Studying the Impact of Social Media Marketing Attributes on the Purchase Intention of Indonesia’s Local Beauty Line
Novelin Magdalena Anggrecia Tesalonika1*
1 School of Business & Management, Institut Teknologi Bandung, Bandung, Indonesia
*Corresponding Author: novelin_magdalena@sbm-itb.ac.id
Accepted: 15 September 2022 | Published: 1 October 2022 DOI:https://doi.org/10.55057/ijbtm.2022.4.3.28
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Abstract: The COVID-19 pandemic has severely affected many industries and is deemed to be a major influence on the change in business practices. With the large-scale social restrictions imposed in Indonesia, the local beauty industry needs to restructure its strategy due to the absence of in-store try on. Many brands then implement the use of social media marketing as it is believed to reach customers digitally even without the need for a physical store. In response to this situation, this research will look at the notion of leveraging social media marketing attributes as a significant medium for boosting the purchase intention to keep beauty items desirable and trustworthy even when the product is not directly tried. Furthermore, it will also investigate the usefulness of each of the social media marketing attributes types of digital marketing techniques that are most commonly utilized when promoting beauty products online.
A quantitative approach will be used in this study through data gathered from online questionnaires answered by 203 respondents. This research uses descriptive statistics, Post- Hoc Tests, and a one-way ANOVA test for data analysis. As a result, this result finds a significant difference between each of the social media marketing attributes. These attributes consist of electronic word of mouth, influencer attributes, interactivity, knowledge sharing, trust, and personalized experience. The results indicate that the electronic word of mouth and influencer attributes are the elements with a higher perceived effectiveness level towards the purchase intention of Indonesia’s local beauty products, whereas the rest of the attributes are found to have a significant difference in terms of the mean by a considerably lower value. These findings contribute to the utilization of social media marketing as a way to effectively boost purchase intention in the beauty industry.
Keywords: Social Media Marketing, Beauty Industry, Purchase Intention, Digital Marketing ___________________________________________________________________________
1. Introduction 1.1. Background
There has been a vast amount of research surrounding the topic of digital marketing effectiveness in business practices, especially with the rapid growth of digital technology as a result of the COVID-19 pandemic. On the one hand, it has been found that the outbreak becomes an accelerator for Indonesia’s local beauty industry since companies are challenged to be more innovative (Kompas.com, 2020). The beauty and personal care market itself comprises four main items which are cosmetics, skincare, personal care products, and fragrances. The absence of in-store try-on makes it very important for beauty brands to quickly adapt to the situation to maintain or potentially grow the sector even larger. As the use of digital
marketing is believed to be fairly high in Indonesia (Najib et al., 2018), utilizing digital marketing to boost purchase intention can be a way to outsmart the negative impact of the outbreak on Indonesia’s local beauty line.
According to the McKinsey & Company report, there are three areas in the industry that will fundamentally be altered. These areas include the rising of digital channels, the increased need for innovation, and the company’s funding. With the substantial social media influence, it becomes more evident that digital marketing plays an important role in marketing practices, especially after the pandemic hit. This put social media marketing to be an interesting subject to dig deeper into. As social media marketing comprises various elements for it to operate optimally, more thorough research on the impact of its attributes can be a value-added to maximizing the digital presence of Indonesia’s local beauty line and indirectly impact the customer’s intention to make a purchase.
1.2. Problem Statement
The sudden transformation as a result of the COVID-19 pandemic has adversely impacted the beauty industry globally as most people do not go out as often due to remote working and there is an obligation to wear a mask in public areas (Gardner et al., 2021). According to Kwon (2021), there is a shift in the purchases of cosmetic items before and after the COVID-19 pandemic hits. It is found that people would avoid coloured makeup, stock up on basic cosmetics while wearing masks, and refrain from purchasing makeup-related items. Make-up usage then became irrelevant as people spend most of their time at home. The data is further supported by the fact that findings were proving the noteworthy losses in the beauty industry and a decrease in the total revenue ever since the pandemic started (Fernandez, 2020). The implementation of social media marketing could then have a substantial impact on purchase intention.
1.3. Research Question
How do different attributes of social media marketing become preferable in helping customers develop purchase intention behaviour?
1.4. Research Objectives
1) To identify which social media marketing attributes have the most significant impact on the purchase intention of Indonesia’s local beauty line.
2) To recommend social media marketing attributes to use for Indonesia’s local beauty line to communicate effectively with its target audience.
3) To find out the difference between the perceived impact of social media marketing attributes in boosting the purchase intention of Indonesia’s local beauty line.
