Volume 12 Number 2 Article 8
8-31-2023
The Impact of Digital Communication on Online Purchasing The Impact of Digital Communication on Online Purchasing Behavior among Indonesian Millennials: A Case Study of Behavior among Indonesian Millennials: A Case Study of Tokopedia
Tokopedia
Erwin Panigoro Universitas Indonesia Yuli Harwani
Faculty of Business Economics, Mercu Buana University, Jakarta, Indonesia Dudi Permana
Faculty of Business Economics, Mercu Buana University, Jakarta, Indonesia Erna Sofriana Imaningsih
Faculty of Business Economics, Mercu Buana University, Jakarta, Indonesia Erlina P. Mahadewi
Universitas Esa Unggul, Jakarta, Indonesia
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Part of the Gender, Race, Sexuality, and Ethnicity in Communication Commons, International and Intercultural Communication Commons, and the Social Influence and Political Communication Commons Recommended Citation
Recommended Citation
Panigoro, Erwin; Harwani, Yuli; Permana, Dudi; Imaningsih, Erna Sofriana; and Mahadewi, Erlina P. (2023)
"The Impact of Digital Communication on Online Purchasing Behavior among Indonesian Millennials: A Case Study of Tokopedia," JURNAL KOMUNIKASI INDONESIA: Vol. 12: No. 2, Article 8.
DOI: 10.7454/jkmi.v12i2.1210
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INDONESIA
August 2023 ISSN 2615-2894
The Impact of Digital Communication on Online Purchasing Behavior among
Indonesian Millennials:
A Case Study of Tokopedia
Erwin Panigoro1, Yuli Harwani2, Dudi Permana3, Erna Sofriana Imaningsih4, Erlina P Mahadewi5
1 Universitas Indonesia, Depok, West Java, Indonesia.
2, 3, 4 Faculty of Business Economics, Mercu Buana University, Jakarta, Indonesia
5 Universitas Esa Unggul, Jakarta, Indonesia
Corresponding Author: Erwin Panigoro. Email: [email protected]
Article Information Received
20/06/2023
Received in revised form 28/07/2023
Accepted 28/08/2023 Available online 31/08/2023 DOI
https://doi.org/10.7454/jkmi.v1 2i2.1197
Keywords
Communication, E-commerce, Online Purchase Behavior, Perceived Digital
Communication, Millennial, Tokopedia
Abstract
Introduction
The development of information technology has brought marketing transformation to digitalization. Digital technology has the most significant impact on communication processes in the business world; developments in electronic devices and equipment, as well as evolving marketing practices, have facilitated this impact (Chen and Lin, 2019). Digital technologies have become the critical foundation for developing new products, values, and properties, as well as the foundation for gaining a competitive advantage in most markets. These technologies have also significantly impacted all business areas, including product development, purchase and sales, branding, customer relationship management (CRM), and communication establishment (Limna, Pongsakorn, 2022). Digital marketing is a component of marketing that promotes products and services through the use of internet and online-based digital This article discusses the impact of digital communication on the online purchasing behavior of millennials in Indonesia, with a particular focus on transaction flow through the online commerce platform Tokopedia. The study aims to show that Tokopedia's digital communications determine users' attitudes and purchasing behavior. This paper adopts the quantitative research method of causal design, and 210 respondents selected by simple random sampling are used as the sample size. The variables examined in this study include perceptions related to digital communication and online purchasing behavior, which are manipulated through different dimensions and indicators. The results show that perceived digital communication significantly and positively impacts online purchasing behavior. Additionally, the study suggested that Tokopedia should develop a digital communication strategy to improve customer experience. Further research could expand the sample size and examine other variables for a more complete understanding of consumer behavior.
technology, including desktops, laptops, smartphones, and other digital media and platforms, Denga et al. (2022).
From 2015 to 2020, sales of global e-commerce online products continued to show a growth trend, which will continue until 2023 and is expected to reach 6.542 billion US dollars (Statista, 2020). The complete data is shown in the Figure 1 below.
Figure 1. Retail E-Commerce Sales Worldwide (2014 – 2023) Source: Statista (2020)
The internet economy in Southeast Asia has also experienced moderate growth, with the internet user base continuing to grow in 2018, supported by the growing popularity of affordable smartphones and the rollout of faster and more reliable mobile telecommunication services. There were over 350 million internet users in Indonesia, