Profit Analysis with Customer Attribute Study

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Profit Analysis with Customer Attribute
Study of Nike
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Contents
Table of Tables............................................................................................................................................2
Table of Figures...........................................................................................................................................3
1.0 Introduction of the Problem..................................................................................................................4
2.0 Classification of Business Problems of Nike...........................................................................................4
3.0 Results of the Analytical and Technical analysis....................................................................................6
3.1 Customer Characteristic Exploration.................................................................................................6
3.11 Do the client perspectives show a separation of three client groups............................................6
3.12 Do the client perspectives show a qualification for two genders..................................................8
3.2 Profit and COGS Analysis.................................................................................................................10
3.21 Which is the best and the most exceedingly worst selling item.................................................10
3.22 Is there any huge distinction in payment strategies....................................................................13
3.23 How was COGS scoring connected item classification.............................................................14
3.24 How are the two payment techniques distinctive for item astute payment.................................16
3.25 What is the level of relationship amongst COGS and net income levels....................................17
3.26 How does profit design change on a monthly basis...................................................................17
3.27 How does profit design change on sex premise.........................................................................19
4.0 Discussion and Proposals.....................................................................................................................21
5.0 References...........................................................................................................................................22
6.0 Appendix..............................................................................................................................................24
Table of Tables
Table 1: Descriptive statistics for personality traits.....................................................................................7
Table 2: Sex-based descriptive value for customer.....................................................................................8
Table 3: Awareness of Nike Cross Tabulation..............................................................................................9
Table 4: Post Hoc results for Nike’s customer attributes...........................................................................24
Table 5: Sex with Product Class Cross tabulation......................................................................................25
Table 6: One-Sample Test for card and Pay pal payment options.............................................................26
Table 7: One-way Descriptive figures for usage groups.............................................................................27
Table 8: ANOVA table for attributes of clients...........................................................................................28
Table 9: Paired Samples t-Test for Pay pal and credit card........................................................................28
Table 10: Pearson’s Correlation between Cost of goods and Profit Total..................................................29
Table 11: Chi-Square Tests for customer attributes..................................................................................29

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Table of Figures
Figure 1: Gender distributed usage group...................................................................................................9
Figure 2: Annual total profit based on product category...........................................................................10
Figure 3: Identification of best and worst product....................................................................................11
Figure 4: Best and worst selling product category.....................................................................................12
Figure 5: Classification tree for complete product segments....................................................................12
Figure 6: Box Plot for Credit card payment................................................................................................13
Figure 7: Box Plot for Pay Pal payment......................................................................................................14
Figure 8: Classification tree describing entire product segments on COGS...............................................15
Figure 9: Product lines on Pay Pal payment...............................................................................................16
Figure 10: Product lines on Credit Card payment......................................................................................17
Figure 11: Monthly total_ profit distribution bar diagram........................................................................18
Figure 12: Month-wise profit distribution of Nike.....................................................................................19
Figure 13: Gender-wise profit distribution................................................................................................19
Figure 14: Classification tree for profit......................................................................................................20
Figure 15: Average profit product item wise.............................................................................................26

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1.0 Introduction of the Problem
When it comes to sports apparel, the first name that comes to mind is NIKE’. The leader in the
sportswear segment with its trademark and quality magnetizes the customers all over the world. It
believes in the motto that, if a person has a healthy body than he/ she can be a worthy
sportsperson for the country. There are few competitors and this very cause drives the company
towards the invention of new product lines for both the sexes. The association takes after by their
principle objective of giving inventive sportswear to all contenders around the world. The
witticism of reasonability and great modernization has made an amazing brand a motivating force
for the clients. Conferred look into the gathering, researchers have manufactured a model which is
controlling Nike to an exponential improvement in thing goes close by general incomes. The
expert environmental approach has added to the brand name and upheld steady improvement at
each edge of the globe. The combination of item offering, each atmosphere wear additional items
has pulled in clients from the whole age areas. The money related experts and accomplices are
enthusiastic about new enthusiasm for the association. The inside organization of the association
has grasped a pilot errand to mull over late examples in shopper steadfastness and profit
examination. The market overview was coordinated in two phases, first for client examination and
a while later for association profit examination in light of picked thing broadens (Babooram,
2014).
2.0 Classification of Business Problems of Nike
The business mainly oriented around two attributes of stakeholders, customer's personality traits
and monthly profit trend from a variety of product lines (Chandra, 2017). The fundamental time
of the work included client contemplation in light of reactions of the clients. The investigation
aggregate gathered data on five fields, they were, item inclination, buy expectation mindfulness

