Factor 7: Passing Trend
4.4.8 Objective 8: The Impact of Age and Gender on Social Media Browsing in the Youth Market
The above objective was addressed using cross tabulations in order to categorize the relationship between the cross tabulated variables namely ‘age’ and ‘do you actively seek out brand pages on social media platforms’, in order to establish if age has an impact on social media browsing. The result of the cross tabulation shown in Table 4.27 which reveals the Pearson Chi-Square test value of p=0.0632, implies that there is no significant relationship between age and social media browsing in the youth market. This finding is supported by other researchers such as Hargittai (2007) and Treadaway and Smith (2010).
Table 4.27: The Relationship between Age and Seeking Information on Social Media Platforms (n=145)
Value Df Asymp. Sig.
(2-sided)
Exact Sig.
(2-sided)
Exact Sig.
(1-sided)
Point Probability
Pearson Chi-Square .918a 2 .632 .781
Likelihood Ratio 1.042 2 .594 .781
Fisher's Exact Test 1.129 .605
Linear-by-Linear Association
.796b 1 .372 .521 .280 .169
N of Valid Cases 145
a. 3 cells (50.0%) have expected count less than 5. The minimum expected count is .72.
b. The standardized statistic is -.892.
A cross tabulation was also conducted between the variables ‘gender’ and ‘do you actively seek out brand pages on social media platforms’, in order to determine if gender has an impact on social media browsing. The result reflected in Table 4.28, shows a Pearson Chi- Square test value of p=0.009., which indicates that there is a significant relationship between
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gender and social media browsing. Hence, gender influences social media browsing in the youth market. This finding is supported by Hargittai (2007).
Table 4.28: Relationship between Gender and Seeking Information on Social Media Platforms (n=145)
Value Df Asymp. Sig.
(2-sided)
Exact Sig.
(2-sided)
Exact Sig.
(1-sided)
Point Probability
Pearson Chi-Square 6.865a 1 .009 .014 .009
Continuity Correctionb 4.984 1 .026
Likelihood Ratio 9.561 1 .002 .014 .009
Fisher's Exact Test .014 .009
Linear-by-Linear Association
6.817c 1 .009 .014 .009 .009
N of Valid Cases 145
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Value Df Asymp. Sig.
(2-sided)
Exact Sig.
(2-sided)
Exact Sig.
(1-sided)
Point Probability
Pearson Chi-Square 6.865a 1 .009 .014 .009
Continuity Correctionb 4.984 1 .026
Likelihood Ratio 9.561 1 .002 .014 .009
Fisher's Exact Test .014 .009
Linear-by-Linear Association
6.817c 1 .009 .014 .009 .009
N of Valid Cases 145
a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 3.38.
b. Computed only for a 2x2 table c. The standardized statistic is 2.611.
Given the aforementioned findings, marketers need to realize that the ‘offline’ identities of consumers such as gender affect their ‘online’ interactions, which have a direct impact on their social media browsing patterns, usage patterns and purchasing behaviour. This is also supported by researchers such as Boyd (2001), and Smith and Kollock (1999). In addition, some studies have revealed that gender has a profound impact on Internet usage (Hargittai, 2007; Bimber, 2000 & Hargittai & Shafer 2006). Furthermore, studies have shown that men spend more time ‘online’ and claim higher-level computer skills (Bimber, 2000; Hargittai & Shafer, 2006; Jackson, Ervin, Gardner, & Schmitt, 2001;
Ono & Zavodny, 2003).
Table 4.29 shows that a large majority (77 percent) of respondents have made use of social networks to make purchases. Hence, social networks are the most predominantly utilised social media platform by respondents for making purchases. This represents several opportunities for marketers and businesses to exploit.
Table 4.29: Social Media Platforms that Respondents have Purchased From (n=145) Social media
platform Frequency Percentage Cumulative percentage
Social Networks 116 77.3 96.7
Content
Communities 73 48.7 60.8
Vlogs 57 38.0 47.5
Blogs 41 27.3 34.2
Podcasts 8 5.3 6.7
Wiki’s 5 3.3 4.2
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Table 4.30 reveals that 79 percent of respondents indicated that they would return to a company page or brand page on social media platforms because of the excellent product search options and discounts or specials and, 77 percent would do so only in order to keep up to date with the latest trends, because of the interactive nature of the social media platform and the availability of consumer recommendations and ratings. This provides valuable information on how marketers and managers can attain and retain users on social media platforms. The findings (Table 4.30) are supported by research carried out by ROI research which stated that 49 percent of respondents expressed a strong desire to receive more printable coupons on social media platforms, 46 percent notifications on sales and special deals and 35 percent on information on new products (Performics Company, 2011).
Table 4.30: Reasons why Respondents would return to a Company or Brand Page on Social Media Platforms (n=145)
Reason Frequency Percent Cumulative
percentage
Excellent product search options 118 78.7 98.3
To find discounts or specials 118 78.7 98.3
To keep up to date with the latest trends 116 77.3 96.7
Interactive nature of the social media platform 115 76.7 95.8 Availability of consumer recommendations and
ratings 115 76.7 95.8
4.5 Conclusion
This chapter presented the results of the data analysis, using various statistical techniques to address the objectives of the study. The demographics of the respondents, their usage patterns of social media platforms and, the purchasing behaviour of respondents who purchased through social media platforms was analyzed and reflected using frequency distributions, cross tabulations and multiple regression. Factor analysis was undertaken in order to establish if social media browsing led to purchasing by consumers in the youth market and if so, to what extent and why. Factor analysis was also used to identify market segments found within the youth market and the impact of these market segments on the purchasing behaviour of consumers. In addition, cluster analysis was conducted in order to determine the potential value of social media as a promotional tool.
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The findings of this study revealed that social media browsing within the youth market does lead to purchasing behaviour. The purchasing behaviour of respondents who purchase through social media platforms are influenced by several factors identified in the literature of this study and the findings. The findings of the study identified several market segments of consumers and the impact of these market segments on the purchasing behaviour of consumers. In addition, the literature and findings of the study revealed the significant potential of social media as a promotional tool.
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