Eco-Fone Smartphones: Report on Market Analysis and Expansion Strategy

This report provides a comprehensive analysis of the UK smartphone market, focusing on Eco-Fone Smartphones, a mobile phone retailer. It begins with an overview of the UK mobile phone market, including trends and forecasting of smartphone usage among adults. The report explores the potential of the older customer market and assesses the feasibility of expanding the business to Kingston using a pros and cons analysis. It also calculates the costs associated with a new building, tests the differences in net takings between two existing shops, and evaluates customer satisfaction through questionnaire analysis. The report concludes with key findings and recommendations, emphasizing the need for Eco-Fone to capitalize on market trends, consider expansion to Kingston, and improve customer satisfaction through quality control measures such as the use of Poisson Distribution to reduce faulty invoices. The report references relevant sources to support its findings and includes appendices with supplementary data, such as the excel formula for the mortgage calculation and graphic of mortgage lenders.

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REPORT FOR ECO-FONE

Contents
Introduction......................................................................................................................................1
1. Analysis of Issues for Eco-Fone Smartphones.........................................................................1
1.1 An Overview of the Mobile phone market in the UK...........................................................1
1.2 Forecasting the UK Adult Smartphone use...........................................................................2
1.3 Smartphones - A potential market for older customers.........................................................4
1.4 Feasibility of Expanding business to Kingston using Pros and Cons table...........................4
1.5 Costs of a New Building........................................................................................................5
1.6 Testing the Possible Difference in Net Takings in the Two Shops.......................................6
1.7 Customer Satisfaction............................................................................................................7
1.8 Quality Procedures.................................................................................................................8
1.9 Conclusions & Important Findings........................................................................................8
2. References....................................................................................................................................9
3. Appendices................................................................................................................................10

Introduction
Eco Fone Smartphones is a UK based mobile phone store which deals in smart phones and
has two shops one in Putney and one in Richmond. This company was founded in the year of
2014 and since then it is growing rapidly as they are fully aware of market demand and notice
trends among their customers (Storey, 2016). The main aim of this report is to analyse the mobile
phone market and advice this company few recommendations for expansion. In this report,
various tasks are conducted which includes assessing the current trends in mobile phone market.
Along with this, a statistical assessment is also conducted to ascertain whether or not Eco Fone
should expand in Kingston. An evaluation between two stores of this organisation has also been
done to analyse the reason behind difference in net profits of two stores.
Analysis of Issues for Eco-Fone Smartphones
1.1 An Overview of the Mobile phone market in the UK
a) Overview based on information from Deloitte
Mobile phone industry is the most rapidly growing sector in United Kingdom’s market. As
per the report of Deloitte, it has been seen that most of the people who are working in an
employment use their smart phone at least once for their work related purposes (Deloitte, 2017).
This statement emphasizes that use of smartphone in older people is higher.
Smartphones are not only used for calling purposes, varied features of these devices helps
people to communicate to be entertained in ample ways. There are various features of
smartphones which can be used for work related communication and activities which are email,
making standard calls, managing workload, viewing documents, making voice calls, editing
spreadsheets, submitting expenses and many other. In the report of Deloitte, information about
two years that 2016 and 2017 is given which reflects use of features of smartphones. The most
interesting fact which has been ascertained from this report that instead of making standard calls,
people are more tend to send emails which 41% in 2016 and 37% in 2017. Besides these two
main features, people at employment also highly tend to view documents in their smartphones
with 17% in 2016 (Rhodes, 2015).
As far as difference between years is concerned, it has been seen that in 2016 employed
people are highly tend to use smartphones in relation to viewing documents and managing their
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calendar but on the contrary no employed people use smartphone anymore for these purposes.
