applications are being realised?

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1.3. Existing literature
CRM can be defined from multiple perspectives such as marketing, strategy, philosophy,
processes and information technology. All the perspectives have their merits and demerits and
as will be demonstrated in the detailed literature review, the perspectives have also been
combined by different authors to enhance the robustness of CRM implementation. Beyond the
way CRM is seen by researchers and organisations, technology seems to be a unifying factor
for all the perspectives. This is because of the ability of CRM applications to store and aid
analysis of customers’ information and this is in turn used by business managers to make
decisions on customer profitability or segmentation. However, the use of technology-based
CRM does not automatically translate to performance benefits for organisations. As a matter of
fact, over 60% of CRM applications’ implementations have been found to result in failure
(Merkle Group, 2013). This implies that other factors need to be considered in ensuring
realisation of benefits from the implementation of CRM applications.
The primary objective for implementing CRM applications is a key consideration in determining
the extent of benefits realised from the implementation. Organisations are justified to implement
CRM applications for profit or customer objectives or both, and this will be explored in more
details in the literature review section. Another determinant to consider in implementing CRM
applications is the supporting structure. This can also be referred to as the success factors and
they include business factors, implementation project factors, technology factors, people factors
and data factors (Freeman and Seddon, 2004). Though the classification to the five factors is
not universal, the next chapter will show that most of the recent literature on CRM applications’
success factors can be grouped under the five factors.
Furthermore, how expected benefits from the implementation of CRM applications are viewed
and measured, can determine the nature of benefits realised from the implementation. For
instance, benefits can be viewed from organisation or customer perspectives. It appears more
researchers cover CRM benefits realisation from organisation perspective than customer
perspective and this will be demonstrated in more details in the literature review chapter.
Another area that will be explored further is the diverse approaches for measuring benefits from
the implementation of CRM applications. This research work however, adopts Chinje’s (2013)
CRM Implementation Index as a preferred approach for measuring benefits realisation of CRM
applications. Amongst other reasons discussed in more details in the literature review chapter,
this is because CRM Implementation Index combines CRM benefits measurement perspectives
from other researchers and the model is yet to be tested.

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1.4. Approach and contributions
To answer the research questions stated above, this research work uses online questionnaire
developed using Google Form survey tool to solicit experience-based input from respondents
within the telecoms industry in Nigeria. Responses to the online questionnaire are automatically
collated in Microsoft Excel by the survey tool. Additionally, chapter 3 of this dissertation work
details how Microsoft Excel is used to graphically and numerically analyse the collated data.
Based on the analysis detailed in chapter 4 and summarised in chapter 5, this research work
answers the research questions using the three research constructs of objectives, supporting
structure and benefits realisation of CRM applications. In doing so, the research also
establishes priority for the other objectives for implementing CRM applications and explains the
link between non-realisation of customer benefits from the implementation of CRM applications
and organisations’ customer focus. Additionally, as part of the contribution of this research to
existing literature and practice of CRM applications, the research validates the CRM
Implementation Index (Chinje 2013) and provides recommendations for both pre and post
implementation phases of CRM applications.
1.5. Chapter summary
Based on the above, the aim of the research work is to understand the reasons why
implementation of CRM applications in Nigeria’s telecoms industry did not translate to better
benefits for organisations and their customers. This will be analysed within the context of the
three research constructs of CRM application objectives, CRM application supporting structure
and CRM benefits realisation. The chapter also provides an overview of the existing literature
and identifies CRM Implementation Index by Chinje (2013) as the starting point for the
theoretical and practical contributions of the research. The remaining part of the dissertation
work will expatiate on the ideas raised in this introductory chapter.

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2. LITERATURE REVIEW
2.1. Chapter Overview
Businesses exist to solve one or more problems through the provision of products and services
to their customers. The fact that there are usually more than one way of solving any particular
problem and no one person or organisation has a monopoly of knowledge guarantee alternative
solutions for the customers (Wedell-Wedellsborg 2017). This creates a competitive environment
and organisations providing similar products or services need to be creative in order to have a
fair share of the market. Discerning organisations have therefore resulted to customer
relationship management (CRM) as a competitive strategy to attract and retain profitable
customers. The remaining part of this chapter will explore the meaning of CRM, the role of
technology in its implementation, why and how organisations deploy CRM applications and the
benefits realised from the implementation of CRM applications. Gaps in existing literature are
also identified and a theoretical framework is proposed to bridge some of the identified gaps.
2.2. CRM and its supporting technology
Starting from relationship marketing perspective, this section reviews other non-marketing
perspectives of CRM and their shortcomings from existing literature. It follows with a review of
the basis for using technology to achieve CRM objectives before zooming in to the overview of
CRM applications in telecommunications industry.
2.2.1. Definition of CRM
CRM stemmed from relationship marketing principles which emphasise focus on retention
values of customers through relationship management rather than transactional values
(Roberts-Lombard, 2011). The benefits of retaining customers through effective relationship
management were exemplified by Reichheld and Sasser (1990), when they noted that only 5%
increase in customer retention can yield between 25% and 85% increase in profits, depending
on the industry.
CRM as a customer-centric initiative has also been defined from one or combination of non-
marketing perspectives such as strategy, philosophy, processes and information technology
tool. In the midst of the multiple and sometimes divergent definitions of CRM, none of the

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definitions or perspectives can lay claim to being the best. Rather, the different definitions or
perspectives of CRM have varying degrees of shortcomings. Based on literature, Table 2.1
provides a summary of CRM definitions from non-marketing perspectives and their respective
shortcomings.
Table 2.1: Summarised definition of CRM and their shortcomings
Perspective Summarised definitions of CRM Summarised Shortcomings of CRM
Strategy CRM is a plan for allocating relationship
management resources such that organisational
resources are scaled according to the expected
lifetime profitability of the customers (Ryals 2003;
Ledingham and Rigby 2004; Jayashree et al.
2011). This implies that highest resources are
allocated to customers with highest potential
lifetime profitability.
It is difficult to determine the lifetime
profitability of customers who may sometimes
exhibit rational and irrational buying
behaviours (Brosekhan et al. 2013).
Additionally, assessment of customer lifetime
value will have to be an ongoing exercise in
order to have relevance for CRM
implementation (Zablah et al. 2004).
Philosophy CRM relates to the culture of treating each
encounter with customers as an investment in a
long-term relationship aimed at understanding
and fulfilling customers’ changing needs (Alsafi et
al., 2012; Laketa et al., 2015).
Existing organisational members are the
custodians of organisational culture and in
the face of job mobility, CRM as a philosophy
or culture may be eroded.
Process CRM involves series of organisational activities
and tasks, grouped together to achieve profitable
customer long-term relationships (Payne and
Frow, 2005; Rigby 2015: 26).
Where processes are too summarised, they
become self-limiting to the achievement of
the intended business objectives and where
they are too detailed and rigid, they become
cumbersome for implementers to execute.
This therefore leads to confusion in
determining which process input or output
should be considered in ensuring successful
implementation of CRM (Zehetner et al.
2011).
Information
Technology
tool.
This perspective to CRM emphasises the
importance of technology as an enabler in
efficiently building and maintaining relationships
with customers. This involves, collection, storage
and use of customer data in designing apt
Over reliance on technology in achieving
CRM objectives may lead to failed
implementation of CRM initiatives. According
to Reichheld et al. (2002), “installing CRM
technology before creating a customer-

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Perspective Summarised definitions of CRM Summarised Shortcomings of CRM
products and services in line with changing needs
of the customers. (Ku 2010).
focused organization” or “assuming that more
CRM technology is better” is detrimental to
the achievement of CRM objectives.
While there are shortcomings from the different perspectives of CRM, the common denominator
is that when CRM is effectively leveraged, especially through technology, it can deliver tangible
values for both the organisation and their customers (Ledingham and Rigby 2004). Given that
the crux of this research work is benefit realisation from CRM applications, the next section will
explore technology perspective of CRM in more details.
2.2.2. Role of Technology in CRM
Zehetner et al. (2011) demonstrated that a company stands to gain more if a customer buys
products of the company throughout the customer lifetime. They emphasised that this is only
possible if the company is able to maintain a long-term relationship with the customers.
However, there are costs associated with acquiring and retaining customers over such a long-
term period and these costs may sometimes exceed the benefits of retaining the customers.
The task of understanding and deciding which customers will be profitable in the long-term calls
for scientific means of collating and analysing customers’ data. This is where the need for
technology in realising benefits from CRM implementation becomes apparent. According to
Buttle and Turnbull (2004), technology is a veritable tool that can be used to “disaggregate
potential and current customers into subsets so that different value propositions and relationship
management strategies can be developed for each group”. This important role of technology
explains the basis for the growth in CRM applications witnessed from late 90’s to date. For
instance, Gartner (Columbus 2013; and Gartner 2016) estimated that the worldwide CRM
applications market will grow to $36.5 billion in 2017 from $26.3 billion reported in 2015.
However, despite the increase in the deployment of CRM and associated technologies,
organisations do not automatically derive benefits from the implementation of CRM applications.
Merkle Group report (2013) revealed that about 63% of CRM projects result in failure or no
tangible performance improvement. Of the few CRM projects that are successful, some
researchers (Zablah et al., 2004; Santouridis and Tsachtani, 2015) also claimed that CRM
applications only have minimal impact in the overall achievement of CRM objectives.

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Notwithstanding the position above, it is not the technology that is the issue but the overall CRM
approach. Implementation of CRM technologies should be seen as enabler to businesses and
should only be considered after attaining a “customer-focused organisation” (Reichheld et al.
2002). Not implementing CRM applications may not even be an option for some organisations,
especially organisations that are involved in high volume transactions which inherently require
CRM technology in order to provide basic level of customer service. For instance, for a
customer service personnel to replace a faulty SIM card (“a small piece of plastic that is inside a
mobile phone and contains information about the person who uses the phone” – Macmillan
Dictionary 2017) for a customer in Nigeria, the personnel require data stored in the CRM
application to validate customer personal data, recharge history and call history. The next
section will provide more details on CRM applications in telecoms organisations.
2.2.3. CRM Applications in Telecoms
Telecoms operators (or organisations) use varying technologies to provide voice and data
communication services and they usually have a large customer base given the increasing need
of interconnectedness among people. For instance, in Nigeria with a population of 182 million
(NPC 2017) and four mobile telecoms operators, average telecoms subscribers for the
operators is 37.2million (NCC 2017). Storing and analysing information such as call location,
called number, call start time, call end time, data usage, etc., for every calls placed by
37.2million subscribers per operator (NCC 2017), require a robust CRM application. The
effectiveness of such CRM applications may then be the competitive advantage needed to
better understand the customers and provide niche products that support long-term
relationships with telecoms subscribers (Camilovic 2008). Example of the use of CRM
application in telecoms can include analysis of time of call which may lead to the design of night
products (e.g. free night calls and token amount for all-night browsing) that can retain some
categories of customers with an operator. Additionally, air-time or data usage reports from CRM
applications can provide viable basis for segmenting customers and thereby enable telecoms
organisations to profitably allocate scarce resources such as dedicated customer support
officers.
2.2.4. Summary of CRM and its supporting technology
The section above reviewed CRM from the perspectives of relationship marketing, strategy,
philosophy, process and information technology, and concluded that CRM is capable of
delivering tangible benefits to organisations when used effectively. This may take the form of
leveraging technology as a tool to build and maintain long-term relationships with customers.

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The section cited example from telecoms industry to justify the need for technology-based CRM
in high volume businesses. The section also suggested that there are many reasons to
implement CRM applications, organisations therefore need to understand why they are
implementing CRM applications and the expected benefits. The remaining part of this chapter
will explore the essence, supporting structures and benefits realisation of CRM applications.
2.3. Objectives of CRM Applications
This chapter attempts to review existing literature on the essence of CRM applications vis-à-vis
profit maximisation and customer satisfaction objectives of organisations. There is no doubt that
implementation of CRM in organisations imply using technology-enabled relationship
management to meet changing customer needs and advance profit objectives of the
organisations (Soltani and Navimipour, 2016). However, the relevance accorded to satisfying
customer needs or increasing profits will determine the CRM approach, and to a large extent,
the success or failure of the CRM initiatives. What follows in this chapter will explore the
essence of CRM applications from the perspectives of profit advancement as priority, customer
satisfaction as priority and equal priority for profit advancement and customer satisfaction.
2.3.1. Profit Advancement as priority objective
Organisations are continuously in search of winning strategies that will enable them achieve
their business objectives. Though organisations may have a number of objectives, most
organisations want to ensure they keep their costs within their income limit in order to stay in
business. Koch (2010) also argued that it is ethically correct for organisations to have profit
maximisation as priority objective and it is in the interest of the shareholders. It is therefore not
surprising that organisations will implement CRM applications as a way of extracting better
profits from transactions with their customers. This is demonstrated in the way CRM
applications can be used to segment customers into different level of profitability and the
resulting treatment accorded to the customers based on the segmentation (Buttle and Turnbull,
2004).
However, segregated treatment of customers according to profitability levels may not always be
in the best interest of organisations. This is because the use of CRM applications to predict
future profitability of customers is not an exact science (Damm and Monroy 2011) and is
therefore prone to errors. Customers that are routinely disengaged as a result of erroneous
CRM reports may be difficult and costly to be re-acquired. Peppers and Rogers (2007) stated

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that organisations can grossly lose out on “real opportunities” to grow their businesses if CRM
efforts are centred on most profitable customers based on current buying patterns. The
expected benefits for prioritising profits over customer satisfaction in the implementation of CRM
applications may therefore not be realised.
2.3.2. Customer satisfaction as priority objective
According to Ledingham and Rigby (2004), the main essence of CRM applications is to enable
organisations to efficiently and effectively respond to changing customer needs. This is in a bid
to developing and maintaining a long-term relationship with their customers. Literature generally
agreed that organisations that successfully implement CRM applications will be rewarded for
consistently meeting customers’ needs via repeat buys and referrals (Goodhue et al. 2002;
Agrawal 2003; Richards and Jones 2008; Awasthi and Sangle 2012; San-Martin et al. 2016).
The implication of this is that organisations can still have ample opportunities to make profit
while making their customers happy.
While it is desirable to retain all customers, it is not healthy for organisations to be in a situation
where profitable customers are perpetually funding the cost of providing services to non-
profitable customers (Peppers and Rogers 2007). It is therefore important for organisations
implementing CRM applications to device means of balancing customer objectives with profit
objectives.
2.3.3. Equal priority for profit advancement and customer satisfaction objectives
According to Williams and Scott (2012), meeting customer objectives and profit objectives
through the implementation of CRM applications need not be mutually exclusive. They argued
that organisations that are desirous of being successful in the long-term must equally recognise
the need for both profits and “purpose [such as customers and people] beyond shareholders’
wealth”. Though this approach may not meet the short-term profit objectives, it provides
organisations opportunity to understand and build lasting relationships with their customers. For
instance, CRM application may require a special report or upgrade in order to aid the
development of new products in line with ever changing customer needs (Braganza et al. 2013).
If management sees the upgrade to the application as negatively impacting the periodic profit
reports, the upgrade may be stalled. However, if management sees the upgrade as potential
benefits to customers, which may in time turn to profits for the organisation, the upgrade will be
accommodated.

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Based on the above, equally prioritising profit and customers’ objectives can be regarded as a
win-win approach that is capable of ensuring “… fair distribution of value between the different
stakeholders” (N’Goala 2015). Organisations implementing CRM applications should therefore
strive to attain a balance of objectives in their approach to customer relationship management.
2.3.4. Summary of CRM Objectives
Though Organisations can justifiably leverage CRM applications to achieve profit or customer
satisfaction objectives, they do not have to choose between the two objectives as both can be
achieved via deliberate CRM implementation strategies and supporting structures. Agrawal
(2003) lent credence to this by stating that “even the best CRM strategies and applications
stand little chance of succeeding …” in the absence of appropriate supporting structures.
2.4. Structures Supporting CRM Applications
Whether CRM is seen as strategy, philosophy, process or technology, organisations
implementing CRM applications want to make a success of it and this requires good
understanding of the factors that can positively or negatively impact the successful
implementation of CRM applications. This section reviews the critical success factors and
barriers to the implementation of CRM applications.
2.4.1. Success factors to the implementation of CRM applications
Given the high failure rate of CRM applications’ implementation (Merkle Group, 2013),
researchers have conducted various studies to understand reasons for the failure and a number
of recommendations have been made to ensure successful implementation of CRM
applications. This dissertation work aligns with the broad classification of the CRM applications’
critical success factors, as enumerated by Freeman and Seddon (2004). This includes
“business factors, implementation project factors, technology factors, people factors and data
factors”. The five factors largely encompass the success factors reviewed in other literatures as
shown in the description below.
Business factors: these relate to organisational-specific and industry factors that support the
implementation of CRM applications in organisations. Business factors include organisational
objectives, customer strategy, processes, regulatory environment, etc. According to Ledingham
and Rigby (2004), CRM applications can only be beneficial to organisations when processes,
people and technology are effectively leveraged.