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about different product offerings, payment level, and unwavering quality of the clients. Clients
were isolated into three classes in perspective of their decision of thing broadens. Overwhelming,
medium and light use class of clients were sorted in view of their sex. Accentuation was given on
two unequivocal inquiries related to the assembled data. The examination organized request was
according to the accompanying,
I. Do the client perspectives show a separation of three client groups?
II. Do the client perspectives show a qualification for two genders?
Three client class and sex of the clients were two ordinal factors. Examination of five client
personality characteristics, which were ordinal in nature, was performed for the client class and
their sex. The correct choice of informative procedure for the relationship was considered as
Cross-Tabulation. The inferential conclusion was drawn from Chi-square test.
Profit examination was finished in the second stage which included COGS information of one
year with nine particular item contributions. Edge of the cost of things (COGS) and total profit,
close by payment modes was inspected (Ngai, Xiu & Chau, 2009). As the essential worry of
every industry is a profit, the organization focused on the profit figures, related to thing orders.
For complete conclusion, seven inquiries were composed as underneath,
I. Which is the best and the most exceedingly worst offering item?
II. Is there any huge distinction in payment strategies?
III. How was COGS scoring connected item classification?
IV. How are the two payment techniques distinctive for item astute payment?
V. What is the level of relationship amongst COGS and net income levels?
VI. How does profit design change on a month to month premise?

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VII. How does profit design change on sex premise?
The connecting with measures for every investigation question was found in perspective of
nature of the data, and the legitimate inferential genuine measure was taken to set up the
instances of illustrative characteristics. The chi-square test, t-test, one path investigation of
fluctuation, the connection was used with the
3.0 Results of the Analytical and Technical analysis
3.1 Customer Characteristic Exploration
3.11 Do the client perspectives show a separation of three client groups
In the customer user groups, twenty-seven customers were identified as light sportswear user. The
medium user group consisted of fifty-one customers and the heavy sportswear was the highest in
number with seventy-two customers. Table 1 consists of the average and root mean square
deviation of the scenario.

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Table 1: Descriptive statistics for personality traits
Speculations were set for the inferential examination. It was hypothesized that the three client
clusters did not shift in ordinary number for five attributes (Sterzing, Lam & Cheung, 2012). As
the examination included the relationship of treatment clusters with ordinal nature with piece
components of scale variable, ANOVA was the choice for the inferential test. The three client
clusters changed in a general sense in, awareness about Nike equipment (F = 82.3, p < 0.05),
satisfaction level (F = 139.9, p < 0.05), preference of gear (F = 23.5, p < 0.05), purchase intention
of things (F = 6.2, p < 0.05). Nevertheless, with a dazzling surprise, the segments were
comparatively unwavering to Nike equipment (F = 0.4, p > 0.05). Tukey HSD test developed the
interrelation of client segments; they shifted basically (p regard < 0.05) in care and satisfaction
scores, however, the resemblance was seen for purchase intention, slant, and steadfastness for
'Nike' things which has been given in table 3 of Appendix.

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3.12 Do the client perspectives show a qualification for two genders
The customer's demographics were recorded with ninety-nine females and fifty-one males in the
collected data. The average number of the customer with standard deviation have provided in the
following table 2.
Table 2: Sex-based descriptive value for customer
It was speculated that sexual introduction compose has no effect on the attribute scores of the
clients. ANOVA was picked as the best possible gadget for inferential genuine examination. The
results revealed truthfully gigantic complexity in care (F = 6.0, p < 0.05) and slant in thing go (F
= 11.4, p < 0.05), and commitment for 'Nike' things (F = 44.3, p < 0.05). The two sexual
introductions were found to have equivalent qualities when satisfaction (F = 0.3, p > 0.05) and
purchase intension (F = 2.3, p > 0.05) scores were explored.

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Figure 1: Gender distributed usage group
Chi-square test with cross tabulation was done for dissimilarity in attributes between two
genders. It was established to be non-significant and table 11 in the appendix provides the clear
picture. Table 3 contains the distribution of customers for the two genders.
Table 3: Awareness of Nike Cross Tabulation
Awareness of Nike: Total
Count
Gender
TotalFemale Male
Website
User
Group
Light
Users 18 9 27
Medium
Users 31 20 51
Heavy
Users 50 22 72
Total 99 51 150

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3.2 Profit and COGS Analysis
3.21 Which is the best and the most exceedingly worst selling item
The best and most observably worst offering thing was recognized as Men's shoes and Girls
pieces of clothing. Indicate profit for Men's shoes and Girls pieces of clothing were $ 1446.3 and
$ 8.0. The histogram in figure 1 and box-plot in figure 2 was used to confirm and attest the best
and most exceedingly awful offering things.
Figure 2: Annual total profit based on product category

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Figure 3: Identification of best and worst product
Histogram result was cross-checked with the classification tree, and girls’ clothing was in the
less than $ 4.00 profit sector, however, Male shoes were right around 78% of profit for the most
astonishing profit level of $ 6.00.

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Figure 4: Best and worst selling product category
Figure 5: Classification tree for complete product segments

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The invalid theory was created with tolerating proportional profit for all the thing goes. The
collaboration among ordinal and scale factors was cross-checked by ANOVA and there was
quantifiably basic (F = 43106.4, P < 0.05) differentiate in the item contributions. The ANOVA
between the best and most exceedingly worst offering things revealed (F = 1686.6, p < 0.05)
significant refinement in all-out profit. The invalid hypothesis was dismissed in light of the
results. The Chi-square test for the grouping tree ( χ2=506 .2 , p < 0.05) completed the
inferential examination for quantifiably enormous qualification in the profit signify for different
level of profits (Panda et al., 2015).
3.22 Is there any huge distinction in payment strategies
Two payment methods, apparently PayPal and Visa payment were contemplated. It was
evaluated that payment systems did not shift in perspective of the thing goes. The typical
purchase paid with Pay Pal was $ 3.06 with SD of $ 3.31, and with charge card was $ 5.12 with
SD of $ 5.14. The t-test set up truthfully tremendous qualification between the two payment
strategies (t = - 6.18, p < 0.05). Ordinary payment with a credit card was higher stood out from
Pay Pal payment procedure (Kumar & Malegeant, 2006).
Figure 6: Box Plot for Credit card payment

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Figure 7: Box Plot for Pay Pal payment
3.23 How was COGS scoring connected item classification
To find the thing keen examination of COGS of the things, arrangement tree was formed for
different thing classes. Cost of men clothing was seen to be the base with cost edge not precisely
or proportional to $ 1.00 and Men shoes were in the most raised cost edge area of more
conspicuous or comparable to $ 2.70. ANOVA was used as a measure of inferential strategy and
the invalid hypothesis, with the assumption of adjusting of the cost of the stock was dismissed in
light of the regard (F = 435796.65, p < 0.05) of the estimation.