The reason behind it can be the high trend of smart watches in 2017 (Siegel, 2016).
b) Development of mixed bar chart for 2016 and 2017
Features % in Year 2016 % in year 2017
Emails 41% 37%
Making standards Calls 33% 32%
Viewing documents 17% 0%
Making voice Calls 6% 4%
1.2 Forecasting the UK Adult Smartphone use
Year
Smartphones Use by
adults
2012 52%
2013 62%
2014 70%
2015 76%
2016 81%
2017 85%
2018 94%
2019 94%
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Smartphones are mostly used by adults and in order to analyse these usage, above linear
forecast method is used (Mariappan, 2019). Using this technique, usage of smartphone in 2018
and 2019 are forecasted. From the above graph and table, it can be seen that there has been an
increase in the usage of these devices in upcoming years. Linear forecasting method is not
appropriate for this case as this technique is used when there is a linear relationship in variables
and trend in this case cannot be termed as increasing or decreasing, it can be fluctuating as well
due to which this technique id not valid here (Gupta and Gupta, 2017).
For this case, a forecasting model must be used which can return the forecasted value for
a specific future date using exponential smoothing method so that a valid prediction should be
made. Below usage of smartphones for 2018 and 2019 are predicted using Exponential
Smoothing (ETS) algorithm (Ott, 2018).
Year Smartphones Use by
adults
2012 52%
2013 62%
2014 70%
2015 76%
2016 81%
2017 85%
2018 91%
2019 98%
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1.3 Smartphones - A potential market for older customers
Smartphones are the devices which provides an ease in lives. Older people which are
between the age of 55 to 75 are considered to be highest users of smartphones as it facilitates
them to have an easier life. Some of these features are discussed below which are based on a
news article of BBC news:
Social media site access: Older people are usually non employed and has ample of free
time in which they like to communicate with their friends and people who are similar to their
age. It has been seen that 50% of the older people has installed Facebook compared to a 70%
figure of total number of adults. These social media sites like Facebook is a platform for older
people to communicate with their friends and be entertainment with the content shared in these
sites (Smartphone sales boom with over-55s, 2017).
Booking a taxi: Another feature which is highly used by older people of UK is taxi
applications. Smart phone devices allow its user to install a cab booking applications and as older
people are not capable to drive, this feature helps them to move from one place to another.
Bigger screens: Smartphones have bigger screens then usual phones which aids people
eyes specially of older people by which it is easier for them to view and also enjoy loud
speakers.
1.4 Feasibility of Expanding business to Kingston using Pros and Cons table
Pros and Cons method is an evaluation by which various merits and demerits are scored
and then all the values are summed in order to identify whether score of pros are higher or of
cons (Anderson and et.al, 2016). In this situation, Eco Fone currently deals in only two cities and
in order to ascertain that whether or not they should expand in Kingston, this analysis is done.
Below are provided few pros and cons for Eco Fone to expand in Kingston:
Should we expand our business to Kingston?
Pros Score/10 Cons Score/10
Increased sales revenue 9 Unaware about market
conditions 8
Enhanced brand equity 8 Increased costs 8
Increased profitability 7 Issues in acquiring store
lease 7
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Improved Goodwill 7 Non determined customer
preferences 7
Increase customer base 8 Increase workload 6
Scope for development 10 Ample operational costs 7
Wider market size 8 Cultural differences 8
Total Pros 57 Total Cons 51
Average Pros 8.14 Average Cons 7.28
From the above evaluation, it can be said that company should expand in Kingston as
average score of pros is 8.14 whereas average score of cons is 7.28
1.5 Costs of a New Building
a) Calculation of the monthly cost of repayment mortgage
Original price of building 400000
Negotiable price of building 350000
Time limit for repayment mortgage in years 15
Repayment mortgage amount 350000
Rate of mortgage 7%
Debt payment [((1+0.07)^15)-1]/
[0.07*(1+0.07)^15]
Total amount of loan / Discounting factor 1.76/0.19
9.11
350000/9.11
Total amount of loan 38419.32
Repayment amount on monthly basis 38419.32/12
3201.61
Costs of new building per month is calculated as £ 3201.61.
