BS2SX2 - Treforest Transport: Cardiff Car Sales Analysis Report

This case study examines the passenger car sales performance of Treforest Transport in Cardiff, with a focus on revenue analysis and strategic planning for expansion into Belfast. The report employs a quantitative exploratory approach, analyzing primary data on customer demographics, car preferences, and travel patterns. It also includes an analysis of regional industry trends and a comparative analysis between Cardiff and Belfast, with findings suggesting that higher-income males and married customers prefer Sports and Estate variants, while lower-income females and singles favor Hatchback and City cars. The study assesses financial performance, tests hypotheses regarding average sales revenue, and proposes marketing strategies. Key findings highlight the importance of factors like licensed car registrations and customer demographics in influencing car sales, and that the sports and estate variant of cars are noted to be the best two possible models for sales to new customers.

1
A Case Study on Passenger Cars of Treforest Transport in Cardiff

2
Executive Summary
This case study provides analysis of the self-assessment of revenues and future strategic plan
for sales of passenger cars of Treforest Transport to setup business in Northern Island city of
Belfast. The report has profound marketing implications, as it investigates and addresses
customers’ preference centred on evidence-based decision making. A quantitative exploratory
approach was adopted for this study. Research was conducted using primary data collected on
income of customers; types of car, distance covered, and job status along with some
demographic properties of customers in Cardiff. Annual car sales data from Great Britain
region was analysed to find that a significantly strong relation existed between sale of cars
and number of licensed cars in that area. Comparative investigation was done between key
findings from Belfast and Cardiff car sales. Key findings conclude that: Higher income
group, males, and married customers preferred Sports and Estate variants. Hatchback and city
cars are favoured by lower income group, females, singles, and students. A strong relation
between number of licensed cars and number of cars sold is also noted, implying that any
government policy of increasing number of licensed cars will improve car sales. Belfast and
Cardiff customers’ preference of car variants (sports) is found to be same corresponding to
age group of 30-39 years, but no such result is obtained in case of gender wise usage of city
cars. Average revenue for car sales in Cardiff is found to be significantly behind other
regional offices in GB. Finally, sports and estate variant of cars are noted to be the best two
possible models for sales to new customers.

3
Table of Contents
Executive Summary...................................................................................................................2
Introduction................................................................................................................................5
Company Overview...................................................................................................................5
1. Customer Analysis.................................................................................................................6
 Customers and their preferred car types..........................................................................6
 Travelling patterns based on average traveling distance and preferred cars.................10
2. Regional Industry Analysis..................................................................................................12
3. Comparative Analysis..........................................................................................................14
 Age comparison of Hatchback Customers....................................................................14
 Gender wise comparison for City Cars buyers.............................................................14
 Income groups by Car types..........................................................................................15
4. Financial Assessment and Marketing Plan..........................................................................16
 Monthly Sales Revenue Calculation.............................................................................16
 Hypothesis testing for average sales revenue in Cardiff...............................................17
 Marketing strategy of new cars.....................................................................................18
Conclusion................................................................................................................................19
Recommendation......................................................................................................................20
References................................................................................................................................21
Table of Figures

4
Figure 1: Distribution of age of customers................................................................................6
Figure 2: Gender percentage in customers’ data for Cardiff......................................................7
Figure 3: Distribution of income of customers..........................................................................7
Figure 4: Average income by gender in Cardiff customer sales data........................................8
Figure 5: Car type usage by two gender.....................................................................................8
Figure 6: Car type usage by marital status.................................................................................9
Figure 7: Car type usage by job type of customers....................................................................9
Figure 8: Distribution of driving years for the Cardiff customers...........................................10
Figure 9: Distribution of the distance covered by the cars.......................................................11
Figure 10: Side-by-side boxplot for distance travelled by car types........................................11
Figure 11: Scatterplot for correlation between car sales and number of licensed registered
cars...........................................................................................................................................12
Figure 12: Scatterplot for correlation between car sales and population.................................13
Figure 13: Scatterplot for correlation between car sales and GVA.........................................13
Figure 14: Car type by age groups of Cardiff customers.........................................................14
Figure 15: Car type by gender for Cardiff customers..............................................................14
Figure 16: Car type usage by Income groups of less than and greater than 50k......................15
Figure 17: Car type usage by marital status in Cardiff............................................................16
Figure 18: Monthly number of car sales by car types..............................................................16
Figure 19: Monthly sales revenue of Cardiff sales by car type................................................17
Figure 20: Pareto Analysis of Car Sales by numbers in Cardiff..............................................18
Figure 21: Pareto Analysis of Car Sales by revenue in Cardiff...............................................18