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Figure 8: Classification tree describing entire product segments on COGS

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3.24 How are the two payment techniques distinctive for item astute payment
The payment mode of Pay pal was plotted against different product categories in a box plot, and
it was found that men's shoe payment was maximum done through credit card whereas Pay pal
was used on average by customized products (Grandison, 2015).
Figure 9: Product lines on Pay Pal payment
It was speculated that the item contributions did not differ in Pay Pal payment procedure,
ANOVA was coordinated with seven degrees of chance. It was found that the item contributions
on a very basic level change in Pay Pal payment system (F = 819561.63, p < 0.05), and the
invalid theory was rejected.

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Figure 10: Product lines on Credit Card payment
3.25 What is the level of relationship amongst COGS and net income levels
The inter association among COGS and total profit included interest. The two components were
scale factors, subsequently, association coefficient was found between them. The positive
relationship (r (364) = 0.65, p < 0.01) for two took after test was really important. The invalid
hypothesis tolerating that, the COGS and total profit were uncorrelated was rejected. High net
income for the lifted cost of things was obvious from the estimation of association coefficient.
3.26 How does profit design change on a monthly basis
Month to month profit dissemination was a basic observation from the association's point of
view. The histogram was used to address the total month to month profit. In view of the brand
name and promoting strategy the total profit was seen to be proportional all through each one of
the months. An ANOVA was used to cross-check the claim, and the assumption of invalid

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hypothesis about consistency in hard and fast arrangements for each one of the months (F = 0.7,
p > 0.05) induced fail to be rejected.
Figure 11: Monthly total_ profit distribution bar diagram

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Figure 12: Month-wise profit distribution of Nike
3.27 How does profit design change on sex premise
The entire educational gathering was disengaged in four sexual introduction classes, men,
women, kids, and custom. Signify profit for the far-reaching thing classes were considered. At
initial, a histogram was produced, which showed that Men fragment was obtaining the most
outrageous profit and youngster's territory was picking up the least profit.
Figure 13: Gender-wise profit distribution

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The gathering tree was used with the ultimate objective of attestation. It was watched that tyke
class item offering had the least profit keep running with a profit not precisely or equal to $ 4.00
and Men expand had the most profit with profit more noticeable than $ 7.00. The chi-square test
was used as an inferential test and it certified with, p < 0.05 for four areas of profit. In this
manner, Men class sports items were getting the most total profit (Jin Gam et al., 2009).
Figure 14: Classification tree for profit

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Cross tabulation was directed between the sex class and item classification. Men's dress was less
sold item than men's shoes; ladies favored garments more than shoes. Kid's shoes were the most
sold portion of child's segment as described in table 5 of the appendix section.
4.0 Discussion and Proposals
The above examinations were assembled and some basic parts were demonstrated out the CEO of
Nike. Men's item contributions were sold more than some different things, the arrangement and
profit figures were the most amazing for comparative item advertising. Visa was seen as the
genuine strategy for payment from Men shoe, and men were seen to be more pulled in by the
promoting systems of the association. This was unmistakable from the cognizance of men about
the item contributions (Godey et al., 2012).
It was suggested that combination in female item offering was required; kid’s territory ought to be
revamped with new things. As a technique for payment, Pay Pal ought to be more urgently
exhibited with extra refund coupons. Elevating target should be the female fragment; especially
mothers should be the point of convergence of the publicizing gathering (Amit & Zott, 2012).