2. Literature Review
2.1. Digital Marketing Communication
Companies are increasingly embracing the adoption and use of digital tools to construct and improve current business processes. Aside from immediately helping businesses, evolving technologies assist firms in developing the workplace culture and improving the customer experience (Kamble et al., 2021). Many digital artefacts, online platforms, and digital infrastructure-building activities have evolved from significant demand for digital technology during the previous two decades (Modgil et al., 2021). Digital artefacts themselves are defined as digital elements and information that are associated with products and services that support a certain function for the end user’s benefit (Liu et al., 2021). Its application has attracted
businesses as it is mainly useful in the areas of service creation, marketing, and distribution (Nambisan, 2017).
Throughout the COVID-19 pandemic, the use of digital marketing has increased significantly as many brands perceive it to be very effective in replacing conventional promotional activities.
The term "digital marketing" itself refers to the use of the internet to send promotional marketing messages to customers (Prathivi, 2019). The traditional marketing strategies are deemed less effective since there is a shift in consumers' purchasing mode preference towards online stores instead of going to a physical store (Martínez et al., 2021). Indeed, Shankar, Grewal, and Sunder et al. (2021) found that as a result of the outbreak, 80% of customers seem to be more receptive to companies’ digital services and put a greater value on digital encounters. The spread of communication technology, as well as shifting attitudes toward digital interactions and digital experiences, may encourage more digital cross-border contacts, allowing businesses to improve their digital strategic approach. Then, as the world is entering the digital economy, the ability of a company to research and harness digital technology is critical to its success (Saputra et al., 2022).
The marketing approach using digital media has a favourable impact on the company's success.
In Indonesia, using a digital marketing approach to advertise items is seen as quite beneficial, particularly for enterprises that are still in the early stages and do not yet have their own store (Najib et al., 2018). In accordance with Genú (2019), there are four main digital communications tools that can be utilized in executing digital marketing practices which consist of Email Marketing, Online Brand Communities, Social Media, and Search Engine Optimization. Amongst all the available tools, social media remains the most used and effective digital marketing tool in the Indonesian market as a result of rapid growth in internet and social media usage rates which put Indonesia as one of the fastest-growing mobile commerce marketplaces in the world (Uy, 2021).
2.1.1. Social Media Utilization
Social media is one of the communication tools used in digital marketing practices (Genú, 2019). It is often confused with the term social networking as both are media that convey data and communicate different kinds of information. According to Alalwan et al. (2017), social media is a communication platform that allows users to publicize, approach, and persuade many others while also sharing user-generated content across companies and individuals.
Whereas social networking is known to be the services, programs, sites, or electronic platforms that are utilized by individuals that have similar interests. The fact that social media has the power to share real testimony regarding a certain product or service caught the attention of many researchers to dig deeper into its effect on driving brand loyalty, purchase intention, and customer behaviour (Subriadi and Baturohmah, 2021). The influence of social media on customer behaviour is then viewed as the primary information source and is utilized to make purchase decisions. In addition, it also found that engaging in social media is a powerful marketing tool that has a significant and beneficial impact on a company's capacity to increase customer loyalty and purchase behaviour (Alalwan et al., 2017). Hence, to boost value co- creation, more businesses are utilizing social media to improve direct relationships with consumers and stakeholders (Bu et al., 2022).
2.1.2. Purchase Intention
Grewal, Monroe, and Krishnan (1998) identified purchase intention as a likelihood held by buyers who plan to acquire a specific product. It is found that there are eight main factors that play an important role in influencing buying intention. Those factors include branding, product
quality, pricing, product design, advertising, retail atmosphere, customer experience, and brand familiarity (Janany & Shanmugathas, 2018). However, despite all the quality that a certain brand offers, purchase intention is also dependent on the recommendation given by the previous customers who have tried the product. This is where user-generated Word of Mouth (WoM) plays a role in consumers' spontaneous forwarding and referrals of products that is believed to be worthy of attention (Hoy & Milne, 2010).
2.1.3. Electronic Word of Mouth (eWoM) to Purchase Intention
All the shared experiences about a product or service through social media are referred to as electronic Word of Mouth (eWoM) (Donthu et al., 2021). Instead of relying on the company site or conventional information sources, the content generated by eWoM on social media is seen as a credible, unbiased, and easily accessible source of information (Subriadi and Baturohmah, 2021). It becomes evident that consumers' brand involvement and projected brand value can directly affect customers' purchase intentions in the context of social media (Bu et al., 2022). Furthermore, voicing opinions can stimulate purchasing intentions even further by attracting a greater deal of attention through the power of influencers. When compared to brand-generated content, scholars argue that influencer-generated messaging is more organic and capable of hitting prospective target consumers (Lou & Yuan, 2019).
It is ascertained that psychological drive plays an important role in determining consumer buying intention. There is this term called homophily which is believed to be the degree to which visual characteristics are comparable (Ladhari et al, 2020). Customers' involvement behaviour can be positively influenced by homophily, which encourages audiences to seek and share knowledge while also promoting responsible behaviour and personal engagement.