5
Introduction
There is no doubt that the automotive industry will continue to have a significant impact on
the world economy (Kumaraswamy et. al., 2012, pp.368-395). It has always been a
fundamental quest that tries to understand the structure of the automotive industry (Jacobides,
MacDuffie, and Tae, 2016, pp.1942-1967). The study focused on Treforest transport
performance in the passenger car sector in Cardiff. The aim is to identify a number of
strategies on which this decision is based and which will enable the company to gain in the
Northern Ireland market, particularly in the highly competitive market in Belfast.
This research uses knowledge from previous literatures on case studies with the empirical
data to look at the details of automobile market within the paradigm (Blankesteijn, Jong, and
Bossink, 2019, pp.74-103). Decision is based on revenue generation, customer preference of
cars with driving distance, and demographic information of customers in Cardiff. Regional
car sales data annual data of Great Britain was assessed for scrutinizing the relationship
between sales and population, GVA, and number of licensed cars. Comparative analysis of
customers’ preference between Cardiff and Belfast was also conducted. Finally, an inferential
analysis is accomplished with monthly average revenue earned from sales of cars in Cardiff
and other regional offices of the company. Decision based analysis with 80-20 rule is also
implemented for finding out the most profitable car that can be marketed to future customers
(Banduka et. al., 2016, pp.487-493).
Company Overview
Treforest Transport is a global enterprise that designs, manufactures and markets passenger
cars (City Cars, Estates, Hatchbacks, Saloons, Sports, and SUVs) across Great Britain and
European countries. At present, the company is interested in expanding its business to
Northern Ireland, and is looking forward to opening an outlet in Belfast. Consequently,

6
Treforest Transport is interested in summarising its performance in Cardiff centred on
relation between annual sales figure and regional population, licenced cars registered, and
GVA in £million. Simultaneously, the sales results of Cardiff have been compared with other
regional offices to assess the performance of the regional office.
1. Customer Analysis
 Customers and their preferred car types
The empirical data from 121 customers of passenger cars from Treforest Transport was
collected. Average age of the customers (M = 39.60, SD = 13.80) and distribution of their age
in Figure 1 reveals presence of handful of aged customers in the sample aged above 60 years.
This indicates that mostly young to mid-aged customers are present in the sample. Gender
wise exploration indicates that there was uniformity in percentage of male and female
customers in the collected data, where slightly higher number of male customers can be noted
from Figure 2.
Figure 1: Distribution of age of customers

7
Figure 2: Gender percentage in customers’ data for Cardiff
Income analysis of customers in Cardiff shows that average salary/ profit (M = 38896.69, SD
= 23457.37) was near to £40,000, where salary varied between £10200 and £119000. The
distribution in Figure 3 indicates presence of very few customers with income more than
£90000. The right skewed distribution is indicative of the fact that majority of the people
were earning between £20000 and £55000. Gender wise average incomes have been
presented in Figure 4 that indicates that males were earning more than females on an average.
Figure 3: Distribution of income of customers

8
Figure 4: Average income by gender in Cardiff customer sales data
Car usage by gender remains one of the close interests for the market strategists. Figure 5
presents the preference of car types by male and female customers. Sports and SUVs are the
two variants noted to be used by males more than females. Hatchback, Saloons, and Estates
are liked more by the females. City cars are found to be equally used by the two genders.
Figure 5: Car type usage by two gender
The Cardiff data of customers is also analysed for car type usage by marital status. Married
customers are noted to be primarily using Sports cars, Saloons, and Estate cars. Singles are
noted to prefer smaller cars like City cars and Hatchbacks. Divorced/ separated customers are
noted to use primarily use Estate cars, and widowed are noted to mainly dependent on Sports
variants.

9
Figure 6: Car type usage by marital status
A greater part of automotive buying depends on job type of the customer. Generally income
of customers is related to their job type making it as the obvious parameter for car sales. In
the Cardiff data, customers with full time employment are noted to use Saloons, Sports cars,
and Estates variants. Part-time employed customers are noted to prefer Hatchback and City
cars. Estates and Hatchbacks are equally used by self-employed customers. Students are
noted to use city cars for commuting.
Figure 7: Car type usage by job type of customers
 Travelling patterns based on average traveling distance and preferred cars
People in Cardiff on an average are noted to drive Treforest cars for 11.93 years (SD = 11.43
years), varying between 1 year to as long as 50 years. The distribution of driving years in

10
Figure 8 indicates that most of customers were driving their automotive between 5 to 30
years. The right skewness of the distribution is indicative of the fact that there also existed a
handful of customers who drove their cars beyond 35 years.
Figure 8: Distribution of driving years for the Cardiff customers
Distance covered by the cars in their lifetime is noted to be almost normally distributed with
average of 4595.60 miles (SD = 2225.89). Figure 9 also discloses that in some cases cars
even covered distances more than 9000 miles. A side-by-side boxplot in Figure 10 assists in
comparison of car type wise covered distance (Pallmann, and Hothorn, 2016, pp.1631-1638).
Performance of Estates, Hatchbacks, and SUVs (with slight right skewness) seems to be
better compared to other models.

11
Figure 9: Distribution of the distance covered by the cars
Figure 10: Side-by-side boxplot for distance travelled by car types

12
2. Regional Industry Analysis
Regional data for car sales from the Great Britain is analysed to examine relationship
between car sales with regional factors. Number of licensed cars registered in the Great
Britain region is evaluated to have a highly positive linear relation (R = 0.877) with number
of cars sold. This relation between number of cars sold and licensed registered cars is noted
to have the highest correlation (Mondal, and Mondal, 2016, pp.180-189). The coefficient of
determination is R2 = 0.7697, implying that number of licensed cars is able to explain 76.97%
variation in car sales. The linear relationship is evaluated as: Car Sales = 1.39*Licensed cars
registered + 1179.9. Hence, using this relation, predicted Car Sales in Belfast = 1.39*114 +
1179.9 = 1338.36 or 1339.
Figure 11: Scatterplot for correlation between car sales and number of licensed registered cars
Population (million) in the Great Britain region is evaluated to also have a highly positive
linear relation (R = 0.849) with number of cars sold. The coefficient of determination is R2 =
0.7215, implying that number of licensed cars is able to explain 72.15% variation in car sales.
Figure 12 explains the nature of the relation, Car Sales = 661.2*Population + 1143.8.

13
Figure 12: Scatterplot for correlation between car sales and population
Value of goods and services produced in the area (GVA) is evaluated to also have a medium
to high positive linear relation (R = 0.681) with number of cars sold. The coefficient of
determination is R2 = 0.4639, implying that number of licensed cars is able to explain 46.39%
variation in car sales. Figure 13 explains the details of the linear relation, Car Sales =
0.016*GVA + 1927.3.
Figure 13: Scatterplot for correlation between car sales and GVA

14
3. Comparative Analysis
 Age comparison of Hatchback Customers
Analysis of Cardiff Sales data has been done to evaluate the age groups corresponding to
hatchback cars. Figure 14 reveals that Hatchback cars buying customers in Cardiff are
primarily of age group 30-39 followed by age group of 20-29. Hence, parity of customers’
age group is noticed between Cardiff and Belfast.
Figure 14: Car type by age groups of Cardiff customers
 Gender wise comparison for City Cars buyers
Figure 15: Car type by gender for Cardiff customers