**Excel formula is shown in appendix
b) Presenting graphic containing eight logos of well-known commercial mortgage
lenders in the UK
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1.6 Testing the Possible Difference in Net Takings in the Two Shops
Information which is available for both the stores of Eco Fone
Particulars Amount
Sample from daily takings 40
Mean of 1st store 100
Standard deviation 20
Mean of 2nd store 90
Standard deviation 40
Significance level 5%
H0: Null hypothesis: There is no significant difference in net taking of two shops.
H1: Alternative hypothesis: There is significant difference in net taking of two shops.
Assessment of Z score value
Table 1
Mean value of one shop 100
Mean value of second shop 90
Standard deviation (one shop) 20
Z score assessment (100 – 90) / 20
0.5
Table 2
Mean value of one shop 100
Mean value of second shop 90
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Standard deviation (two shop) 40
Z score assessment (100 – 90) / 40
0.25
In above assessment, two hypotheses are taken from which one states that there is no
difference in daily takings of two stores of Eco Fone. And the other hypothesis which has taken
states that there is significant difference in net takings for both the stores. From the evaluation of
Z score, it has been observed that for both the stores value is greater than 0.05 which is the
significance level from which it can be said that there is no significant difference in net takings
of both the stores. This means null hypothesis is true.
1.7 Customer Satisfaction
Eco Fone is smartphone retail firm which distributes questionnaire in public in the form of
Email. The results from the questionnaire is analysed using Excel and that data is attached in
appendix. In total six questions are asked with the help of questionnaire. Answers to that code
are analysed, a total of 103 people has filed the questionnaire with options based on likert scale.
Mean from all the answers along with question IDs are presented below:
ID Q1 Q2 Q3a Q3b Q3c Q3d Q4 Q5 Q6
Mean
values 2.951456 2.893204 1.980583 2.504854 3.252427 2.514563 2.514563 2.524272 3.708738
From the above data, it has been analysed that when the question was asked that when was
the last time they purchased something from Eco Fone then the result was determined as 2.95
which means average people has bought something from their stores in last 3 to 6 months which
is actually good for the organisation. In case of where, respondents were asked that how long
they have used the products purchased from the stores of Eco Fone, they answered 2.89 which
means between 1 to 3 years.
Another question which is question 3 has four sub points which aims to procure rating on
customer service, quality of product, sales staff and price value. From the average value of 103
respondents, it has been concluded that service quality needs improvement as it rated as “Fair”;
whereas all other aspects are rated as “excellent” to “good”. Question 4, 5 and 6 are based on
what satisfaction level does customers attain from Eco Fone and how likely are recommend
them. From the mean value of all respondents it is determined that they are not really satisfied
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with the services of Eco Fone and are unlikely to stay their customers, but they are definitely
willing to recommend them to their friends and family.
1.8 Quality Procedures
Poisson distribution is the discrete distribution based on probability concept which
characterize events that has low probability of occurrence in a time period by which probability
can be reduced (Lee and Peters, 2015). In the case of Eco Fone, management is facing an issue in
which 2 invoices per month are faulty. In order to reduce the probability of these faulty invoices
by 15%, Poisson distribution must be used as it will characterize the faulty invoices and lower its
probability of occurrence.
Poisson random variable 2
Mean rate of success 15
Poisson probability P(X=2) 0.000
Cumulative probability P(X<2) 0.000
Cumulative probability P(X>2) 1
Cumulative probability P(X>=2) 1
From the above workings, it can be said that this technique will lower the probability of
occurrence of faulty invoices.
Two faulty invoices per month is not a big issue, but it reflects that quality procedures in
company has not been met for which it has been advised to Eco Fone that they should use
Poisson Distribution so that these invoices can be send after ensuring their quality.
