INTRODUCTION

Thanks to innovations in communication technology, creative thinking, and the ever-changing dynamics of different channels of communication, new forms of communication like social media have emerged, facilitating instantaneous access to information. In recent years, social networking sites have exploded in popularity, providing a great place to meet new people, have meaningful conversations, share information, and stand out from the crowd. Companies and individuals are able to communicate more easily because of this. This disparity is becoming smaller because to social media. These days, most young people's social lives revolve on various forms of online communication and sharing, including but not limited to: making new friends, sharing content (such as videos and photos), and more. Social media allows people to connect with others who share their interests and goals. Internet marketing is impacted by the ever-growing significance of social media (Dissanayake, 2019).

Another perk of doing business online is the opportunity for direct communication with customers. This allows companies to learn more about their likes, preferences, and customer service habits, as well as to stay in close touch with their target audience. The creation of a plan for selling the products is facilitated by this (Park, 2021). They may now reach a large enough audience to get prompt feedback from their customers. Personal interaction is made possible via online purchasing platforms. Customer satisfaction is enhanced when they are able to positively recommend a product or service to others. Revenue, market share, and name recognition all take a hit when customers leave, but a solid customer base helps keep customers coming back. With proper preparation and execution, social media may be an inexpensive means of internet advertising (Jain, 2021).

Internet companies may reach local customers using social media by advertising their products' characteristics, quality, sales, and other facts and by providing interesting and useful content to keep people engaged. Branding, product development, and customer service are some of the ways it could be used by e-commerce companies. The primary function of social media is the dissemination of content that encourages users to engage in real-time conversations and, ultimately, makes a purchase. They can't function without social media these days. In order to bolster a purchase, consumers seek for praise. Suddenly, they're seen as crucial. There are a lot of factors contributing to the increased activity and comfort level of online shoppers these days. These include people's busy modern lives, longer workdays, the ability to browse products from the convenience of one's own home, more options, etc. Social media and online business networking sites help companies find a variety of high-quality goods and services for their customers, which is useful for many things like buying clothes, shoes, leather belts, purses, jewellery, and more (Ibrahil, 2022).

The word "e-commerce" refers to the practice of buying and selling goods and services online via a website or branded app. Users may access the websites from any device, including desktop computers, mobile phones, and tablets (Laroche, 2021). Marketing strategies that target the top of the sales funnel, such as digital advertisements and social media posts, bring in clients for online businesses. There are additional steps in the buying process that customers must do when they reach the store, increasing the likelihood that they may lose interest and the transaction. Furthermore, 86% of mobile shoppers abandon their carts while 92% of active internet users access the web using mobile devices. Sadly, there are certain e-commerce websites that do not support responsive design. Using social commerce, businesses can reach customers wherever they are, rather than just pointing them in the direction of an online store. Social commerce streamlines the buying process by allowing direct payment via social media platforms. The outcome is an improvement in the shopping experience for customers and an increase in revenue for the store. Social commerce is also a great approach to reach a wide range of consumers since most social media platforms are mobile-friendly (Laroche, 2021).

So, if you want to reach your target audience and establish a lasting impression of your business, social media marketing is a great way to do it. Because of this, the idea of social media influencers (SMI)—people with a large number of followers on social media—has emerged. Basically, these social media influencers are the new drivers of clothes promotion. They do this by providing consumers with reliable and direct information via posts, which may be text, audio, or video. People who are interested in the aforementioned apparel items are more inclined to buy them if they are promoted to follow SMIs (Soegoto, 2022).

RESEARCH METHODOLOGY

It is typical practice in research to employ survey questionnaires to gather data, and that is exactly what this study did. The surveys were sent out via various email campaigns and received within a few days from a wide variety of social media users (Facebook Messenger, Twitter, Instagram, WhatsApp, etc.). Also, a qualitative research strategy is used in this study. It is via qualitative research that the relationship between causes and effects may be shown.

Participants in this study are social media users from Northern Cyprus who have made purchases online and utilise sites like Facebook, Twitter, and Instagram.

Four hundred people are considered to be a representative sample for the research.

In order to reach a wide variety of individuals, this study's research tool of choice is a survey questionnaire.

Alternatively, data sources that were primarily obtained from another research but were also relevant to the current inquiry are known as secondary data sources. In order to compile secondary data for this investigation, relevant articles were reviewed. Books, journals, annual reports, and unpublished studies.

In order to gather and assess the numerical data, S.P.S.S (vs23) was used. There are a lot of reasons why this software package was chosen, one of which is that it helps the researcher spot data input issues.

DATA ANALYSIS

Demographic details of the participants

Gender Demographic

According to Table 1 below, out of a total of 180 participants, 45.0% were male, 37.5% were female, and 17.5% were from other backgrounds.