15
A comparative analysis between the two genders regarding their buying preference of
passenger cars. Regarding preference of city cars there is no difference between the two
genders regarding its usage in Cardiff. But, considerable differences in usage can be seen for
other variants of cars.
 Income groups by Car types
Figure 16 is representative of the fact that customers with income more than £50k, Saloon
and Sports variants are the two most favoured car types. Customers with income less than or
equal to £50k, Hatchback and Estates are the two top selections. Therefore, customers
earning over £50k noted to possess same preference in Belfast and Cardiff.
Figure 16: Car type usage by Income groups of less than and greater than 50k
 Marital Status with Car types
Marital status of customers and their choice of cars have been depicted in Figure 17. It is to
be noted that Saloons, Sports, Estates, and SUVs are primarily used by married people. City
cars and Hatchbacks are mainly preferred by single living customers. Hence, people who own
SUVs or Sports cars are mainly married. This finding is contrary to that of Belfast where
SUVs or Sports cars are mainly driven by singles.

16
Figure 17: Car type usage by marital status in Cardiff
4. Financial Assessment and Marketing Plan
 Monthly Sales Revenue Calculation
Number of sales of different car types in Cardiff has been presented in Figure 18 that clearly
indicates that Estate, Sports, and Hatchback cars are the leading sold cars in Cardiff.
Figure 18: Monthly number of car sales by car types

17
Using average price of each car type and number of sales from Figure 18 are multiplied to
obtain revenue for each car type. The average monthly revenue earned in Cardiff is evaluated
to be £3.575 million.
Car type Sales price range in £ Average Price Count of Car Revenue
1. City Car 10,000 – 16,000 13000 16 208000
2. Hatchback 16,000 – 22,000 19000 23 437000
3. Saloon 30,000 – 36,000 33000 21 693000
4. Estates 28,000 – 34,000 31000 23 713000
5. SUVs 25,000 – 31,000 28000 15 420000
6. Sports 45,000 – 51,000 48000 23 1104000
3575000
Figure 19: Monthly sales revenue of Cardiff sales by car type
 Hypothesis testing for average sales revenue in Cardiff
Findings from all regional office indicate that average revenue was £5.1 million with £1.8
million standard deviation. Average revenue from the present sample is £3.58 million.
Hypothesis testing for mean with known population standard deviation has been conducted to
compare performance of Cardiff sales with other regional offices. A z-test is conducted to
know that average revenue of £3.58 million is significantly lower (z-calculated = -2.075 < z-
critical (5%) = -1.645) compared to other regional offices in Great Britain.

18
 Marketing strategy of new cars
Figure 20: Pareto Analysis of Car Sales by numbers in Cardiff
Figure 21: Pareto Analysis of Car Sales by revenue in Cardiff
It is well known that 80% of profit comes from 20% of the products (Hariharan, 2016,
pp.703-708). A Pareto analysis has been done with pictorial presentation in Figure 20. It can
be noted that Estates, Sports, Hatchbacks, and Saloons are generating 80% business for the
company in Cardiff. Estates, Sports, and Hatchbacks have equal probability of getting sold.
From previous analysis it has been observed that Sports cars have the highest revenue,