Therefore, Influencers should pay attention to common traits among target audiences, especially when aiming to attract prospective customers who have similar views, personal experiences, beliefs, and even physical qualities (Bu et al., 2022).
2.1.4. Influencer Attributes
There has been a significant increase in the number of influencer marketing practices (Lou &
Yuan, 2019). This method of promotion aims at utilizing people that have the potential to bring massive exposure to a particular product or service or are known as influencers. With the possibility of achieving viral growth in the market, partnering with influencers is believed to be an effective way for achieving a larger audience organically (Bu et al., 2022). It found that In comparison to brand-related content, influencer-generated content is perceived to be natural and able to reach prospective markets more easily (Lou & Yuan, 2019). In addition, the para- social relationship that exists from influencer marketing practices can create some kind of imitation effect that inspires social media followers to imitate influencers through consumption (Bu et al., 2022).
2.1.5. Interactivity
Aims to give end-users the ability to communicate successfully to obtain information, with the end-user controlling the timing, material, and sequencing of the communication (S et al., 2020).
The media features allow users to alter the functions of social media in a variety of ways, such as customizing profiles, scrolling down for sources, and many more. It gives so many advantages for users as they can participate in a number of activities such as sharing sentiments and ideas, joining online campaigns, and broadening their understanding of the value of a certain brand. With that being said, the interactivity elements of social media provide benefits that enable users to engage in reciprocal exchanges (Gu et al., 2013).
2.1.6. Knowledge Sharing
According to Yepeng et al. (2022), knowledge sharing is defined as actions by which individuals exchange and transmit information with one another, while co-creating new knowledge. Knowledge sharing requires two circumstances which are the capacity to share and the willingness to share. By fulfilling these two criteria then the information exchange can take place (Chiu et al., 2006). On the one hand, social media brings people together from all over the world, making it an increasingly popular medium for knowledge exchange and collaboration. Furthermore, online sharing has been proven to offer numerous benefits over offline sharing, including variation, virtuality, and versatility (Harrigan et al., 2020).
2.1.7. Customer Trust
As social media usage is expanding, its reliability is being questioned due to the numerous scams that exist in it. Social media usage then becomes heavily dependent on the ability of message senders to capture the trust of the audience towards the shared information. Trust itself was found to be the important factor that determines the way influencing behaviour is perceived in society (Johnson et al., 2022). In the context of social media, the main factors that influence user trust towards information are the quality of the information itself, security perception, privacy, and structural safeguards (Khan et al., 2003). Therefore, the study will further highlight trustworthiness as one of the factors that influence customer preference for social media usage by brands.
2.1.8. Personalized Experience
It is discovered that when marketers customize the experience, 80 per cent of customers are more inclined to make a purchase (Epsilon, 2018). Advertisers personalize the experience by gathering data about customer attitudes and preferences through personal data collection. The collected data usually consisted of user interest, demographics, and past actions taken on social media (Hayes et al., 2021). Although tailored advertising allows advertisers to send relevant messages to the appropriate consumer, there are system downsides that may put customers at disadvantage. The personalized content that customers receive may suit their preferences, but it means that their personal information can be wrongly used by others to jeopardize their privacy. Therefore, the reliability of personalization messages in social media is then being questioned.
2.2. Hypothesis Development
The null hypothesis, in this case, would be that all the social media attributes have the same level of impact according to the mean influencing customers’ intention of buying Indonesia’s local beauty line products. Whereas the alternative hypothesis is that there is a difference in the mean between all the social media attributes. A represents electronic word of mouth, B represents influencer attributes, (C represents interactivity, D represents knowledge sharing, E represents trust, and F represents personalized experience.
H0: μA=μB=μC=μD=μE=μF H1: Not all μ’s are the same
3. Methodology
3.1. Methods of Data Collection
The primary data were gathered using the survey method through the creation of an online questionnaire hosted on Google Forms. The survey will be constructed with a combination of multiple-choice, short answers, and linear scales. The questionnaire will be distributed through social media platforms in order to reach a wider audience. Each form is intended to be filled in
by one respondent only to provide an individual point of view with the data kept confidentially to avoid any ethical misguidance. Whereas concerning the study subject, the respondents are assessed on social media attributes comprised of electronic word of mouth, influencer attributes, interactivity, knowledge sharing, trust, and personalized experience, as summarized in exhibit 4.1. The cross-sectional study is then the preferred method as the data were gathered at one point in time, which is within the period of one month since the online form is launched.
5 Point Likert Scale was then used to measure the respondent’s opinion. In addition, this approach provides greater control over the measurement process and allows multiple variables to be measured at the same time.
