tiểu luận title analyzing fashion clothing brand survey data by working with spss

Living area Out of 500 survey respondents, 78,4% of survey respondents are living in urban areas; 5,8% of people live in the suburbs; 14,2% of people live in rural areas and 0,6% live in

DA NANG UNIVERSITY OF ECONOMICS

REPORT MARKETING RESEARCH

Title: Analyzing fashion clothing brand survey

data by working with SPSS

Lê Ng ọc Đan Nhi

Da Nang, 26/5/2023

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Table of contents

1 Research objective 3

1.1 Research problem 3

1.3 Research hypothesis 3

2 Data preparation 3

3 Data Descriptive Statistics 4

3.1 Research sample characteristics 4

3.2 Evaluate each research variable 9

4 Identify analytical techniques 13

5 Hypothesis test results 14

6 Recommendations for managers 16

Appendix 17

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1 Research objective

1.1 Research problem

Research issue: Young people's buying habits of fashion brands

1.2 Research variables and measurement methods

No Variation Sign Measurement

= Ordinal scale (4 levels)

05 Channel of buying Channel

- On average, young people only buy a particular type of item from their favorite brand

- On average, young people only buy clothes on a particular channel

- The total number of buying channels that women and men buy from their favorite brands is the same

- There is no difference in the age of customers who buy clothes online and those who do not

- There is no relationship between living areas and online purchase channel selection

- There is no relationship between occupation and online purchase channel selection

- Brand loyalty has a positive effect on the number of items purchased

2 Data preparation

Loyalty variable: Generate the Loy General Loyalty variable according to the formula: Loy = (Loy_1

+ Loy_2 + Loy_3 + Loy_4) / 4

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Item variable: Create a Sum_Item variable that represents the number of clothing items purchased

from the brand according to the formula: Sum_Item = Item_1 + Item_2 + Item_3 + Item_4 + Item_5 + Item_6 + Item_7 + Item_8 + Item_9

Channel of buying variable:

- Create a Sum_Channel variable that represents the number of channels used to buy clothes according

to the formula: Sum_Item = Item_1 + Item_2 + Item_3 + Item_4 + Item_5 + Item_6 + Item_7 + Item_8 + Item_9

- Create an Online_Channel variable that represents whether or not a customer uses an online purchase channel with the values 0 (Do not use online purchase channel) and 1 (Use online purchase channel)

3 Data Descriptive Statistics

3.1 Research sample characteristics

The table shows the mean and standard deviation of the demographic variables:

a Sex

Among 500 survey respondents, 40,4% of survey respondents are male; 59,4% of people are female The age distribution of survey participants is uneven with more female survey participants The standard deviation between the male and female is 0.495

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b Age

Of the 500 survey respondents, 9% of the survey respondents are in the 15-17 age group; 45,2% of people are in the 18-22 age group, 27,6% are in the 23-27 age group and 18,2% are in the 28-year-old group or older The age distribution of survey participants is uneven, most of them are between the ages of 18 and 22

The average age of survey participants was 22,81 It can be seen that the subjects participating in the survey are young people, most of them are students The standard deviation between the age groups

is 0,89 The dispersion of the data is low, most of the respondents are concentrated in the average age group of 18-22 years old

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c Marital status

According to information collected from 500 respondents between the ages of 15 and 32, the marital status of the respondents is unevenly distributed Most of the respondents are single 403/500 accounts for 80,6% of single people This group of people are mainly students and students who are still studying 15,2% of people are married, this group of people is between the ages of 27 and 32 and are working The rest 4,2%

In the marital status variable, the standard deviation is 0,515

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d Monthly income

According to the above analysis, the monthly income of 500 respondents is also unevenly distributed The group under 5 million dong accounted for the most with 45% This group is mainly students, students who do not have a job, so they have unstable income

The income group from 5 to under 10 million ranked second and accounted for 28,4% of the total, followed by the income group from 10 to under 15 million accounted for 16,6%, from 15 to under 20 million accounted for 6,4% and the lowest is the income group over 20 million, accounting for 3,6%

For the monthly income variable, the standard deviation has a value of 1,094 and the mean is 1,95

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e Education level

The educational level of the respondents is not evenly distributed Out of a total of 500 people surveyed, most of them were in the group with a university education, 325, 65% It shows that the respondents are mainly students attending universities

The second is the Postgraduate group with 14,8%, followed closely by the High School students with 13,8% and the last is the College and Vocational group with 6,4%

f Occupation

Out of 500 survey respondents, 50,8% are students; 21,0% are employees, managers; 9,4% are employed; 9,0% are self-employed, trading; 6,0% are civil servants and public employees; 2,8% and 2,0% are unskilled workers and housewives, respectively; The remaining 8,0% is different The distribution of survey participants' occupation is unevenly distributed, most are students (50,8%) and then employees and managers (21,0%)

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g Living area

Out of 500 survey respondents, 78,4% of survey respondents are living in urban areas; 5,8% of people live in the suburbs; 14,2% of people live in rural areas and 0,6% live in other areas The distribution

of the survey respondents' living area is uneven, most of the respondents are living in urban areas

3.2 Evaluate each research variable

a Item

Out of 500 survey respondents, 26,1% bought T-shirts; 16,7% of people buy shirts; 11,5% of people bought jacket/Vest/Blazer; 10,6% of people bought shorts/badgers; 12,4% of people bought long

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c Purpose of buying

Of the 500 respondents who conducted the survey, 52,5% of them shopped for the purpose of daily needs - this shows that people appreciate the essential needs of daily life; 31,1% used for special occasions and 16,3% used as gifts; The remaining 0,1% is used for other purposes

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d Frequency of buying

Of the 500 respondents who conducted the survey, 32,4% of the survey respondents bought with a frequency of about 1-2 times; 44,4% of buyers with a frequency of about 3-4 times; 20,2% of buyers with a frequency of about 5-12 times; 3% of people buy more than 12 times

It can be seen that the distribution of buying frequency of survey participants is not uniform Most of them focus on 1-2 purchases and 3-4 purchases, very few people buy more than 12 times The average buying frequency is quite low This proves that most of the respondents do not often or rarely buy clothes from their favorite brands

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f Social influence

There are differences among survey respondents in terms of purchasing habits Of the 500 respondents who conducted the survey, there were: 63,8% of those who bought alone; 42,2% of people bought with people of the same sex; 20,8% of people bought with the opposite sex; 15% of people bought with groups of both the same and opposite sex; 0,7% of people have bought with other objects

It can be seen that the majority of survey participants often have the habit of buying independently because the rate of buying alone is very high In addition, the rate of buying with people of the same sex is also quite high The heterosexual and mixed groups account for a relatively low proportion

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g Information sources

Of the 500 respondents who conducted the survey, 63,8% of people know about the brand and product through the store; 20,2% through the company website; 68.4% through social networks; 32,8% through referrals from relatives/friends/colleagues; 17,8% through mass media; 0,2% through other sources

Survey participants searched for information about brands, products, and brand's advertising and promotions through different sources, and there were significant differences between groups of information sources In the era of the development of social networks, it is not surprising that the majority of respondents often find and know information about brands and products through social networking sites However, direct sources at the store are still favored and account for a high percentage The remaining sources such as the company website, referrals from acquaintances and mass media account for a lower percentage because of less access to the respondents

4 Identify analytical techniques

variables

Analytical techniques

1 On average, young people only buy a

particular type of item from their favorite

brand

Sum_Item One sample t-test

2 On average, young people only buy

clothes at a particular channel

Sum_Channel One sample t-test

3 The total number of buying channels that

women and men buy from their favorite

brands is the same

Sex Sum_Channel

Independent samples test

t-4 There is no difference in the age of

customers who buy clothes online and

those who do not

Age Online_Channel

Independent sample test

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5 There is no relationship between living

areas and online purchase channel

selection

Area Online_Channel

Chi-square test

6 There is no relationship between

occupation and online purchase channel

selection

Job Online_Channel

Chi-square test

7 Brand loyalty has a positive effect on the

number of items purchased

Loy Sum_Item

Regression

5 Hypothesis test results

No Hypothesis Condition check Relevant

Statistical Value

Conclude

1 On the average, young

people only buy a

particular type of item

from their favorite brand

H0: Sum_Item = 1

H1: Sum_Item ≠ 1

Mean = 3,1240

t = 32,989 p-value = 0,000 <

0,05

Reject H0, accept H1⇒ Not qualified

to accept the hypothesis

0.05

Reject H0, accept H1 Not qualified ⇒

to accept the hypothesis

3 The total number of

buying channels that

women and men buy

from their favorite brands

t = 0,338 p-value = 0,736 >

0,05

Accept H0, reject H1 ⇒ Accept hypothesis

4 There is no difference in

the age of customers who

buy clothes online and

those who do not

Variances:

p-value = 0,031 <

0,05

⇒ Equal variances not assumed

t = 1,111 p-value = 0,267 >

0,05

Accept H0, reject H1 ⇒ Accept hypothesis

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H0: There is no

difference in the age of

customers who buy

clothes online and those

who do not

H1: There is a difference

in the age between

customers who buy

clothes online and those

who do not

5 There is no relationship

between living areas and

online purchase channel

p-value = 0,064 >

0,05 Phi = 0,121

Accept H0, reject H1 ⇒ Accept hypothesis

6 There is no relationship

between occupation and

online purchase channel

0,05 Phi = 0,149

Accept H0, reject H1 ⇒ Accept hypothesis

7 Brand loyalty has a

positive effect on the

number of items

purchased

ANOVA:

F = 6,481 p-value = 0,011 <

0,05

⇒ Equal variances

R square = 0,013 Coefficients:

p-value = 0,000 <

0,05

Reject H0, accept H1 ⇒ Accept hypothesis

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H0: Brand loyalty has no

positive effect on the

number of items

purchased

H1: Brand loyalty has a

positive effect on the

number of items

purchased

not assumed Sum_Item = 2,256

+ 0,226*Loy + e

6 Recommendations for managers

Result Decision problem related Suggest ideas to solve the

decision problem

Young people do not just buy

a particular type of item from

their favorite brand

How to keep customers loving the brand?

- Creatively diversifying fashion items

- Create products that match customer preferences and needs Young people do not just buy

channels that women and

men buy from their favorite

brands is the same

How to effectively optimize the sales strategy towards multiple genders?

Use omnichannel sales strategies

to reach male and female customers on many different buying channels at the same time,

to increase advertising effectiveness and optimize advertising costs

There is no difference in the

age of customers who buy

clothes online and those who

do not

Are users of all ages changing their approach to online purchases?

- Personalize the experience, and diversify products on online platforms, so that customers can easily access a variety of products

to suit their needs

- Create engaging online experiences - provide a friendly, easy-to-use interface

There is no relationship

between living areas and

online purchase channel

selection

How to ensure that all living areas can access and purchase products online?

- Expand the scope of delivery by diversifying shipping partners

- Minimize product price differences due to shipping costs between different regions There is no relationship

between occupation and

How to optimize the online sales strategy to target customers with many

Focus on expanding a variety of sales channels on the online platform to reach a wide range of

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Brand loyalty has a positive

effect on the number of items

purchased at a weak level

How to build, maintain and enhance brand loyalty with customers?

- Ensure items meet customer expectations in terms of price and quality

- Receive and resolve customer feedback and inquiries

Appendix

Hypothesis 1: On average, young people only buy a particular type of item from their favorite brand

With a test value of 1 (buy only a certain type of product from a favorite brand), the t-value is 32,989

and the p-value is 0,000 > 0,05, inferring reject H0, accept H1 Specifically, the sample mean value

- Mean equal to 3,1240 indicates that the average youth buys more than 3 types of items from one of their favorite brands From that conclusion, on the whole, young people on average do not buy only one type of product from their favorite brand

Hypothesis 2: On average, young people only buy clothes on a particular channel

With a test value of 1 (number of youth clothing shopping channels is 1), after performing the test,

we can calculate the t-value equal to 16,887 and the p-value equal to 0,000 < 0,05, reject H0, accept

H1 Specifically, the mean sample value - Mean is 1,5740 indicates that young people shop for clothes