1.9 Conclusions & Important Findings
From the above report, it has been concluded that Smartphone industry in United Kingdom
is rapidly growing and organisations working in this sector must develop themselves so that they
can take advantage of these trends. From various tasks conducted above, it has been concluded
that older people are more tend to use smart phones and working people use their smartphones
for the purpose of emailing and for making standard calls. Pros and Cons evaluation has also
been done from which it is observed that company must expand their business activities in
Kingston and should own a property there with month repayment of mortgage. At last, with the
help of questionnaire analysis, it is concluded that customers are not well satisfied with the
services which of Eco Fone for which they should use Poisson Distribution to improve their
quality standards.
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2. References
Books and Journals
Anderson, D. R., and et.al, 2016. Statistics for business & economics. Nelson Education.
Gupta, K. R. and Gupta, M. P., 2017. Business statistics. Atlantic Publishers & Distributors.
Lee, N. and Peters, M., 2015. Business statistics using EXCEL and SPSS. Sage.
Mariappan, P., 2019. Statistics for Business.
Ott, W.R., 2018. Environmental statistics and data analysis. Routledge.
Rhodes, C., 2015. Business statistics. Briefing paper. 6152.
Siegel, A., 2016. Practical business statistics. Academic Press.
Storey, D. J., 2016. Understanding the small business sector. Routledge.
Online
Deloitte. 2017. [ONLINE]. Available through:
<https://www.deloitte.co.uk/mobileuk2017/assets/img/download/global-mobile-consumer-
survey-2017_uk-cut.pdf>
Smartphone sales boom with over-55s. 2017. [ONLINE]. Available through:
<https://www.bbc.co.uk/news/technology-41319684>
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3. Appendices
Task 1
b) Development of mixed bar chart for 2016 and 2017
Features % in Year 2016 % in year 2017
Emails 41% 37%
Making standards Calls 33% 32%
Viewing documents 17% 0%
Making voice Calls 6% 4%
Task 2
Using linear forecast
Year
Smartphones Use by
adults
2012 52%
2013 62%
2014 70%
2015 76%
2016 81%
2017 85%
2018 94%
2019 94%
Using Exponential Smoothing (ETS) algorithm
Year Smartphones Use by
adults
2012 52%
2013 62%
2014 70%
2015 76%
2016 81%
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2017 85%
2018 91%
2019 98%
Task 5
Formula of calculating mortgage repayment from Excel
Debt payment [((1+0.07)^15)-1]/
[0.07*(1+0.07)^15]