3.2. Population and Sample
The survey will be addressed to female and male local beauty product online purchasers ranging from 15 years old and older. As for the sampling method, the study will utilize probability sampling (simple random sampling specifically) as it is believed to help ensure that the sample is representative and unbiased. A total of 203 data points were gathered from diverse participants' backgrounds as it is perceived to be the minimum number of participants to reflect the Indonesian online beauty market in a smaller group.
3.3. Methods of Analysis
On the subject of analyzing the gathered data, outlier identification will first be conducted in order to obtain a more accurate representation. All of the participant’s answers that are outside of the intended demographic will be removed from the analysis. The gathered data is analyzed using a one-way ANOVA to assess whether there are any statistically significant differences between the means of the different social media marketing attributes toward purchase intention.
Since this study aims to determine which social media marketing attributes gives the most significant impact on the success of Indonesia's local beauty line in boosting purchase intention, finding the significant difference between each of the attributes will help find the relationship through the comparison of the assessed variables. Social media marketing attributes will then be the independent variable, whereas purchase intention of Indonesia’s local beauty line will be the dependent variable. Then, as the research is conducted quantitatively, the survey respondents' answers will be numerically processed further using SPSS software. This software has the capability to conduct complex statistical analyses while generating descriptive statistics to get the general view of the assessed data.
3.4 Methodology Limitations
Implementing online surveys for research purposes can lead to methodological limitations. The obtained data may be biased as the population to which online surveys are dispersed cannot be characterized. Furthermore, the lack of male perspectives can lead to gender biases which may not represent the whole market. However, despite the possible biases, market analysts found that people prefer to do online surveys overprinted questionnaires or phone interviews and they offer longer and more thorough responses. Then, with an online survey, participants may be pre-screened so that only those who fit the intended profile are allowed to participate. Hence, all the mentioned strengths outweigh the drawbacks. The data validity and reliability test can also be performed to strengthen the database.
4. Data Collection and Analysis 4.1. Survey Data Collection
A total of two hundred and four respondents managed to complete the assessment and their answers were recorded as per permission. The data gathered is measured and analyzed into six
categories; (A) electronic word of mouth, (B) influencer attributes, (C) interactivity, (D) knowledge sharing, (E) trust, and (F) personalized experience. The details will be explained in the following sections. However, since there are criteria that respondents needed to follow, not all recorded answers could be processed. In this survey, there was one participant that did not agree with the way their data was collected and wished to submit the survey right away without completing all the questions list. This one participant was then becoming the outlier that was taken away from the data processing.
4.1.2 Respondents Socio-Demographic Profile 4.1.2.1. Age
From the total of 204 respondents, it can be seen that the results are dominated by the respondents from the age group of 25 to 34 years old by 121 responses. Then, there are 66 respondents (32.5%) that are aged between 15 to 24 years old and 16 respondents (7.9%) with aged between 25 to 34 years old. From the recorded results, there was one outlier recorded so the data was taken out from the information processing.
Figure 1: Respondent’s Age
4.1.2.2. Gender
It is found that the proportion of female respondents dominates the survey gender composition by a total of 76.4% (155 respondents). Meanwhile, the male respondents serve a third of the total respondents by 22.7% (46 respondents), then followed by 1% of the respondents who prefer to not mention their gender.
Figure 2: Respondent’s Gender
4.1.2.3. Occupation
The online survey is participated by people from different occupations. The occupation of the respondents is highly dominated by employees with over 40.4% (82 respondents). It is then followed by college students with 23.2% (47 respondents), currently unemployed with 9.9%
(20 respondents), and business owners with 8.4% (17 respondents).
Figure 3: Respondent’s Occupation
4.1.3. Descriptive Analysis 4.1.3.1. Variable Indicators
As the main objective of this study is to measure the effectiveness of social media usage towards the purchase intention of Indonesia’s local beauty products, the social media attributes will serve as the independent variables, while the purchase intention will be the dependent variable. By analyzing the data, it is expected that by the end of the study, the result will show which one of the social media attributes performs the most effective and the least powerful marketing strategy to drive customers’ desire to purchase the product
Figure 4: Descriptive Analysis According to the Variable Indicator
No. Dimension Variables Indicator MEAN STD DEV MODE
1. Social Media Marketing
Electronic word of mouth
WOM1 4.2611 1.2491 5
WOM2 4.1921 1.3304 5
WOM3 4.9409 1.1801 6
WOM3 5.1034 1.0690 6
2. Influencer attributes IA2 4.5911 1.1104 5
IA3 4.2956 1.2825 5
IA4 4.5616 1.2664 5
IA5 4.5911 1.2994 5
3. Interactivity IN1 4.3645 1.1962 5
IN2 4.8276 1.0506 5
IN3 4.7340 0.9891 5
4. Knowledge sharing KS1 4.7192 1.0412 5
KS2 4.4236 1.2259 5
KS3 4.4483 1.2027 5
5. Trust TR1 4.1970 1.0993 4
TR2 5.0000 1.0341 5
TR3 4.4483 1.3016 5
6. Personalized experience PE1 4.6552 1.0480 5
PE2 4.2956 1.2433 5
PE3 4.5369 1.0956 5
Figure 4 represents the average answer in each of the social media attributes and the amount of variation it contributes to customer intention in purchasing Indonesia’s local beauty products according to the different statements mentioned in the online survey. As it can be seen from the above table, the electronic word of mouth indicator “I perceive the review made by other customers on social media to be influential in my purchase intention.” has the highest mean score of 5.1034. It shows that customers play an important role in shaping the brand image and create a stronger product presence in the market. On the contrary, the electronic word of mouth indicator “I want to share information about my experience using beauty or self-care products on social media.” has the lowest mean score of 4.1921. This score can be correlated with the highest mean score indicator, that even though people perceive reviews from other customers to be influential in their purchase intention, it does not directly affect their willingness to share their own experience after purchase.