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Implementation project factors: these are factors that enable the CRM applications to be
implemented to scope, quality, time and cost. For instance, Vazifehdust et al. (2012) identified
phased implementation as a success factor for CRM applications. Additionally, 18 specific
factors were identified by Freeman and Seddon (2004) as implementation project factors that
organisations need to consider in their CRM applications’ deployment. These include effective
leadership, clear communication, stakeholder management and CRM application vendor
support, amongst others.
Technology factors: these relate to the nature of CRM applications and other supporting
technology infrastructure that will ensure fitness of organisational purpose. Where an
organisation does not have customer-focused strategy and objectives before selecting CRM
applications, any application will seem appropriate until the organisation runs into
implementation issues. Going by Mendoza et al. (2007) submission, CRM is a “complex
combination of business and technology” and doing it right requires selection of appropriate
CRM application. However, CRM implementation must not be mistaken for a technology-only
solution in order to make a success of it (Reichheld et al. 2002).
People factors: these relate to the rigour of identifying stakeholders, getting their buy-in and
ensuring they are constructively engaged both pre and post implementation of the CRM
application. This is especially required given that relationship are expected to be maintained
throughout the customers’ lifetime (Jayashree et al. 2011). There is therefore need to share
organisation’s vision with the stakeholders and sufficiently motivate them in a bid to ensure
long-term relationships with the customers. Irrespective of how good the CRM system is, there
will be need for human intervention from time to time in order to maximise the insight provided
by the application.
Data factors: these are closely linked to technology factors and involve decision on the type of
customer information to be maintained in the CRM application, the level of details, the mode of
storage, integration with internal and external systems, means of mining the data and the
access and security of the data. To buttress the importance of data factors, Babon et al. (2011)
identified “data profile and context, data control, data integration and storage, data
augmentation, data monitoring, assigning ownership, users training and commitment to data-
quality process” as critical success factors that must be considered by organisations
implementing CRM applications.
Based on the literature reviewed, the five factors above were identified in different combination
but all the researchers identified at least one of the factors as a success factor for the

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implementation of CRM applications. Table 2.2 shows CRM applications’ success factors as
identified by different researchers.
Table 2.2: Mapping of CRM applications’ success factors
Researchers Success Factors
Mapping of Success Factors
Business Implementation
Project
Technology People Data
Foss et al.
2008
Strategic planning; staged
development  
Dhaka and
Nahar 2014
Right project team;
Customisation of industry best
practices.
  
Chinje 2013 Multichannel integration;
operating structure; training
and staff recruitment practices;
customer data storage and
mining capabilities; socio-
cultural context of the country.
   
Vazifehdust
et al. 2012
Robust project approval
process; use of CRM best
practices; phased
implementation; project
management; cross-functional
commitment.
 
Mendoza et
al. 2007
Senior management
commitment; staff commitment;
customer information
management; information
systems integration.
   
Boban et al.
2011
Data quality; data privacy; and
data security 
2.4.2. Barriers to the implementation of CRM applications
In addition to the success factors above, there are barriers that can limit or inhibit the
achievement of CRM applications objectives. However, literature reviewed suggest that barriers
to CRM applications are the reverse of the success factors described above. For instance, while
lack of strategic planning was identified by Wamai and Nzuki (2016) as a key barrier to the
implementation of CRM application, adequate strategic planning was identified by Foss et al.
(2008) as critical success factor for the implementation of CRM application. Other factors
identified as barriers and their reverse identified as success factors include implementing CRM
application as technology-only solution; inadequate management support; implementing CRM

18
systems without customer strategy and; inadequate change and project management. See
Table 2.3 below for more details.
Table 2.3: CRM implementation barriers as reverse of success factors
Barriers Success Factors
Lack of strategic planning (Wamai and Nzuki, 2016) Adequate strategic planning (Foss et al., 2008)
Implementing CRM application as technology-only
solution (Dhaka and Nahar, 2014)
Implementing CRM application as enabler (Wu, 2008;
Gholami and Rahman, 2012)
Inadequate support from top management (Maklan et
al. 2011)
Senior management commitment (Mendoza et al. 2007)
Implementing CRM systems before creating a customer
strategy (Rigby et al., 2002)
Customer strategy as starting point for CRM
implementation (Payne and Frow, 2005)
Inadequate change and project management (Kale,
2004)
Adequate project management and cross-functional
commitment to change (Vazifehdust et al. 2012).
2.4.3. Summary of structures supporting CRM applications
CRM application does not exist in a vacuum and its successful implementation requires
consideration for factors that can be broadly classified as business, implementation project,
technology, people and data (Freeman and Seddon, 2004). These factors can also be viewed
from barrier perspective as inadequate consideration for the factors can lead to implementation
failure. This implies that successful implementation of CRM applications depends on how the
barriers or success factors described above are combined in an organisation. There is therefore
need for organisations to measure their combination of the factors from time to time in order to
put their CRM initiatives on the path of success.
2.5. Realisation of CRM applications’ benefits
Given that measurement of CRM applications’ performance aids achievement of business
objectives (Reinartz et al. 2004), it is a worthy exercise for organisations to formally articulate

19
their expected benefits from CRM applications and periodically measure their realisation of the
benefits. This section will explore CRM applications’ benefits and means of measuring the
benefits.
2.5.1. Benefits of CRM applications
There are several studies on benefits of CRM applications, especially from organisational
perspective. For instance, Rushforth (2007) claimed that CRM applications help organisations
to maintain up-to-date information about customer transactions and this assist in product or
service related decision making. Bezhovski and Hussain (2016) also stated that successful
implementation of CRM applications can result in quality service, cost reduction and profitability.
Additionally, Dong and Zhu (2006) observed that the integration capabilities within CRM
applications can enable organisations to collaboratively relate with their customers and other
business partners.
However, Mohammadhossein and Zakaria (2012) argued that more studies focused on CRM
benefits from organisational perspective whereas the secret to making customers happy lies in
the understanding of expected benefits from customers’ perspective. Mohammadhossein and
Zakaria arrived at this conclusion after they reviewed 60 papers on CRM benefits and noted that
only 15 of the papers addressed CRM benefits from customer perspective. They summarised
their findings into 8 CRM benefits that are considered as most important by customers. These
include “improved customer service, increased personalized service, responsiveness to
customers’ needs, customer segmentation, improved customization of marketing, multichannel
integration, time saving and improved customer knowledge”. However, their research is only
exploratory and did not identify how to achieve or measure the stated CRM benefits. While
awareness of the potential customer benefits is required for successful implementation of CRM
applications, it will only be meaningful if organisations can implement structures for measuring
the benefits and implementing corrective actions where appropriate.
2.5.2. Measurement of CRM applications’ benefits
Researchers have suggested a number of ways for organisations to measure benefits from their
CRM applications (Kim et al. 2003; Richards and Jones 2008; Al-Safi et al. 2012; Chinje 2013;
Venturini and Benito 2015). The approaches to measure CRM benefits generally cover
objective and subjective measurements in the areas of process, technology, decision making,
value enhancement, data-enabled innovation, customer service improvement, operational and

20
organisational performance. Table 2.4 below shows contributions of researchers to the
measurement of CRM applications’ benefits.
Table 2.4: Approaches to measuring benefits of CRM applications
Researchers CRM Application Measurement Model
Kim et al. 2003 Modified customer-oriented Balanced Score Card (BSC) to
measure value enhancement, effectiveness, innovation, and
service improvement.
Richards and Jones 2008 Evaluation of process, technology expenditures and strategic
initiatives that drive decision making.
Alsafi et al. 2012 CRM scorecard based on perspectives of organizational
performance, customer, process and infrastructure.
Chinje 2013. 16-scale model from the perspectives of organisation, institution
and customer data.
Venturini and Benito 2015 3-dimensional scale of customer life cycle, firm performance and
operational performance.
Based on the above, there is no agreed universal framework for measuring benefits of CRM
applications. Sundar et al. (2012) observed that contexts of each CRM application deployment
are different and as such, measurement model commensurate for each implementation should
be applied. Of particular interest therefore, is the work of Chinje (2013) which identified a 16-
scale model for measuring CRM applications’ benefits. The model, called “CRM Implementation
Index” (Appendix G), has the following indicators:
“vision and strategy, enterprise wide CRM, operating structure, multichannel integration,
programme management, CRM measures, change management, customer processes,
training and recruitment practices, adequate technology, coercive isomorphisms,
normative isomorphisms, mimetic isomorphisms, customer data volumes and velocity,
customer data quality, customer data storage and mining capabilities”.
The CRM Implementation Index (“Chinje’s model” or “the model”) is of interest because it
combines dimensions from most of the other researchers; the model is yet to be validated; and
it was developed in the context of telecommunication industry in emerging markets. This makes
the model appropriate for Nigeria mobile telecommunications industry which is the subject of
this dissertation work.

21
2.5.3. Summary of CRM benefits realisation
Though benefits realisation is a common subject, literature seem to be biased towards
organisational-based benefits of CRM application. However, this does not imply that customers
do not benefit from the implementation of CRM applications, but it implies that more needs to be
done to focus literature and practice on customer benefits of CRM applications. This may
include understanding and measuring appropriate customer-focused benefits of CRM
applications.
2.6. Chapter summary and theoretical framework
In an attempt to understand customer benefits realisation from CRM applications, the chapter
explored the definition of CRM and the role of technology in achieving CRM objectives.
Literature suggests that CRM means different things to different organisations and these can
include strategy, philosophy, process and information technology. Irrespective of CRM
definitions and albeit failed CRM implementation, effective use of CRM and its supporting
technologies have been found to be beneficial to organisations and their customers (Ledingham
and Rigby 2004; Brown 2016). The extent of the benefits realised may however depends on the
objectives for implementing CRM applications and the supporting structure within the
organisations.
CRM applications’ objectives can be profit-oriented if the organisation prioritises profits over
customer satisfaction and can be customer-oriented if the organisation prioritises customer
satisfaction over profits advancement. It is also possible for organisations to maintain a balance
of the two dimensions. The latter approach can be a win-win strategy for organisations that
really want to build a sustainable and profitable long-term relationships with customers (N’Goala
2015). However, implementing CRM applications to satisfy both profits and customer objectives
requires careful consideration of success factors such as business, implementation project,
technology, people and customer data.
The ultimate test of successful implementation of CRM application in any organisation is the
benefits realised from such endeavour. Though there are many approaches to the
measurement of these benefits (Table 2.4), there seems to be no universal framework for
measuring CRM applications’ benefits. Additionally, literature reviewed suggest that more
studies focused on CRM benefits realisation from organisation perspective than the benefits
realisation from customer perspectives (Mohammadhossein and Zakaria 2012).

22
Based on the above and the fact that recent literature (Soltani and Navimipour, 2016) calls for
“… researchers to investigate the patterns of CRM systems and their uses across industries and
countries …”, this research work seek to answer the following questions:
1. What are the priority objectives and expected benefits of telecoms organisations for
implementing CRM applications?
2. How effective are the structures in place to ensure the success of CRM applications?
3. To what extent do telecoms organisations believe the expected benefits of CRM
applications are being realised?
This is with a view to gaining insight as to how benefits can be further realised from the
implementation of CRM applications in Nigeria’s mobile telecoms sector. In addressing the
research questions, the theoretical framework in Figure 2.1 will be used to validate Chinje’s
(2013) “CRM Implementation Index” vis-à-vis customer benefits realised from the
implementation of CRM applications in Nigeria’s telecoms industry. The next chapter will
provide more details on the approach to the dissertation work.
Figure 2.1: Dissertation theoretical framework

23
3. DATA AND METHODS
To answer the research questions stated in section 2.6, this chapter describes the methods
followed in conducting the research, including the research methodology, design of the research
instrument, and the data collection and analysis approaches. Basis for using the methods and
means of resolving the limitations encountered are also discussed.
3.2. Research methodology
This research work used a deductive approach to validate Chinje’s model (2013) for measuring
CRM benefits through the three constructs of CRM objectives, CRM supporting structures and
CRM benefits realisation. According to the review of existing literature in Chapter 2, the model
called “CRM Implementation Index” is yet to be validated but it considered other researches on
CRM benefits realisation before it. The deductive approach was used in this research because it
has been found to be effective in confirming or modifying existing theories and models (AlKindy
et al. 2016).
Online Self-Administered Questionnaire (SAQ) were used to solicit input on the research
questions from employees of Nigeria’s mobile telecoms organisations, especially employees in
Customer Service, Marketing, Information Technology and Programme Management
departments. The described population is suitable for the research given their expected direct
involvement in the implementation and use of CRM applications. Apart from the population
cutting across departments and organisations, the fact that telecoms employees have easy
access to internet made online questionnaire appropriate for this research. According to NIHR
(2009), questionnaires are very useful when research respondents are large and widely
dispersed. The remaining part of this chapter provides details of the approach adopted in
designing the questionnaire, and collecting and analysing the research data.
3.3. Design of research instrument
Using the dissertation theoretical framework (Figure 2.1) as a guide, the CRM Implementation
Index (Chinje 2013) was mapped to the three main constructs of the research to identify
applicable measures of CRM applications in Nigeria’s telecoms industry. This then served as

24
basis for designing questions that addressed the three research questions stated in section 2.6.
See Table 3.1 for how the questions per the questionnaire mapped to the research questions
and CRM implementation indicators.
Table 3.1: Mapping of questionnaire to research construct and
CRM Implementation Index
Research Construct
Indicators per CRM Implementation
Index (Chinje 2013)
Corresponding question number
per Questionnaire
CRM objectives Vision and strategy 1, 2 and 3
CRM supporting structure Enterprise wide CRM 4 and 5
CRM supporting structure Operating Structure 6
CRM supporting structure Multichannel integration 7
CRM supporting structure Programme management 6
CRM supporting structure Change management 9
CRM supporting structure Customer processes 10
CRM supporting structure Training and recruitment practices 11
CRM supporting structure Adequate technology 12
CRM supporting structure
Normative isomorphisms: adopting an
approach based on organisational or
industry culture.
This is not represented in the
questionnaire. However, CRM
application related norms in Nigeria
telecoms sector include functionality to
interact with customers in local
languages, outsourcing of call centre
operations where the input to CRM
applications are generated, etc.
Mimetic isomorphisms: adopting the
approach of successful organisations
14
CRM supporting structure Customer data volumes and velocity 15 and 16
CRM supporting structure Customer data quality 15 and 16
Customer data storage and mining
capabilities
15 and 16
CRM benefit realisation CRM measures 8, 17, 18,19 and 20
CRM benefit realisation
Coercive isomorphisms: adopting an
approach for market requirement
reasons.
13
The questionnaires (Appendix F) contained mostly closed questions with “opt out” options and
used Likert scales (e.g. from strongly agree to strongly disagree) to solicit subjective
experience-based input from respondents (Iarossi 2006). Though Iarossi (2006) argued that
including “opt-out” option may increase the number of unanswered questions in the form of
middle or neutral responses, other research works (Grondin and Blais 2010; Adelson and
McCoach 2010) suggested that “opt-out” option increases the chances of honest feedback by

25
not boxing respondents to select from limited or inappropriate options. However, Losby and
Wetmore (2012) concluded that including or not including “opt out” options have both
advantages and disadvantages, but the overall “difference in [questionnaire] response is
negligible”. Furthermore, few questions (5 out of 28) were designed as open in order to collect
respondents’ background information and experienced-based CRM applications’ improvement
areas. This proved helpful as duplicate submission was easily spotted and removed based on
the background information.
Another important element of the questionnaire design is the quality review which took the form
of peer and supervisor’s reviews. After the reviews, the questionnaire was updated and
converted to online questionnaire via Google Form tool. This survey tool was selected because
of its ease of use, free availability, multi-browser compatibility, laptop and mobile devices
compatibility, and spreadsheet-based responses (Eaton 2011). Google Form also provided
options to make some questions mandatory but this was only applied to the question on
respondents’ consent. This is in order to give respondents control over the questions they
answer in line with the research commitment made in the Participant Information Sheet
(Appendix D). Additionally, prior to publishing the online questionnaire, a pilot run was
conducted with five members of the mobile telecoms organisation where I currently work. As
rightly suggested by Presser et al. (2004), the pilot run identified some problems the
questionnaire could have posed to the respondents. For instance, the Participant Information
Sheet on the first page of the pilot questionnaire prevented some respondents from completing
the questionnaire at a go. This feedback was addressed by sharing the Participant Information
Sheet as attachment to the invitation (Appendix E) for the final version of the questionnaire.
3.4. Data collection approach
Mobile telecommunications industry in Nigeria has four operators that provide services to over
148million subscribers or customers (NCC 2017). This research work set out to collect data
from the four operators by sending email request for research access to two of the operators
and physical request letter for research access to the other two operators. The dual mode of
request was informed by the researcher’s knowledge of the telecoms operators in Nigeria.
However, access was granted for only two of the four operators (Appendix C). Of the other two
operators where access was not granted, access was not expressly denied. Rather, one of the
operators did not respond to the access request letter while the other requested for additional
information via email. Though the latter looked promising initially, access was not granted as at

26
the close (5 May 2017) of the questionnaire despite thirteen email correspondences and at least
six phone calls over a 4-month period. To minimise the impact of the research access issues,
knowledge of labour mobility within the industry was leveraged. This is by asking respondents if
they have worked with other mobile telecoms operators in Nigeria and the extent to which their
responses to the questionnaires reflect customer benefits realised from CRM applications in
their former organisations.
The research progressed with the two organisations that granted access as this represents 50%
of the total population. Given that CRM applications are meant to be implemented by cross-
functional teams (Dhaka and Nahar, 2014), a purposive non-random sample of employees with
high likelihood to partake in CRM implementation projects was selected. This includes
employees in Customer Service, Marketing, Information Technology and Programme
Management departments. This sampling approach has been found to be effective when
researching representativeness of concepts such as benefits realisation in an industry (Teddlie
and Yu, 2007; Etikan et al, 2016).
Email invitations to participate in the research questionnaire were sent directly to selected
sample of 65 participants. Based on discussion with these first set of participants, it is also
estimated that the invitations were in turn forwarded to another 20 participants. Of the total 85
participants, 46 valid responses were received, representing 54% response rate. This response
rate is acceptable for the research work as equal or lower response rates have been used or
proposed for similar researches (Love et al., 2005; Nulty 2008).
3.5. Data analysis approach
The use of Google Form in this research enable the responses to the online questionnaire to be
automatically collated in Excel format. The research considered the use of SPSS and Microsoft
Excel software in analysing the collected data but settled for Excel because of its wide
availability, functionality and the researcher’s dexterity in using the tool.
In order to code the data, four categories of scale used to collect responses to the questionnaire
were identified. 5-point Likert scale was used to solicit “Strongly disagree” to “Strongly agree”
responses. There were also questions requiring “Yes” or “No” responses and rating of
importance from “Least important” to “Most important”. Additionally, there was a question
requiring rating of most important CRM objective out of “Reduced cost of marketing”, “Increased