Table 1: Responders’ Gender Distribution

Frequency

Percentages (%)

Male

180

45.0

Female

150

37.5

Other

70

17.5

Total

400

100.0

Source: Field Study

Age Distribution

The age range of the participants, 38.5% or 154 individuals, is 20–25 years old, as shown in Table 2 below. 117 persons, or 29.3% of the total, are in the 26–30 age bracket. There are 51 persons, or 12.8% of the total, who are in the 31–35 age bracket, and 39 individuals, or 9.8% of the total, who are in the 36–40 age bracket. Finally, there are 39 individuals (or 9.8% of the total) who are 40 and above.

Table 2: Participants’ Age Range Distribution

Frequency

Percentages (%)

20-25

154

38.5

26-30

117

29.3

31-35

51

12.8

36-40

39

9.8

40+

39

9.8

Total

400

100.0

Source: Field Study

Employment Status

The following statistics are derived from the survey: 14.0%, or 56 people, are employed; 19.3%, or 77 people, are self-employed; 12.3%, or 49 people, are jobless; 5.5%, or 22 people, are retired; and 49.0%, or 196 people, are students.

Table 3: Respondents’ Employment Status Distribution

 

Frequency

Percentages (%)

Employed

56

14.0

Self-Employed

77

19.3

unemployed

49

12.3

Retired

22

5.5

Student

196

49.0

Total

400

100.0

Source: Field Survey

Respondents’ Household Gross Income

The data in table 4 shows that out of the total number of respondents, half (82 people) have an annual gross household income of less than $1,200. One hundred and ten people fall in the middle, with an income of $1,200 to $2,500. Twenty-eight people make between $2,500 and $5,000, and seventeen people do the same for $5,000 to $10,000. Lastly, 36 respondents, or 9.0% of the total, fall within the $10,000–$100,000 income bracket. And lastly, 20 respondents, or 5.0% of the total, had a yearly gross income of $120,000 or more.

Table 4: Participants’ Household Gross Income Distribution

Frequency

Percentages (%)

Less than $1,200

82

20.5

$1,200-$2,500

110

27.5

$2,500-$5000

82

20.5

$5000-$10,000

70

17.5

$10,000-$100,000

36

9.0

$120,000 and more

20

5.0

Total

400

100.0

Source: Field Study

TEST OF NORMALITY

All of the variables in this research were tested for normality using the Shapiro-Wilk and Kolmogorov-Smirnov tests. You can see that the variables' Sig. values are less than the alpha value for the Kolmogorov-Smirnov and Shapiro-Wilk tests in table 5 below. This finding rules out the possibility of normally distributed data.

Table 5: Tests of Normality

Kolmogorov smimova

Shapiro-Wilk

 

Statistic

df

Sig

Statistic

df

Sig

SMM

.096

400

.000

.941

400

.000

OPI

.094

400

.000

.954

400

.000

PU

.122

400

.000

.934

400

.000

PEU

.125

400

.000

.916

400

.000

AT

.178

400

.000

.893

400

.000

SN

.100

400

.000

.957

400

.000

 

Lilliefors Significance Correction

CORRELATIONS

All of the dependent variables have a positive association with all of the independent variables, as shown by the correlation coefficients in table 6 below. Additionally, the results show that when one variable goes up, the other goes up as well, and the other way around.

Table 6: Correlations

 

OPI

PEU

SMM

PU

AT

SN

OPI Pearson correlation Sig.(2-tailed) N

1

400

.683**

.000

400

.704**

.000

400

.697**

.000

400

.551**

.000

400

.472**

.000

400

PEU Pearson correlation Sig. (2tailed) N

.683**

.000

400

1

400

.642**

.000

400

.716**

.000

400

.676**

.000

400

.507**

.000

400

SMM Pearson correlation Sig. (2tailed) N

.704**

.000

400

.642**

.000

400

1

400

.763**

.000

400

.417**

.000

400

.291**

.000

400

PU Pearson correlation Sig. (2tailed) N

.697**

.000

400

.716**

.000

400

.763**

.000

400

1

400

.539**

.000

400

.394**

.000

400

AT  Pearson correlation Sig. (2tailed) N

.551**

.000

400

.676**

.000

400

.417**

.000

400

.539**

.000

400

1

400

.620**

.000

400

SN  Pearson correlation Sig. (2tailed) N

.472**

.000

400

.507**

.000

400

.291**

.000

400

.394**

.000

400

.620**

.000

400

1

400

**Correlation is significant at the 0.01 level (2-tailed).

CONCLUSION

The major goal of this study is to determine the extent to which social media marketing affects customers' tendency to make online purchases. Researchers found that social media marketing significantly influences people's inclination to shop online. In order to attract customers, online stores selling a wide variety of goods and services need active social media marketing strategies. There has to be greater communication between management and the prospective customers' online community in order to share information and create a platform that is much more interactive.