On the one hand, it can be seen that the social media marketing attributes, interactivity, has the lowest standard deviation of 0.9891 within the “I find social media promotions entertaining so they keep me updated with beauty and personal care product offerings.” indicator. It means that this specific indicator shares the least varied responses, clustered around the mean of 4.737.
This is further explained by the considerably high mode of 5 which shows that most of the respondents agree with the statement. These results explain that overall, Indonesia's local beauty product purchasers find that entertainment resulting from engaging social media content has a significant influence on them to stay updated regarding product launching and offering.
4.1.3.2. Social Media Attributes
As the previous section discusses each of the variable’s indicators, here is a broader view of the performance of each of the social media attributes with all the indicators combined. For the electronic word of mouth, the average score was 18.4975, which was then followed by the influencer attributes with 18.0394. Whereas the rest of the attributes (interactivity, knowledge sharing, trust, and personalized experience) share similar mean scores of 13.9261, 13.5911, 13.6453, and 13.4877 respectively. Hence, descriptively it can be concluded that both electronic word of mouth and the influencer attributes share the greatest influence on the purchase intention of Indonesia’s local beauty product customers.
On the other hand, when all indicators are combined, the personalized experience turns out to be the attribute that shares the least varied responses according to the standard deviation score (0.18149). Whereas the variable with the most varied answers based on the standard deviation score lies on influencer attributes (0.29181). These results indicate that overall, Indonesia's local beauty product customers have a similar opinion regarding the impact of experience personalization, whereas the influencer attributes impact remains to be the most debatable.
Figure 5: Descriptive Analysis According to the Social Media Attributes
N Mean Std.
Deviation Std.
Error
95% Confidence interval for mean
Min Max Lower
Bound
Upper Bound
eWoM 203 18.4975 3.30073 .23167 18.0407 18.9543 9.00 24.00 Influencer Attributes 203 18.0394 4.15759 .29181 17.4640 18.6148 4.00 24.00 Interactivity 203 13.9261 2.66058 .18674 13.5579 14.2943 5.00 18.00 Knowledge Sharing 203 13.5911 2.91383 .20451 13.1879 13.9944 3.00 18.00
Trust 203 13.6453 2.62175 .18401 13.2825 14.0081 3.00 18.00 Personalized Experience 203 13.4877 2.58587 .18149 13.1298 13.8455 3.00 18.00 Total 1218 15.1979 3.77699 .10822 14.9855 15.4102 3.00 24.00
4.1.4. Statistical Analysis
In this research, to measure the effectiveness of social media attributes towards the purchase intention of Indonesia’s local beauty products, One Way Anova will be used to determine whether there are any statistically significant differences between the mean of each attribute.
This is believed to be the most effective way to test which practice can be elevated and utilized more effectively in growing the business revenue through virtually boosting the customer purchase intention.
4.1.4.1. ANOVA Test
One-way ANOVA test is used as a way to measure all of the social media attributes and test whether there are statistical differences among them within the process of gaining customer awareness to boost purchase intention of Indonesia’s local beauty line products specifically.
According to the given table, it is found that the statistical significance value is equal to 0.00001
< 0.005. When the significance value is lower than the confidence level, there is enough evidence to conclude that there is a difference in the perceived usefulness of the social media attributes
Figure 6: ANOVA Table
Sum of Squares df Mean Square F Sig.
Between Groups 5784.743 5 1156.949 121.126 .00001
Within Groups 11576.571 1212 9.552
Total 17361.314 1217
4.1.4.2. Post Hoc Tests
Tukey HSD test is a multiple comparison test to determine whether the average effectiveness for each of the social media attributes is significant in the number variance analysis. This method is used in this study to find which attributes perform the same or are different in terms of the level of effectiveness towards the purchase intention.
Figure 7: Multiple Comparison Table Dependent Variable: Purchase Intention
(I) Social Media (J) Social Media
Mean Difference (I-J)
Std.