27
sales through additional purchases” and “Improved customer relationship”. Respondents were
coded as “R1” to “R46” while the questions (excluding the background questions) were coded
as “Q1” to “Q20”. The Likert scale responses of “Strongly disagree” to “Strongly agree” were
coded as “1” to “5”; the “Yes” or “No” responses were coded as “2” or “1” respectively; the
“Least important” to “Most important” responses were coded as “1” to “3”; while the response on
CRM objective was coded as “1” to “3” using the order above. Questions not responded to
were coded as “0” in all cases. This coding method was selected because of its simplicity and
clarity, and it has also been used in similar researches (Al-Alawi et al., 2016; Madhovi and
Dhliwayo, 2017).
The coding method described above was implemented in Excel using the “IF” functionality.
Additionally, further analysis were done on the coded data using Excel functionality such as
“MEDIAN”, “MODE”, “FREQUENCY”, “GRAPH”, etc. Following the Excel analysis, responses
were interpreted along the lines of the three research questions using graphical (bar charts) and
numerical (percentage, median and mode) representations. Bar charts were used because of
the discontinuous nature of the data and the ease of creating and interpreting the charts
(Cooper and Shore 2010). Percentage and mode were used in order to determine responses
with the highest frequency. However, given that mode has been found to relatively skew results
depending on the grouping of the data, median was used to compensate for this as median is
“hardly affected by outliers” (University of Leicester 2016: 128). Additionally, the research
adopted a triangulation method to corroborate the research findings using secondary data.
The chapter described a deductive approach for validating an existing CRM application model
(Chinje 2013) through the use of online questionnaire. The questionnaire was designed in line
with the research construct using Google Form and data collected were analysed with Microsoft
Excel. The research used graphical and numerical representations to interpret the data. This
involved the use of bar charts and combination of measures (i.e. mode and median) to limit the
impact of bias that may be introduced by any of the measure of location.

28
4. ANALYSIS AND RESULTS
Based on the data collection methodology described in Chapter 3 above, this chapter describes
the analysis and findings from the implementation of CRM applications by the mobile telecoms
operators in Nigeria. This includes general analysis of responses to identify valid responses and
code them appropriately for further analysis. The coded responses are also analysed along the
line of the three research questions and a summary of the analysis results is provided at the
end of the chapter.
4.2. Broad analysis of responses
Apart from the question on participants consent, the online questionnaire (Appendix F) used
seven questions and twenty questions to collect background information and CRM application
information respectively from the participants. Though 47 responses were received from
participants, one of the participants responded twice and the duplicated response was removed
to avoid bias in the questionnaire results. Chesney and Penny (2013) referred to such
duplicated response as “farming” and they reported that if this is not controlled, it can lead to “…
statistical … errors in unpredictable ways”. The remaining 46 responses after the removal of the
duplicated response are summarised below.
4.2.1. Background information
Background information is to enable categorisation and better understanding of responses.
Below is the analysis of participants’ responses based on the background information provided.
Summary by industry: As stated in Section 2.6, the focus of this study is the mobile telecoms
industry in Nigeria. It is therefore necessary to analyse responses from industry perspective in
order to ensure their validity. Analysis of the 46 responses showed that 43 respondents work in
mobile telecoms industry while 3 respondents provide outsourcing services for telecoms
organisations (see Table 4.1).

29
Table 4.1: Questionnaire responses by industry
Industry
Count of
Participants
Mobile Telecoms 43
Outsourcing Services for
Telecoms 3
Total 46
It is a common practice in Nigeria’s telecoms industry to outsource services such as customer
support, information technology, etc. and outsourced staff are usually integrated into the
organisations they provide services for. For the purpose of this study, all the responses are
therefore valid on the basis of industry.
Summary by department: Responses to the questionnaire are largely from participants in
customer service (57%), information technology (22%) and sales (9%). The remaining 12% of
the responses are from participants in project management, finance and strategy departments
(see Table 4.2). The responses therefore represent a good spread of CRM applications’
stakeholders within the target industry.
Table 4.2: Questionnaire responses by function
Department Count of Participants Percentage
Customer Service 26 57%
Information Technology 10 22%
Sales 4 9%
Marketing 2 4%
Project/Program Management 2 4%
Finance 1 2%
Strategy and Business Development 1 2%
Total 46 100%
Summary by role: 65% (see Table 4.3) of the respondents are manager level and above in their
organisations and this will enable the respondents to provide management view on the
customer benefit realisation of CRM applications in their organisations. This is also
complemented by 35% respondents below manager level and this category of respondents is
capable of providing actual customer impact of CRM applications given their expected day-to-
day interactions with the customers.

30
Table 4.3: Questionnaire responses by role
Organisational Role Count of Participants Percentage
Below Manager 16 35%
Manager 17 37%
Senior Manager & Above 13 28%
Total 46 100%
4.2.2. Participants consent
The three statements used to confirm participants’ consent are “I confirm that the Participant
Information Sheet containing details of the research, has been provided to me via email
invitation to the questionnaire”, “All the questions that I have about the research have been
satisfactorily answered” and “I agree to participate in the research”. Analysis of the
questionnaire responses revealed that 91% (see Table 4.4) of respondents expressly
consented to participate in the research. Furthermore, consent can be inferred from the
remaining 9% of the respondents as they confirmed that all their questions have been
satisfactorily answered and also responded to all the CRM-specific statements in the
questionnaire.
Table 4.4: Summary of participants consent
Statements of Participants Consent
Summarised
Response
Count of
Participants
Percentage
All the questions that I have about the research
have been satisfactorily answered; I agree to
participate in the research.
Participants agreed to
participate
2
91%
I agree to participate in the research. 2
I confirm that the Participant Information Sheet
containing details of the research, has been
provided to me via email invitation to the
questionnaire; All the questions that I have about
the research have been satisfactorily answered; I
agree to participate in the research.
38
I confirm that the Participant Information Sheet
containing details of the research, has been
provided to me via email invitation to the
questionnaire; All the questions that I have about
the research have been satisfactorily answered.
All participants’
questions were
satisfactorily answered.
2
9%
All the questions that I have about the research
have been satisfactorily answered.
2
Total 46 100%