19
demand among married persons, is the second popular car in more than £50k income group,
has most of the buyers from 30-39 age groups, and the most desired car for the males. Hence,
Sports cars should be pushed for sales among potential new customers after analysis of their
demographics. The second variant which can be sold is Estate cars considering its popularity
and earned revenue.
Conclusion
Passenger vehicle production and sales impact the economy as it is largely related to
employment growth of a country (Marx, de Mello, and de Lara, 2020. pp. 349-375). The
project of Treforest transport in Northern Ireland will be very important from the
employment generation point of view. Before initiating any production plan, review of
company’s revenue and internal strategies become very important (Vallaster, 2017, pp.509-
523). This report enables to review the sales position of Cardiff in Great Britain, and also
enables us to compare the revenue performance with other regional offices in GB. The aim of
the project is to analyse the customer and revenue data for setting up a production unit in
Northern Ireland city of Belfast. It is found that the best two selling variants are Sports and
Estates in Cardiff. The sample of car sales and revenue from the whole GB region turned to
be fully representative of the entire Britain region. Consequently, the focus of the present
work focuses on conclusion based on sufficient number of customers with their age, gender,
and marital status.
Analysis of customers’ data augments the fact that the policy of the company to setup a new
production unit considers buyers’ preference. A strong and highly positive relation of car
sales with number of registered licensed cars indicates that with higher number of registered
cars in the region a favourable atmosphere exists for future higher sales. In this paradigm,
Estate and Sports models are found to be top two liked variants in higher income group, here

20
lower income group preferred hatchback and city cars. Also, it is known that age of
customers preferring Hatchback cars in Belfast are between 30-49 years, whereas in Cardiff
Hatchbacks are preferred by customers in 20-39 years age bracket.
Recommendation
The study identifies few scopes of improvements which have been presented below as
suggestions or recommendations.
 The Treforest Transport should first look towards improving the revenue earned from
Cardiff office, as average sales revenue in Cardiff is noted to be significantly lower
than the regional data. Marketing team should look forward to frequent promotion of
Sports and Hatchback cars in Cardiff.
 The Cardiff model can be implemented in Belfast with higher average revenues,
where sales of Saloon and Sports cars should be promoted for higher income group of
customers.
 Correspondingly, hatchback cars should also be promoted for comparatively lower
income group, female, and single customers, especially considering the fondness
towards Hatchback cars for 30-49 years age group of customers in Belfast. The
company should look forward to top selling cars to be sold that contributes to easier
adaptation in the new market of Belfast.
 City cars are known to be preferred by females compared to males in Belfast.
Considering the Pareto analysis and demand of City cars in Cardiff, focus in
production for City cars should be considered in the bottom half of the priority list.

21
References
Banduka, N., Macuzic, I., Stojkic, Z., Bosnjak, I. and Peronja, I., 2016. Using 80/20 principle
to improve decision making at PFMEA. Annals of DAAAM & Proceedings, pp.487-493.
Blankesteijn, M., Jong, F.D. and Bossink, B., 2019. Closed-open innovation strategy for
autonomous vehicle development. International Journal of Automotive Technology and
Management, 19(1-2), pp.74-103.
Hariharan, R., 2016. Analysing the deficiencies in teacher education by Pareto
chart. IJAR, 2(1), pp.703-708.
Jacobides, M.G., MacDuffie, J.P. and Tae, C.J., 2016. Agency, structure, and the dominance
of OEMs: Change and stability in the automotive sector. Strategic Management
Journal, 37(9), pp.1942-1967.
Kumaraswamy, A., Mudambi, R., Saranga, H. and Tripathy, A., 2012. Catch-up strategies in
the Indian auto components industry: Domestic firms’ responses to market
liberalization. Journal of International Business Studies, 43(4), pp.368-395.
Marx, R., de Mello, A.M. and de Lara, F.F., 2020. The New Geography of the Automobile
Industry: Trends and Challenges in Brazil. In New Frontiers of the Automobile Industry (pp.
349-375). Palgrave Macmillan, Cham.
Mondal, H. and Mondal, S., 2016. Sample size calculation to data analysis of a correlation
study in Microsoft Excel®: A hands-on guide with example. International Journal of
Clinical and Experimental Physiology, 3(4), pp.180-189.
Pallmann, P. and Hothorn, L.A., 2016. Boxplots for grouped and clustered data in
toxicology. Archives of Toxicology, 90(7), pp.1631-1638.

22
Vallaster, C., 2017. Managing a company crisis through strategic corporate social
responsibility: A practice‐based analysis. Corporate Social Responsibility and Environmental
Management, 24(6), pp.509-523