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5.0 References
“Nike Official Site.” NIKE, Inc.- Inspiration, and Innovation for Every Athlete in the World.,
Retrieved from www.nike.com/au/en_gb/.
Amit, R. and Zott, C., 2012. Creating value through business model innovation. MIT Sloan
Management Review, 53(3), p.41.
Babooram, N., 2014. BUSINESS 478 Section D300.
Chandra, A., 2017. NIKE VS. UNDER ARMOUR: STRATEGY COMPARISON. About the
publishing institution.
Godey, B., Pederzoli, D., Aiello, G., Donvito, R., Chan, P., Oh, H., Singh, R., Skorobogatykh,
I.I., Tsuchiya, J. and Weitz, B., 2012. Brand and country-of-origin effect on consumers' decision
to purchase luxury products. Journal of Business research, 65(10), pp.1461-1470.
Grandison, K., 2015. vTerminal Credit Card Processing App for AuthorizeNet and PayPal
Payflow Pro for Curve 8350 8500 8900 and Bold 9000. Retrieved from the Internet URL:
http://www. 4blackberry. net/tag/business-tools/vterminal-credit-card-processing-app-for-
authorizenet-and-paypal-payflow-pro-for-curve-8350-8500-890-download-2075. html, on, pp.1-
4.
Jin Gam, H., Cao, H., Farr, C. and Heine, L., 2009. C2CAD: a sustainable apparel design and
production model. International Journal of Clothing Science and Technology, 21(4), pp.166-179.
Kumar, S. and Malegeant, P., 2006. Strategic alliance in a closed-loop supply chain, a case of
manufacturer and eco-non-profit organization. Technovation, 26(10), pp.1127-1135.

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Ngai, E.W., Xiu, L. and Chau, D.C., 2009. Application of data mining techniques in customer
relationship management: A literature review and classification. Expert systems with
applications, 36(2), pp.2592-2602.
Panda, S., Modak, N.M., Basu, M. and Goyal, S.K., 2015. Channel coordination and profit
distribution in a social responsible three-layer supply chain. International Journal of Production
Economics, 168, pp.224-233.
Sterzing, T., Lam, W.K. and Cheung, J.T.M., 2012. 29 Athletic Footwear Research by Industry
and Academia.

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6.0 Appendix
Table 4: Post Hoc results for Nike’s customer attributes

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Table 5: Sex with Product Class Cross tabulation
Product Class
Total
Men’s
shoes
Men’s
clothing
Women’s
shoes
Women’s
clothing
customiz
e
boys
shoes
girls
shoes
girls’
clothing
Sex Men 91 78 0 0 0 0 0 0 169
Women 0 0 13 116 0 0 0 0 129
Kid 0 0 0 0 0 51 2 2 55
Custo
m
0 0 0 0 13 0 0 0 13
Total 91 78 13 116 13 51 2 2 366

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Figure 15: Average profit product item wise
Table 6: One-Sample Test for card and Pay pal payment options
Test Value = 0
t df
Sig. (2-
tailed)
Mean
Difference
95% Confidence
Interval of the
Difference
Lower Upper
Total
purchases
paid with
Pay Pal
17.662 365 .000 3.05874 2.7182 3.3993
Total
purchases
paid with
a Credit
card
19.049 365 .000 5.11831 4.5899 5.6467

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Table 7: One-way Descriptive figures for usage groups
N Mean
Std.
Deviatio
n
Std.
Error
95% Confidence
Interval for Mean
Minimum Maximum
Lower
Bound
Upper
Bound
Awareness
of Nike
Light
Users 27 2.81 1.711 .329 2.14 3.49 1 6
Medium
Users 51 4.90 1.676 .235 4.43 5.37 2 7
Heavy
Users 72 6.46 .604 .071 6.32 6.60 5 7
Total 150 5.27 1.857 .152 4.97 5.57 1 7
Satisfaction
with Nike
Light
Users 27 2.52 1.156 .222 2.06 2.98 1 6
Medium
Users 51 5.39 1.041 .146 5.10 5.68 2 7
Heavy
Users 72 6.07 .775 .091 5.89 6.25 2 7
Total 150 5.20 1.601 .131 4.94 5.46 1 7
Preference
for Nike
Light
Users 27 2.41 1.526 .294 1.80 3.01 1 6
Medium
Users 51 2.82 1.584 .222 2.38 3.27 1 5
Heavy
Users 72 4.46 1.652 .195 4.07 4.85 1 7
Total 150 3.53 1.834 .150 3.24 3.83 1 7
Purchase
Intention for
Nike
Light
Users 26 4.23 1.861 .365 3.48 4.98 1 7
Medium
Users 51 4.04 1.907 .267 3.50 4.58 2 7
Heavy
Users 72 5.01 1.193 .141 4.73 5.29 3 7
Total 149 4.54 1.646 .135 4.28 4.81 1 7
Loyalty for
Nike
Light
Users 27 3.85 1.537 .296 3.24 4.46 2 6
Medium
Users 51 4.14 1.575 .221 3.69 4.58 2 6
Heavy
Users 72 3.94 1.591 .188 3.57 4.32 2 7
Total 150 3.99 1.569 .128 3.74 4.25 2 7