31
4.2.3. Coding of responses
Following the coding method described in Section 3.5, responses to the research questionnaire
were classified into four categories depending on their scales. Category A has two questions
with “Yes” or “No” responses; Category B has three questions in one question in an attempt to
rank expected benefits of CRM applications; Category C has one question to determine the
most important objective of CRM applications; and Category D has fifteen questions with Likert
scale responses. Table 4.5 shows the data set generated after the coding of the questionnaire
responses. The remaining sections of this chapter will further analyse the coded data with
specific focus on the three research questions.
Table 4.5: Coding of questionnaire responses
A B C D
Q
1
Q
19
Q
2a
Q
2b
Q
2c
Q
3
Q
4
Q
5
Q
6
Q
7
Q
8
Q
9
Q
10
Q
11
Q
12
Q
13
Q
14
Q
15
Q
16
Q
17
Q
20
R1 2 2 3 2 1 3 5 5 5 4 5 4 4 3 3 4 3 4 4 5 3
R2 2 1 1 3 2 3 5 5 5 4 5 5 4 4 2 4 2 5 4 4 0
R3 2 2 2 3 2 3 5 5 4 5 4 5 5 5 3 5 2 5 5 4 2
R4 2 1 2 3 2 3 4 2 4 4 4 4 4 4 3 4 2 2 4 5 0
R5 2 1 3 3 3 3 5 4 4 2 4 5 5 2 4 4 4 5 4 5 4
R6 2 1 2 2 2 3 4 4 4 3 4 3 4 4 5 4 4 5 3 5 4
R7 2 1 2 3 1 3 5 5 5 5 5 4 4 4 4 5 2 5 5 5 0
R8 2 2 2 2 3 3 4 3 5 2 4 3 4 3 5 4 2 4 2 4 4
R9 2 1 2 3 3 3 4 4 4 4 4 4 4 4 5 4 2 4 4 5 0
R10 2 1 1 2 3 3 2 4 4 4 4 3 4 4 5 4 2 4 4 5 0
R11 2 1 1 3 2 3 5 5 5 5 5 5 5 5 3 4 2 5 4 4 0
R12 2 2 1 3 2 3 3 4 4 5 5 5 4 4 4 4 2 4 5 5 4
R13 2 1 3 0 0 3 5 5 5 5 5 4 5 4 5 4 2 5 4 4 5
R14 2 2 1 3 2 3 4 4 4 4 4 4 4 2 4 2 4 4 4 4 4
R15 2 2 3 3 3 3 4 5 5 4 4 4 4 5 2 4 1 4 4 4 4
R16 2 1 2 2 2 3 5 4 4 5 5 5 5 4 1 3 3 5 5 5 0
R17 2 1 1 3 2 3 5 4 5 4 4 4 4 5 5 3 2 4 2 5 0
R18 2 1 2 3 3 3 4 4 4 5 4 3 4 5 5 3 4 4 4 4 4
R19 2 1 3 2 1 3 4 4 5 5 4 4 4 4 5 3 3 5 5 4 0
R20 2 1 2 3 3 3 5 5 5 5 5 5 5 5 2 2 2 5 5 5 1
R21 2 2 2 2 2 3 4 3 3 4 3 3 4 5 4 3 2 4 4 5 3
R22 2 2 3 2 1 3 4 4 4 5 4 4 3 4 3 3 3 4 4 5 4
R23 2 1 3 2 3 3 3 3 4 5 4 4 4 3 4 4 4 2 2 4 4
R24 2 1 1 2 2 3 5 5 5 5 5 5 5 5 2 4 1 5 5 4 0
R25 2 1 2 3 3 2 5 5 4 5 4 4 4 3 2 3 4 4 5 5 0
R26 2 1 2 2 2 3 4 4 4 4 4 0 4 4 5 4 2 4 3 4 5
R27 2 2 2 1 2 3 4 1 3 5 5 3 4 4 3 5 2 4 5 5 5
R28 2 2 3 3 3 3 5 5 5 5 5 5 5 5 5 4 3 5 5 5 5
R29 2 1 3 3 2 3 4 3 4 4 3 4 4 4 4 3 2 4 2 5 5
R30 2 2 2 3 1 3 5 5 5 5 5 5 5 4 4 5 4 5 2 5 5
R31 2 1 2 3 3 3 4 4 5 5 5 4 5 4 5 4 2 4 4 4 0
R32 2 1 1 2 3 2 4 5 5 5 5 2 2 4 2 5 2 5 5 5 0
R33 2 1 2 3 3 3 5 3 5 5 5 4 4 5 4 5 1 5 5 4 0
R34 2 1 2 2 2 3 4 4 4 4 4 4 4 4 3 3 4 4 4 4 0

32
A B C D
Q
1
Q
19
Q
2a
Q
2b
Q
2c
Q
3
Q
4
Q
5
Q
6
Q
7
Q
8
Q
9
Q
10
Q
11
Q
12
Q
13
Q
14
Q
15
Q
16
Q
17
Q
20
R35 2 1 3 2 3 1 3 3 2 2 4 5 4 3 4 4 5 3 4 4 3
R36 2 1 2 3 3 3 4 4 4 4 3 5 4 3 5 4 2 4 5 5 4
R37 2 1 3 3 3 3 3 3 4 4 4 2 3 2 3 4 2 4 4 5 4
R38 2 1 1 3 3 3 5 4 4 4 4 4 4 4 4 3 2 3 3 4 0
R39 0 0 1 3 3 3 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
R40 2 1 2 3 2 3 1 4 1 5 5 4 5 5 4 5 1 5 5 3 0
R41 2 1 2 3 2 3 4 4 4 5 4 4 4 5 5 4 4 4 1 5 0
R42 2 1 3 3 3 3 4 4 4 5 4 4 3 3 4 3 2 3 4 3 4
R43 2 1 3 3 2 3 3 3 3 3 2 2 3 2 4 2 4 2 1 5 3
R44 2 2 2 3 3 3 4 4 4 4 4 4 3 3 4 4 2 4 4 4 0
R45 2 1 2 2 1 3 4 2 4 2 4 4 3 2 5 4 2 4 4 5 0
R46 2 1 1 2 3 3 4 3 4 4 5 4 4 3 5 4 3 4 3 5 2
4.3. Priority objectives of CRM applications
To determine the priority objective for implementing CRM application in Nigeria’s mobile
telecoms industry, three questions were posed to the respondents. The first question (Q1)
sought to confirm if the respondent’s organisation has implemented CRM applications. Figure
4.1 shows the responses to the question and it is in the affirmative as 45 of the 46 respondents
confirmed their organisations have implemented CRM applications. One respondent did not
answer Q1 but the respondent answered all other questions. Implementation of CRM
application can therefore be inferred based on other responses of the respondent.
Figure 4.1: Confirmation of CRM application implementation
No Response, 1 No, 0
Yes, 45
0
5
10
15
20
25
30
35
40
45
50
No Response No Yes
Frequeency
CRM application implemented?

33
Following the confirmation that CRM applications have been implemented in respondents’
organisations, respondents were asked to rank three common objectives (Soltani and
Navimipour, 2016) of implementing CRM applications from least important to most important.
The responses are depicted in Figure 4.2 below.
Figure 4.2: Graphical ranking of CRM application objectives
Going by the height of the chart in Figure 4.2, “responsiveness to customer needs” is ranked as
most important CRM application objective while “cost reduction” is ranked as more important
CRM application objective. However, though “revenue improvement” has the lowest bar, it
cannot be ranked as the least important CRM application objective because 46% (21 of 46) of
the respondents believed “revenue improvement’ is the most important CRM application
objective. In order to clearly rank the objectives of implementing CRM application, the research
therefore analysed the median and mode (see Table 4.6) of the responses.
Table 4.6: Numerical ranking of CRM application objectives
Scale
Cost
reduction
Responsiveness to
customer needs
Revenue
improvement
Q2a Q2b Q2c
No Response (0) 0 1 1
Least Important (1) 11 1 6
More Important (2) 22 16 18
Most Important (3) 13 28 21
Total 46 46 46
Median 2 3 2
Mode 2 3 3
0
1 1
11
1
6
22
16
18
13
28
21
0
5
10
15
20
25
30
Cost Reduction Responsiveness to customer needs Revenue Improvement
Frequency
No Response Least Important More Important Most Important

34
The median and mode of “responsiveness to customer needs” is 3 and 3 respectively,
confirming that “responsiveness to customer needs” is the most important objective of
implementing CRM application as noted in Figure 4.2 above. However, Table 4.6 shows that
“cost reduction” and “revenue improvement” share the same median of 2 but they have different
modes of 2 and 3 respectively. This implies that though both “cost reduction” and “revenue
improvement” have a median of 2, higher mode of 3 for “revenue improvement” implies that
“revenue improvement” is closer to being the most important objective of implementing CRM
application than “cost reduction”. “Revenue improvement” is therefore the more important
objective of implementing CRM application while “cost reduction” is the least important.
To further validate the ranking of CRM application objectives above, respondents were also
asked to select the most important benefit expected from the implementation of CRM
applications in their organisations. The responses (Figure 4.3) to the question show 94% of
respondents believed that “improved customer relationship” is the most important benefit for
implementing CRM application, and the median and mode of the responses also converged to
the same result. This validates the findings in the two earlier questions and suggests that
meeting customers’ needs is the most important objective for implementing CRM applications in
Nigeria’s mobile telecoms industry.
Figure 4.3: The most important benefit for implementing CRM applications
Scale Frequency Percentage
No Response (0)
0 0%
Reduced cost of
marketing (1)
1 2%
Increased sales
through additional
purchases (2) 2 4%
Improved customer
relationship (3)
43 94%
Total 46 100%
Median 3
Mode 3
0 1 2
43
0
5
10
15
20
25
30
35
40
45
50
No Response (0) Reduced cost of
marketing (1)
Increased sales
through
additional
purchases (2)
Improved
customer
relationship (3)
Frequency