Task 7
Questionnaire analysis
ID Q1 Q2 Q3a Q3b Q3c Q3d Q4 Q5 Q6
001 1 3 2 3 4 3 2 3 5
002 4 2 4 3 2 1 4 3 2
003 1 4 2 3 2 4 2 3 5
004 3 4 1 2 4 2 1 2 5
005 2 4 2 3 4 1 2 3 4
006 2 3 2 3 4 4 2 3 4
007 1 3 1 4 4 4 4 5 4
008 4 2 2 3 4 1 2 3 4
009 1 1 3 2 4 1 3 2 4
010 3 4 2 2 1 2 2 2 1
011 2 4 2 2 4 2 2 2 4
012 2 3 1 1 1 1 4 1 5
013 5 3 3 4 4 3 3 5 4
014 4 2 2 2 4 3 2 2 4
015 1 4 2 1 1 3 2 1 5
016 3 4 1 2 4 4 4 2 4
017 2 4 2 2 1 2 2 2 5
018 2 3 1 2 4 3 5 2 4
019 1 3 3 4 4 3 3 4 4
020 4 2 1 2 2 3 5 2 2
021 1 1 2 3 4 3 2 3 4
022 3 4 1 3 2 1 5 3 2
023 2 4 2 3 2 4 2 3 2
024 2 3 1 2 4 2 5 2 4
025 1 3 2 3 4 1 2 3 5
026 4 2 2 3 4 4 2 3 5
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027 5 1 4 4 4 4 4 4 5
028 3 4 2 3 4 1 2 3 4
029 2 4 3 2 4 1 3 2 4
030 2 3 2 2 1 2 2 2 5
031 1 3 2 2 4 2 2 2 4
032 4 2 1 1 1 1 5 1 1
033 1 4 1 4 4 3 3 4 4
034 3 4 2 2 4 3 2 2 4
035 5 3 2 1 1 3 2 1 5
036 4 2 1 2 4 4 5 2 4
037 5 3 2 2 1 2 2 2 5
038 4 2 1 2 4 3 1 2 4
039 2 4 3 4 4 3 3 4 4
040 2 3 1 2 2 3 1 2 2
041 5 3 2 3 4 3 2 3 4
042 4 2 4 3 2 1 5 3 2
043 1 4 2 3 2 4 2 3 2
044 3 4 1 2 4 2 1 2 4
045 5 3 2 3 4 1 2 3 5
046 4 2 2 3 4 4 2 3 5
047 5 3 4 4 4 4 4 4 4
048 4 2 2 3 4 1 2 3 4
049 2 4 3 2 4 1 3 2 4
050 2 3 2 2 1 2 2 2 1
051 5 3 2 2 4 2 2 2 4
052 4 2 1 1 1 1 1 1 5
053 1 4 3 4 4 3 3 4 4
054 3 4 2 2 4 3 2 2 4
055 5 3 2 1 1 3 2 1 1
056 4 2 1 2 4 4 1 2 4
057 5 3 2 2 1 2 2 2 1
058 4 2 1 2 4 3 1 2 4
059 1 1 3 4 4 3 3 4 4
060 2 3 1 2 2 3 1 2 2
061 5 3 2 3 4 3 2 3 4
062 4 2 4 3 2 1 4 3 2
063 1 4 2 3 2 4 2 3 2
064 3 4 1 2 4 2 1 2 4
065 5 3 2 3 4 1 2 3 4
066 4 2 2 3 4 4 2 3 4
067 5 3 4 4 4 4 4 4 4
068 4 2 2 3 4 1 2 3 4
069 1 1 3 2 4 1 3 2 4
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070 2 3 2 2 5 2 2 2 5
071 5 3 2 2 4 2 2 2 4
072 4 2 1 1 1 1 5 1 5
073 1 4 3 4 4 3 3 4 4
074 3 4 2 2 4 3 2 2 4
075 1 3 2 1 1 3 2 1 5
076 4 2 1 2 4 4 5 2 4
077 1 3 2 2 5 2 2 2 5
078 4 2 1 2 4 3 1 2 4
079 1 1 2 4 4 3 3 4 4
080 2 3 1 2 2 3 1 2 2
081 5 3 2 3 4 3 2 3 4
082 4 2 4 3 2 1 4 3 2
083 1 4 2 3 2 4 2 3 2
084 3 4 1 2 4 2 5 2 4
085 1 3 2 3 4 1 2 3 4
086 4 2 2 3 4 4 2 3 4
087 5 3 2 4 4 4 4 4 4
088 4 2 2 3 4 1 2 3 4
089 1 1 3 2 4 1 3 2 4
090 2 3 2 2 1 2 2 2 1
091 1 3 2 2 4 2 2 2 4
092 4 2 1 1 5 1 1 1 5
093 1 4 3 4 4 3 3 4 4
094 3 4 2 2 4 3 2 2 4
095 5 3 2 1 1 3 2 1 1
096 4 2 1 2 4 4 1 2 4
097 5 3 2 2 1 2 2 2 5
098 4 2 1 2 4 3 5 2 4
099 1 1 3 4 4 3 3 4 4
100 5 5 1 2 5 3 1 2 2
101 4 4 1 2 4 3 1 2 4
102 2 2 3 4 4 3 3 4 4
103 2 4 1 2 2 3 1 2 2
Mean
val-
ues
2.95145
6
2.8932
04
1.9805
83
2.5048
54
3.2524
27
2.5145
63
2.5145
63
2.5242
72
3.7087
38
13