Error Sig.
95% Confidence Interval Lower Bound
Upper Bound
Tukey
HSD eWoM
Influencer
Attributes .45813 .30676 .669 -.4175 1.3337 Interactivity 4.57143* .30676 .000 3.6958 5.4470
Knowledge
Sharing 4.90640* .30676 .000 4.0308 5.7820
Trust 4.85222* .30676 .000 3.9766 5.7278
Personalized
Experience 5.00985* .30676 .000 4.1343 5.8854
Influencer Attributes
eWoM -.45813 .30676 .669 -1.3337 .4175
Interactivity 4.11330* .30676 .000 3.2377 4.9889 Knowledge
Sharing 4.44828* .30676 .000 3.5727 5.3239
Trust 4.39409* .30676 .000 3.5185 5.2697
Personalized
Experience 4.55172* .30676 .000 3.6761 5.4273
Interactivity
eWoM -4.57143* .30676 .000 -5.4470 -3.6958 Influencer
Attributes -4.11330* .30676 .000 -4.9889 -3.2377 Knowledge
Sharing .33498 .30676 .885 -.5406 1.2106
Trust .28079 .30676 .943 -.5948 1.1564
Personalized
Experience .43842 .30676 .709 -.4372 1.3140
Knowledge Sharing
eWoM -4.90640* .30676 .000 -5.7820 -4.0308 Influencer
Attributes -4.44828* .30676 .000 -5.3239 -3.5727 Interactivity -.33498 .30676 .885 -1.2106 .5406
Trust -.05419 .30676 1.000 -.9298 .8214
Personalized
Experience .10345 .30676 .999 -.7721 .9790
Trust
eWoM -4.85222* .30676 .000 -5.7278 -3.9766 Influencer
Attributes -4.39409* .30676 .000 -5.2697 -3.5185 Interactivity -.28079 .30676 .943 -1.1564 .5948
Knowledge
Sharing .05419 .30676 1.000 -.8214 .9298
Personalized
Experience .15764 .30676 .996 -.7180 1.0332
Personalized Experience
eWoM -5.00985* .30676 .000 -5.8854 -4.1343 Influencer
Attributes -4.55172* .30676 .000 -5.4273 -3.6761 Interactivity -.43842 .30676 .709 -1.3140 .4372
Knowledge
Sharing -.10345 .30676 .999 -.9790 .7721
Trust -.15764 .30676 .996 -1.0332 .7180
4.1.4.2.1. Electronic Word of Mouth Comparison
According to the multiple comparison table, the difference between the mean of social media attributes, electronic word of mouth, with the mean of influencer attributes, interactivity, knowledge sharing, trust, and personalized experience is 0.45813, 4.57143, 4.9064, 4.85222, and 5.00985 respectively. With the 95% significance level, all of the differences values for each of the attributes are still within the confidence interval. Then, based on the multiple comparison output, the significant value for the electronic word of mouth and influencer attributes is 0.669 > 0.05. This indicates that descriptively, the effectiveness difference for those two attributes is not significant. Whereas it can be said that the effectiveness of the other attributes (interactivity, knowledge sharing, trust, and personalized experience) as it is compared to the electronic word of mouth is significant (<0.05).
4.1.4.2.2. Influencer Attributes Comparison
According to the multiple comparison table, the difference between the mean of social media attributes, and influencer attributes, with the mean of electronic word of mouth, interactivity, knowledge sharing, trust, and personalized experience is -0.45813, 4.11330, 4.44828, 4.39409, and 4.55172 respectively. With the 95% significance level, all of the differences values for each of the attributes are still within the confidence interval. Then, based on the multiple comparison output, the significant value for the influencer attributes and the electronic word of mouth is 0.669 > 0.05. This indicates that descriptively, the effectiveness difference for those two attributes is not significant. Whereas it can be said that the effectiveness of the other attributes (interactivity, knowledge sharing, trust, and personalized experience) as it is compared to the electronic word of mouth is significant (<0.05).
4.1.4.2.3. Interactivity Comparison
According to the multiple comparison table, the difference between the mean of social media attributes, and interactivity, with the mean of electronic word of mouth, influencer attributes, knowledge sharing, trust, and personalized experience is -4.57143, -4.1133, 0.33498, 0.28079, and 0.43843 respectively. With the 95% significance level, all of the differences values for each of the attributes are still within the confidence interval. Then, based on the multiple comparison output, the significant value for the knowledge sharing is 0.885 > 0.5, trust is 0.943
> 0.05, and personalized experience is 0.709 > 0.5. These figures represent the insignificant difference between the three attributes with the interactivity indicator. On the one hand, electronic word of mouth and influencer attributes share a low significance level which makes both of them significant as compared to the interactivity attribute.
