The Influence that YouTubers Have towards the Consumers Purchase Intention - Case Study Example

Data Analysis Name: Tutor: Course: Date: Data Analysis The aim of this research study was to investigate the influence that YouTubers have towards the consumers purchase intention. A total of 119 respondents were involved in this study which was conducted online on Qualtrics.com. i) Age of respondents Table 1: Age of respondents Age Frequency %Frequency Below 18yrs 1 8.4% 18-20yrs 34 28.5% 21-23yrs 75 63.0% 24-25yrs 9 7.5% Over 26yrs 0 0% Total 119 100% From the table above, majority of the respondents were 21-23 years (75) of age representing 63% of the total count. This was closely followed by to age 18-20 years (34) representing 28.5% of the total count. There were no respondents aged above 26 years. The graphical presentation of respondents’ ages is as shown in the figure below. Figure 1: Age of respondents ii) Gender of respondents Table 2: Gender of respondents Gender Frequency %Frequency Male 39 32.7% Female 80 67.3% Total 119 100.0% As shown in the table above, majority of the respondents were female 80(67.3%) while the rest were male 39(32.7%). This count is also represented in the pie chart below. Figure 2: Pie chart showing gender of respondents iii) Descriptive statistics Table 3: Descriptive statistics From the table above, the mean average weekly time spent by YouTube users was 2.69 hours. The standard deviation from the mean is high at SD=1.158 indicating that the variance from the mean was high. Similarly, it has a kurtosis of -0.4 which indicates a light tailed distribution and positive skewness of +0.554 which shows that the data is skewed to the right i.e. the left tail is longer compared to the right tail. In addition, the mean age is 2.77 which is a value between 2 and 3. This means that the mean age is between 18 and 23 years with negative skewness and positive kurtosis. iv) Factors affecting consumer purchase intention of product information Age and gender of respondents were considered as some of the factors that influence consumer purchase intention. The following hypotheses were formulated; H11: Age affects the attitudes of consumers when acquiring product information from YouTubers. H10: Age does not affect attitudes of consumers when acquiring product information from YouTubers As shown in table 4 below, respondents below 18 years of age insisted that the functionality of YouTube is very important in making purchase intentions. On the other hand, those aged 18-20 years noted that accessibility 16(41%) was an important in making purchase intention. The same case applied to respondents aged between 21-23 years and those aged 24-25 years which indicated that they found accessibility as a critical factor in making purchase intention of YouTube. However, the Pearson Chi-square and Phi values were not statistically significant at (p=0.05), which indicates that the hypothesis is not statistically significant. We therefore accept the null hypothesis that ages of consumers do not influence their YouTube purchase intentions. Table 4: Age and attitudes factors of respondents On the other hand, gender was also considered factors that influence the attitudes of consumers to buy YouTube services. The following hypotheses were formulated; H21: Gender affects attitudes of consumers when acquiring product information from YouTubers H20: Gender does not affect attitudes of consumers when acquiring product information from YouTubers As indicated in the table below, male respondents 25(64.1%) said that accessibility was more critical attitudinal factor in determining the purchase intention. Similarly, majority of the female respondents 36(45.6%) and 21(26.6%) noted that accessibility and functionality were critical attitudinal factors that affect YouTube purchase intentions respectively. Based on the chi-square and symmetry measures (Phi), it shows that the data was statistically significant at (p=0.05). The values shows (Phi=0.286; p=0.02) which indicates that the degree of association between the variations is fairly high. Based on this observation, we then reject the null hypothesis and accept the alternative hypothesis that gender affects attitudes of consumers when acquiring product information from YouTubers. Table 5: Gender and attitude factors of respondents v) Influences and factors to purchase intentions The study sought to know how YouTubers influenced the purchase intention of its audience according to these factors. The following hypotheses were formulated. H31: Users are prevailed by certain factors and qualities to influence their YouTube purchase intention H30: Users are not prevailed by certain factors and qualities to influence their YouTube purchase intention From the table below, the factor analysis of the elements that contribute to purchase intention were analyzed. The first component tends to measure the intention to purchase YouTube services. The loadings of more than 0.4 were taken and it shows that; time-saving (loading=0.693) and multitasking ability (loading=0.581) have strong correlations. The second component