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Table 8: ANOVA table for attributes of clients
Sum of
Squares df
Mean
Square F Sig.
Awareness
of Nike
Between
Groups 271.334 2 135.667 82.253 .000
Within
Groups 242.459 147 1.649
Total 513.793 149
Satisfactio
n with Nike
Between
Groups 250.450 2 125.225 139.932 .000
Within
Groups 131.550 147 .895
Total 382.000 149
Preference
for Nike
Between
Groups 121.528 2 60.764 23.518 .000
Within
Groups 379.805 147 2.584
Total 501.333 149
Purchase
Intention
for Nike
Between
Groups 31.443 2 15.722 6.212 .003
Within
Groups 369.523 146 2.531
Total 400.966 148
Loyalty for
Nike
Between
Groups 1.769 2 .884 .356 .701
Within
Groups 365.224 147 2.485
Total 366.993 149
Table 9: Paired Samples t-Test for Pay pal and credit card
Paired Differences
t df Sig. (2-
tailed)Mean Std.
Deviation
Std.
Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair 1
Total
purchases
paid with
Pay pal -
Total
purchases
paid with
a Credit
card
-2.05956 6.37706 .33333 -2.71506 -1.40407 -6.179 365 .000

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Table 10: Pearson’s Correlation between Cost of goods and Profit Total
Cost of
Goods
($)
Profit
Total
Cost of
Goods
($)
Pearson
Correlation 1 .646
Sig. (1-
tailed) .000
N 366 366
Profit
Total
Pearson
Correlation .646 1
Sig. (1-
tailed) .000
N 366 366
Table 11: Chi-Square Tests for customer attributes
Awareness of Nike Value df
Asymp.
Sig. (2-
sided)
Exact
Sig. (2-
sided)
Exact
Sig. (1-
sided)
a little
familiar
Pearson
Chi-Square .640c 1 .424
Continuity
Correction 0.000 1 1.000
Likelihood
Ratio .980 1 .322
Fisher's
Exact Test 1.000 .625
Linear-by-
Linear
Association
.600 1 .439
N of Valid
Cases 16
somewhat
familiar
Pearson
Chi-Square .000e 1 1.000
Continuity
Correction 0.000 1 1.000
Likelihood
Ratio 0.000 1 1.000
Fisher's
Exact Test 1.000 .745

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Linear-by-
Linear
Association
0.000 1 1.000
N of Valid
Cases 12
moderately
familiar
Pearson
Chi-Square 2.127f 2 .345
Likelihood
Ratio 2.883 2 .237
Linear-by-
Linear
Association
.774 1 .379
N of Valid
Cases 11
mostly
familiar
Pearson
Chi-Square 10.558g 2 .005
Likelihood
Ratio 11.567 2 .003
Linear-by-
Linear
Association
9.923 1 .002
N of Valid
Cases 57
extremely
familiar
Pearson
Chi-Square 3.197h 1 .074
Continuity
Correction 1.707 1 .191
Likelihood
Ratio 3.279 1 .070
Fisher's
Exact Test .146 .096
Linear-by-
Linear
Association
3.121 1 .077
N of Valid
Cases 42
Total
Pearson
Chi-Square 1.004a 2 .605
Likelihood
Ratio .997 2 .607
Linear-by-
Linear
Association
.274 1 .601

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N of Valid
Cases 150