4.1.4.2.4. Knowledge Sharing Comparison
According to the multiple comparison table, the difference between the mean of social media attributes, knowledge sharing, with the mean of electronic word of mouth, influencer attributes, interactivity, trust, and personalized experience is -4.9064, -4.44828, -0.33498, -0.05419, and 0.10345 respectively. With the 95% significance level, all of the differences values for each of the attributes are still within the confidence interval. Then, based on the multiple comparison output, the significance value for the interactivity is 0.30676 > 0.05, trust is 1 > 0.05, and personalized experience is 0.30676 > 0.05. These figures represent the insignificant difference between the three attributes with the knowledge sharing indicator. It means that the social media attributes of knowledge sharing, interactivity, trust, and personalized experience share a similar level of impact when it comes to boosting purchase intention among Indonesia’s local beauty line customers. On the other hand, it is seen that the electronic of mouth attribute and influencer attribute share a significant difference with knowledge sharing.
4.1.4.2.5. Trust Comparison
According to the multiple comparison table, the difference between the mean of social media attributes, trust, with the mean of electronic word of mouth, influencer attributes, interactivity, knowledge sharing, and personalized experience is -4.85222, -4.39409, -0.28079, 0.05419, 0.15764 respectively. With the 95% significance level, all of the differences values for each of the attributes are still within the confidence interval. Similar to the previous section, it is seen that the social media attribute of trust is not significantly different from the attribute of interactivity, knowledge sharing, and personalized experience as the significant level for these attributes is less than 0.05 (0.885, 0.943, 0.709 respectively), while influencer attributes and the electronic word of mouth remains significantly different in purchase intention influence.
4.1.4.2.6. Personalized Experience Comparison
According to the multiple comparison table, the difference between the mean of social media attributes, personalized experience, with the mean of electronic word of mouth, influencer attributes, interactivity, trust, knowledge sharing, and is -4.9064, -4.44828, -0.33498, -0.05419, 0.10345 respectively. With the 95% significance level, all of the differences values for each of the attributes are still within the confidence interval. Then, as it was already mentioned on the previous section, the experience of personalization that social media offers is believed by the customers to have a similar effect in driving purchase intention towards Indonesia’s local beauty products. However, the personalized experience attribute of social media shares a significantly different effect when compared to the mean of electronic mouth and influencer attribute of social media.
Figure 8: Significance of Social Media Attributes Comparison Summary
(I) Social Media (J) Social Media Sig. Confidence Significant Difference
eWoM
Influencer Attributes .669 0.05 No
Interactivity .000 0.05 Yes
Knowledge Sharing .000 0.05 Yes
Trust .000 0.05 Yes
Personalized Experience .000 0.05 Yes
Influencer Attributes
eWoM .669 0.05 No
Interactivity .000 0.05 Yes
Knowledge Sharing .000 0.05 Yes
Trust .000 0.05 Yes
Personalized Experience .000 0.05 Yes
Interactivity
eWoM .000 0.05 Yes
Influencer Attributes .000 0.05 Yes
Knowledge Sharing .885 0.05 Yes
Trust .943 0.05 No
Personalized Experience .709 0.05 No
Knowledge Sharing
eWoM .000 0.05 Yes
Influencer Attributes .000 0.05 Yes
Interactivity .885 0.05 No
Trust 1.000 0.05 No
Personalized Experience .999 0.05 No
Trust
eWoM .000 0.05 Yes
Influencer Attributes .000 0.05 Yes
Interactivity .943 0.05 No
Knowledge Sharing 1.000 0.05 No
Personalized Experience .996 0.05 No
Personalized Experience
eWoM .000 0.05 Yes
Influencer Attributes .000 0.05 Yes
Interactivity .709 0.05 No
Knowledge Sharing .999 0.05 No
Trust .996 0.05 No
4.1.4.3. Mean Similarity
In the first subset, there is the mean data of personalized experience, knowledge sharing, trust, and interactivity. This means that these four attributes do not have a very significant mean difference. In other words, it can be assumed that the mean for these four attributes is the same.
On the one and, in the second subset, there is the mean data of influencer attributes and electronic word of mouth. This indicates that these two attributes do not have a very significant mean difference. Then, it can be assumed that the mean for these two attributes is the same.
With that being said, the mean differences result in the rejection of the null hypothesis.
Figure 9: Homogeneous Subsets
Social Media Marketing Attributes N Subsets
1 2
Tukey HSD
Personalized Experience 203 13.4877
Knowledge Sharing 203 13.5911
Trust 203 13.6453
Interactivity 203 13.9261
Influencer Attributes 203 18.0394
eWoM 203 18.4975
Sig. .709 .669
5. Conclusion and Recommendation
This chapter will summarize the research findings, which will help to better understand how social media marketing attributes impact Indonesia's beauty business. It will further highlight the analysis of the technique in comparison to the purchase intention of Indonesia’s local beauty brands.