could be viewers who prefer social media or Television channels. This shows that this component of watching YouTube is highly preferred by users who intend to save time and also multitask. The correlations are positive. We therefore reject the null hypothesis and accept the alternative hypothesis that users are prevailed by certain factors to influence their YouTube purchase intention. Table 6: Factor analysis of factors influence purchase intention Similarly, the qualities or influences that affect the purchase intention among YouTube users are as shown in the table below. The Spearman correlation matrix table shows that the number of viewers and subscribers to YouTube are affected to a greater degree by the level of detail of content (r=-0.479**; p=0.01) and the quality of editing (r=-0.346**; p=0.01) influence the level of credibility of YouTubers. This was followed by followed by a distant third by the number of likes and dislikes (r=-.100; p=0.05) and feedback from the comments section (-0.039; p=0.05). However, the last two influences were seen as not significant at p=0.05. This shows that higher number of viewers and subscribers may are affected by the quality of editing and the type of content. On the same vein, we accept the alternate hypothesis that users are prevailed by certain qualities such as level of detail of content and quality of editing towards their YouTube purchase intention. Table 6: User factors and qualities on YouTube purchase intention vi) Decision-making process and purchase intention The study observed that product information required by the customers to make decisions will influence their purchase intention. The following hypotheses were formulated; H41: Users are likely to get influenced by product decision-making process on their purchase intention YouTube H40: Users are not likely to get influenced by product decision-making process on their purchase intention of YouTube From the table below, customers who said they had a better understanding of a product or service after acquiring information 61(55.5%) from Youtubers were somewhat likely to purchase a product recommended by the YouTubers. This implies that customers with prior product information were more likely to be aware of the product that they want to purchase. However, the phi=0.278 showing the association between the variables were not significant at p=0.05. We therefore accept the null hypothesis that users are not likely to get influenced by product information in the product decision-making process on their purchase intention YouTube. This means that the customers are irrational and can made decisions based on the product brand and not as recommended by the YouTubers. Table 7: Product information and purchase intentions on recommendations On the same vein, the ease of making purchase decisions in correlated to factors associated with the intention to purchase. The hypotheses were formulated as follows; H51: There is a statistically significant relationship between services and goods recommended by YouTubers and ease of making purchase decisions H50: There is no statistically significant relationship between services and goods recommended by YouTubers and ease of making purchase decisions As shown in the table below, the ease of making purchase decisions is influenced by the availability of product information to customers. However, consumers have certain opinion regarding the intention to make such decisions. From the table, the ease of making purchase decisions is positive correlated to all the three variables; renewed interest in services and goods (0.306**; p=0.01), change in opinion and visions of a give product (0.287**; p=0.01) and the risk of low quality (0.371**; p=0.01). The results show that the three factors influence the ease of making purchase decisions after watching YouTube videos that review products one is interested in. The null hypothesis is rejected and the alternative hypothesis accepted that there is a statistically significant relationship between services and goods recommended by YouTubers and ease of making purchase decisions. Table 8: Services and goods recommended by YouTubers and ease of making purchase decisions Summary The results show that majority of the respondents are women and also the age group of 21-23 years. While this age bracket found accessibility as a critical factor in making purchase intention of YouTube, age of consumers was established to be influencing their YouTube purchase intentions. However, gender was found to affect attitude factors of consumers when acquiring product information from YouTubers. Users were prevailed by certain factors such as multitasking ability, level of detail of content, quality of editing, and time-saving as influencing their YouTube purchase intention. Meanwhile, users are not likely to get influenced by product information in the product decision-making process on their purchase intention YouTube. The results showed that there is a statistically significant relationship between services and goods recommended by YouTubers and ease of making purchase decisions. Read More