35
4.4. Effectiveness of CRM applications’ supporting structures
For the purpose of analysing the effectiveness of CRM applications’ supporting structures,
Freeman and Seddon’s (2004) five perspectives of business, implementation project,
technology, people and data, as described in Chapter 2.4, are applied. Following from the
mapping of questionnaire to research constructs and CRM Implementation Index in Table 3.1,
questions relating to CRM applications’ supporting structures are further classified into the five
perspectives (see Table 4.7). The remaining part of this section shows analysis of the
effectiveness of CRM applications’ supporting structures using the five perspectives.
Table 4.7: Classification of questionnaire for analysis purpose
CRM Implementation
Indicators (Chinje 2013)
Classification
Corresponding questions
per Questionnaire
Enterprise wide CRM Business factor 4 and 5
Operating Structure Business factor 6*
Customer processes Business factor 10
Mimetic isomorphisms Business factor 14
Programme management
Implementation project
factor
6*
Change management
factor
9
Multichannel integration Technology factor 7
Adequate technology Technology factor 12
Training and recruitment
practices
People factor 11
Customer data volumes and
velocity
Data factor 15 and 16
Customer data quality Data factor 15 and 16
Customer data storage and
mining capabilities
Data factor 15 and 16
*Question 6 can be classified as both business and implementation project factors, however,
the question will be analysed as part of implementation project factor.
4.4.1. Effectiveness of business factors
As shown in Table 4.7, there are four questions (Q4, Q5, Q10 and Q14) that relate to business
factors. The questions aimed to test the effectiveness of the business factors in supporting CRM
applications by asking respondents to confirm if: “there is a clearly defined customer-focused
vision that is supported by a defined CRM strategy” (Q4); “CRM strategy is communicated to
stakeholders prior to the implementation of CRM application” (Q5); “customer related processes
are documented and communicated to all personnel that have responsibility to implement the

36
CRM strategy” (Q10) and; “implementation and use of CRM application are more of a reflection
of what other industry operators are doing than the customer vision of the organisation (Q14).
By virtue of design of the questionnaire, agreement to the statements in Q4, Q5 and Q10
implies CRM applications’ supporting structures are effective while agreement to the statement
in Q14 implies the opposite. The questions are therefore analysed in two separate ways as
follows.
Analysis of responses to Q4, Q5 and Q10: although to varying degrees, Figure 4.4a shows that
respondents agreed to the statements in Q4, Q5 and Q10. This is also reflected in the common
median (4 – Agree) and mode (4 – Agree) of the responses to the three questions (see Table
4.8). Additionally, total percentage of “agree” (i.e. combination of “agree” and “strongly agree”)
responses to Q4, Q5 and Q10 are 85%, 74% & 85% respectively. This indicates that
respondents believe that their organisations have defined and communicated a customer-
centric CRM strategies and have implemented same through a well-defined customer
processes.
Figure 4.4a: Analysis of business factors as CRM application’s supporting structure -
(responses to Q4, Q5 & Q10)
0
5
10
15
20
25
30
Q4 Q5 Q10
No Response (0) Strongly Disagree (1) Disagree (2)
Neither agree nor disagree (3) Agree (4) Strongly Agree (5)

37
Table 4.8: Analysis of business factors as CRM application’s supporting structure
Scale
Frequency
Q4 Q5 Q10
No Response (0) 0 0% 0 0% 0 0%
Strongly Disagree (1) 1
4%
1
6%
0
2%
Disagree (2) 1 2 1
Neither agree nor
disagree (3)
5 11% 9 20% 6 13%
Agree (4) 22
85%
20
74%
27
85%
Strongly Agree (5) 17 14 12
Total 46 100% 46 100% 46 100%
Median 4 4 4
Mode 4 4 4
Analysis of responses to Q14: To further validate the effectiveness of business factors as a
supporting structure for CRM application, respondents were also asked to confirm if
implementation and use of CRM application are more of a reflection of what other industry
operators are doing than the customer vision of their organisations (Q14). The median (2) and
mode (2) of responses (Figure 4.4b) to this question suggest that respondents disagreed that
the use of CRM applications in their organisations are more of a reflection of what other industry
operators are doing than their organisation’s customer vision.
Figure 4.4b: Analysis of business factors as CRM application’s supporting structure –
(responses to Q14)
Scale Q14 Percentage
No Response (0) 0 0%
Strongly Disagree
(1) 4 9%
Disagree (2) 24 52%
Neither agree nor
disagree (3) 6 13%
Agree (4) 10 22%
Strongly Agree (5) 2 4%
Total 46 100%
Median 2
Mode 2
Based on the analysis of responses to Q4, Q5, Q10 and Q14 above, respondents therefore
believe that business factors such as customer vision, CRM strategy, customer processes and
0
5
10
15
20
25
30
No
Response
(0)
Strongly
Disagree (1)
Disagree (2) Neither
agree nor
disagree (3)
Agree (4) Strongly
Agree (5)
Frequecy
Q14 - Implementation and use of CRM application are more
of a reflection of what other industry operators are doing
than the customer vision of my organisation.

38
communication mechanisms are effective in supporting the implementation and use of CRM
applications in Nigeria’s telecoms industry.
4.4.2. Effectiveness of implementation project factors
As shown in Table 4.7 above, Q6 (“there are defined resources, roles and responsibilities to
support CRM Strategy in my organisation”) and Q9 (“changes including replacement of CRM
applications are done with input from all departments and they follow defined change
management procedures”) are classified under implementation project factors. Analysis of
responses to these implementation project factors indicates that respondents agreed to the
statements in Q6 and Q9 (see bar chart in Figure 4.5). Additionally, Figure 4.5 shows that the
two questions have a common median and mode of 4 (i.e. Agree), and this position is further
corroborated by the number of “Strongly Agree” responses in Q6 (17 of 46 = 37%) and Q9 (13
of 46 = 28%). Therefore implementation project factors such as resource management and
change management are effective in supporting the implementation and use of CRM
Figure 4.5: Analysis of implementation project factors as CRM application’s supporting
structure
Scale
Frequency
Q6 Q9
No Response (0) 0 1
Strongly Disagree (1) 1 0
Disagree (2) 1 3
Neither agree nor
disagree (3)
3 6
Agree (4) 24 23
Strongly Agree (5) 17 13
Total 46 46
Median 4 4
Mode 4 4
4.4.3. Effectiveness of technology factors
Table 4.7 above shows that Q7 (“interactions at customer touch points [such as shops, social
media, call centres, etc.] are fully integrated into the CRM applications and can be easily
leveraged to enhance customer service or marketing efforts”) and Q12 (“selection of CRM
application in my organisation is more of parent company’s decision than business
requirements”) are classified under technology factors. Analysis of responses to one of the
0
5
10
15
20
25
30
Q6 Q9
Frequency
No Response (0) Strongly Disagree (1)
Disagree (2) Neither agree nor disagree (3)
Agree (4) Strongly Agree (5)

39
technology factors (Q7) indicates that respondents strongly agreed that interactions at customer
touch points are fully integrated into the CRM applications and can be easily leveraged to
enhance customer service. This is evidenced from the median (4.5), mode (5) and height of the
bar chart in Figure 4.6a.
Figure 4.6a: Analysis of technology factors as CRM application’s supporting structure –
(responses to Q7)
Scale Q7 Percentage
Strongly Disagree
(1) 0 0%
Disagree (2) 4 9%
Neither agree nor
disagree (3) 2 4%
Agree (4) 17 37%
Total 46 100%
Median 4.5
Mode 5
However, the median (4) and mode (5) of responses to the other technology factor (Q12)
suggests that selection of CRM application in respondents’ organisations are more of parent
company’s decision than business requirements (see Figure 4.6b). Therefore, though
technology factors such as technology infrastructure and system integration are effective in
supporting the use of CRM applications in Nigeria’s telecoms industry, respondents believe that
the selection of CRM application is informed by parent companies’ decisions rather than the
business requirements.
0
5
10
15
20
25
No
Response
(0)
Strongly
Disagree (1)
agree nor
disagree (3)
Agree (4) Strongly
Agree (5)
Frequency
--------------------------------- Q7 ----------------------------

40
Figure 4.6b: Analysis of technology factors as CRM application’s supporting structure–
(responses to Q12)
Strongly Disagree
(1) 1 2%
Disagree (2) 6 13%
Neither agree nor
disagree (3) 8 17%
Agree (4) 15 33%
Total 46 100%
Median 4
Mode 5
4.4.4. Effectiveness of people factors
In order to validate the effectiveness of people factors as a supporting structure for CRM
application, respondents were asked to confirm if continuous training of personnel in the use of
CRM applications and new CRM approaches is an integral part of CRM implementation in their
organisations (Q11). Respondents agreed to the statement going by the median (4), mode (4)
and height of the bar chart in Figure 4.7. Additionally, 28% of respondents strongly agreed to
the statement in Q11 and thereby bringing the total “Agree” response to 69% (i.e. Agree - 41%
and Strongly Agree - 28%). People factors such as training and retraining of personnel are
therefore effective in supporting the implementation and use of CRM applications in Nigeria’s
telecoms industry.
Figure 4.7: Analysis of people factors as CRM application’s supporting structure
Strongly Disagree
(1) 0 0%
Disagree (2) 5 11%
Neither agree nor
disagree (3) 9 20%
Agree (4) 19 41%
Total 46 100%
Median 4
Mode 4
0
2
4
6
8
10
12
14
16
18
No
Response
(0)
Strongly
Disagree (1)
agree nor
disagree (3)
Agree (4) Strongly
Agree (5)
Frequency
----------------------------------- Q12 -------------------------------
0
2
4
6
8
10
12
14
16
18
20
No
Response
(0)
Strongly
Disagree (1)
agree nor
disagree (3)
Agree (4) Strongly
Agree (5)
Frequency
------------------------------------ Q11 -------------------------------