5.1. Conclusion
This research objective is to identify which social media marketing attributes have the most significant impact on the purchase intention of Indonesia’s local beauty line and eventually recommend which social media marketing attributes to use for Indonesia’s local beauty line to communicate more effectively with its target audience. Furthermore, the study intends to find
out the difference between the perceived impact of social media marketing attributes in boosting the purchase intention of Indonesia’s local beauty line. For this research, there are six attributes being utilized to analyze further social media marketing usage; electronic word of mouth, influencer attributes, interactivity, trust, knowledge sharing, and personalized experience.
Based on the final result of data analysis, the level of the perceived effectiveness for each of the social media attributes towards the purchase intention of Indonesia’s local beauty products are classified into two categories. The first category comprises electronic word of mouth and influencer attributes. These two elements are believed to boost purchase intention more effectively. According to the result, the impact that these two attributes have are far greater than the rest of the attributes. On the other hand, with a statistically lower mean, the social media marketing attributes of interactivity, trust, knowledge sharing, and personalized experience remain to be the ones that share a lower influence in boosting customers’
willingness to buy local Indonesian beauty products. Therefore it is can be concluded that there is a difference between the mean of each social media marketing attribute with the electronic word of mouth and the influencer attributes remain to be the most influential in driving sales through purchase intention boosting.
5.2. Managerial Recommendation and Implication
Based on the outcomes of this study, some advice for future initiatives for an Indonesian beauty company that wants to use social media marketing more successfully to increase sales is included below.
5.2.1. Social Media Marketing Attributes Utilization
To allocate the budget more effectively, each of the social media marketing attributes should be prioritized as the impact it gives on customers’ willingness to purchase is varied. Therefore, it is important to invest more in the customer testimonials section and partnerships as electronic word of mouth and influencer attributes are perceived to have a higher impact. Then, the brand can focus on developing other social media attributes as mentioned above to optimize the business performance digitally.
Exhibit 5.1 Social media marketing attributes detailed recommendations
No. Detailed Recommendations Implication
1. Influencer collaboration
Selecting influencers to make a partnership with needs to be very selective as they will represent the company.
Therefore, having strong branding can help find the potential influencer that suits the brand. This strategy is believed to give a virality effect that can help create awareness in a larger market.
Social media live streaming
In order to maximize the partnership, this activity can be selected to make the social media audience more aware of the brand value while being educated about the product features.
Limited edition product launching To create the FOMO (Fear of missing out) effect, creating a limited edition product through influencer collaboration can attract the prospects to make a purchase.
2. Community development
To give a real testimonial, a brand can utilize its current loyal customers to spread their positive experiences of using the product. The larger the community, the higher the chances for our brand to be trusted in terms of product quality.
Membership
This can be one of the ways to let people who have already been loyal members gain extra benefits. By doing this, a brand can give added value to its customers and create interest on the upcoming product launch.
5.2.2. Future Research
Overall, this study only highlights the social media marketing attribute's impact on the purchase intention through all aspects of the beauty industry. It is suggested to narrow down the scope so that it will be more specific and targeted. In addition for future studies, each variable must be validated so that the indication can be comprehended by the respondents better. There might be some other factors influencing customers in making purchase decisions. Also, it is important to deepen the relationship between social media marketing and the creation of value co-creation behaviour as a way to understand the customer journey in more detail.
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Appendix
Questionnaire Operational Variable
No. Variables Label Indicator Source
1. Electronic word of mouth
WOM1 I consider shared experiences through social media as unbiased and credible sources of information when it comes to beauty and self-care products
Masuda et al., 2022; Lou and Kim, 2019 WOM2 I would like to pass out information about my
experience of using a certain product or services on social media
WOM3 I perceive the review made by other customers on social media to be influential in my purchase intention WOM4 I know many beauty brands from social media
advertisement 2. Influencer
attributes
IA1 I feel that beauty influencers are competent enough when asked to do product reviews on social media IA2 I feel entertained by sponsored social media content
which makes me have a greater tendency to purchase a product or service
IA3 I feel that the physical attractiveness of an influencer on social media promotion heavily influences my decision to purchase a product or services
Duran and Kelly, 1988
IA4 I feel that social attractiveness of an influencer on social media promotion increases his/her reliability which heavily influenced my decision to make a purchase
Masuda et al., 2022
3. Interactivity IN1 Social media campaign often makes me feel engaged to a product or service promotion
Onofrei et al., 2022) IN2 Social media allows me to connect with other customers
with similar needs
IN3 I found social media promotion entertaining so that it makes me stay updated with the latest product or service offer
4. Knowledge sharing
KS1 The product or services information shared on social media are clear and relevant for purchase consideration
Navitha Sulthana and Vasantha,
2021 KS2 The information provided on social media is the main
reason why I shop online