41
4.4.5. Effectiveness of data factors
As depicted in Table 4.7 above, Q15 (relevant customer data are maintained in a central
database for sufficient period of time to enable relevant personnel instantly fetch customers’
history as required) and Q16 (the CRM application in my organisation has data mining
capabilities to enable retrieval and analysis of customer data and to aid quality of business
decisions) are classified under data factors. Analysis of responses to the data factors shows
that respondents agreed to the statements in Q15 and Q16 (see bar chart in Figure 4.8).
Additionally, Figure 4.8 shows that the two questions have a common median and mode of 4
(i.e. Agree), and this position is further supported by the number of “Strongly Agree” responses
in Q15 (17 of 46 = 37%) and Q16 (15 of 46 = 33%). Data factors such as data generation,
storage and retrieval are therefore effective in supporting the implementation and use of CRM
Figure 4.8: Analysis of data factors as CRM application’s supporting structure
Scale
Frequency
Q15 Q16
No Response (0) 0 0
Disagree (2) 3 5
Neither agree nor
disagree (3)
3 4
Agree (4) 23 20
Total 46 46
Median 4 4
Mode 4 4
4.4.6. Summary of CRM applications’ supporting structures
Analysis in sections 4.4.1 to 4.4.5 above can be summarised as Table 4.9 below and it shows
that CRM applications’ supporting structures are effective. This is despite respondents believe
that selection of CRM applications is more of parent companies’ decision than the requirement
of the business. Having established the effectiveness of supporting structure for CRM
applications in Nigeria’s mobile telecoms industry, the next section will review the benefits
realisation of CRM applications within the same context.
0
5
10
15
20
25
Q15 Q16
Frequency

42
Table 4.9: Summarised results for analysis of CRM applications’ supporting structure
CRM Implementation
Indicators (Chinje 2013)
Supporting Structure
Classification
Analysis Results
Enterprise wide CRM Business factors: customer
vision, CRM strategy,
customer processes and
communication
mechanisms.
Effective in supporting the
implementation and use of
CRM applications in
Nigeria’s telecoms industry
Operating Structure
Customer processes
Mimetic isomorphisms
Programme management
factors: resource
management and change
management.
CRM applications in
Nigeria’s telecoms industryChange management
Multichannel integration
Technology factors:
technology infrastructure
and system integration.
use of CRM applications in
Nigeria’s telecoms industry.
However, respondents
believe that the selection of
CRM application is
informed by parent
companies’ decisions rather
than the business
requirements
Adequate technology
Training and recruitment
practices
People factors: training and
retraining of personnel.
CRM applications in
Customer data volumes and
velocity Data factors: data
generation, storage and
retrieval.
CRM applications in
Customer data quality
Customer data storage and
mining capabilities
4.5. Evaluation of CRM applications’ benefits
In order to evaluate the benefits realisation of CRM applications, this section assesses the
performance measures, service delivery and improvement areas of CRM applications.
Additionally, respondents’ opinion on benefits realisation of CRM applications in other mobile
telecoms operators within Nigeria are also reviewed.
4.5.1. CRM applications benefits realisation
As shown in Table 3.1, Q8 (there are defined performance measures or targets for CRM
implementation in my organisation and the measures are closely monitored) and Q13 (service
delivery levels achieved by the aid of CRM application in my organisation generally exceed the
levels set by the regulatory authorities) relate to CRM benefits realisation, among other
questions. Analysis of responses to these questions shows that respondents agreed to the
statements in Q8 and Q13 (see bar chart in Figure 4.9). Additionally, median and mode of

43
responses for both Q8 and Q13 converge to “4” (i.e. “Agree”), indicating respondents believe
that continuous monitoring of CRM application measures enable them to meet customer service
delivery levels.
Figure 4.9: Analysis of CRM application’s benefits
Scale
Frequency
Q8 Q13
No Response (0) 0 0
Disagree (2) 1 3
Neither agree nor
disagree (3)
3 11
Agree (4) 24 24
Total 46 46
Median 4 4
Mode 4 4
However, analysis of responses to Q17 (there are some areas which if improved, can enable
my organisation to better realize benefits from CRM application) indicates that 96% (Figure
4.10a) of respondents believe that there are a number of improvement areas to be addressed
by their organisations in order to better realise benefits from CRM applications. Furthermore,
respondents were asked to state the top three CRM application improvement areas that can
benefit their organisations. “Supporting Processes” top the list of CRM application improvement
areas with 65% (Figure 4.10b) of the responses alluding to that position. This is followed by
“Data Storage & Mining” and “CRM Vision/Strategy” with 57% and 54% of the responses
respectively. Other CRM application improvement areas stated by the respondents include
“Data Quality” (52%), “Training” (48%) and “Unfit CRM Application” (7%).
0
5
10
15
20
25
30
Q8 Q13
Frequency

44
Figure 4.10a: Analysis of CRM applications improvement areas - (responses to Q17)
Strongly Disagree
(1) 0 0%
Disagree (2) 0 0%
Neither agree nor
disagree (3) 2 4%
Agree (4) 18 39%
Total 46 100%
Median 5
Mode 5
Figure 4.10b: Analysis of CRM applications improvement areas - (responses to Q18)
Improvement
Areas (Q18)
Frequency
Total
Response
Percent
Supporting
Processes 30 46 65%
Data Storage &
Mining 26 46 57%
CRM Vision/
Strategy 25 46 54%
Data Quality 24 46 52%
Training 22 46 48%
Unfit CRM
Application 3 46 7%
4.5.2. Extrapolation of responses
This research work collected data from two of the four mobile telecoms operators in Nigeria and
in an attempt to make the research more representative of the industry, respondents that have
worked with the telecoms operators not sampled were asked about benefits realisation of CRM
applications in their former organisations. Analysis of responses to Q19 (have you worked for
any of the other mobile Telecoms operators in Nigeria?) shows that 26% of the respondents
have worked with other mobile telecoms operators in Nigeria (see Figure 4.11). These 26%
agreed that customer benefits realised from the implementation of CRM applications in their
current organisations are similar to that of their former organisations. This is evidenced by the
median (4) and mode (4) of responses to Q20 (my responses to all the questions above also
reflect customer benefits realised from the implementation of CRM applications in my former
0
5
10
15
20
25
30
No
Response
(0)
Strongly
Disagree (1)
agree nor
disagree (3)
Agree (4) Strongly
Agree (5)
Frequency
----------------------------------- Q17 ------------------------------
30
26 25 24
22
3
0
5
10
15
20
25
30
35
Frequency
Improvement Areas (Q18)

45
Telecoms organisation) as shown in Figure 4.12. It can therefore be inferred that the results of
this analysis represent the benefits realised from the implementation of CRM applications in
Nigeria’s mobile telecoms industry.
Figure 4.11: Analysis of respondents with multiple operators’ experience
Scale Q19 Percent
No (1) 33 72%
Yes (2) 12 26%
Total 46 100%
Figure 4.12: Extrapolation of responses on implementation of CRM applications
Strongly Disagree (1) 0 0%
Disagree (2) 1 8%
Neither agree nor
disagree (3) 2 17%
Agree (4) 5 42%
Total 12 100%
Median 4
Mode 4
4.5.3. Summary of CRM applications’ benefits
Based on the analysis above, respondents believe that though current implementation of CRM
applications in Nigeria mobile telecoms industry enable operators to measure performance and
improve customer service delivery levels, there are still improvement areas that can enable the
operators to realise better benefits from the implementation of CRM applications. In order of
1
33
12
0
5
10
15
20
25
30
35
No Response (0) No (1) Yes (2)
Frequency
Worked for any other operators in Nigeria?
0
1
2
3
4
5
6
No
Response
(0)
Strongly
Disagree (1)
agree nor
disagree (3)
Agree (4) Strongly
Agree (5)
Frequency
-------------------------- Q20 -------------------------

46
criticality, the improvement areas include supporting processes, data storage and mining, and
CRM vision and strategy.
The section identified 46 valid responses based on industry, departments and roles of
respondents within Nigeria’s mobile telecoms industry. All the respondents voluntarily agreed to
participate in the study and their responses were coded and analysed in order to answer the
research questions.
The findings from the analysis indicate that meeting customers’ needs is the priority objective for
implementing CRM applications. Additionally, the supporting structures are generally effective in
realising benefits from CRM applications, save for some improvement areas that can be
addressed to realise better benefits. The findings from this research work and its implication and
contribution to CRM literature will be discussed in the next chapter.

Evading Customer Benefits of CRM in Nigerian Telecoms

Evading Customer Benefits of CRM in Nigerian Telecoms

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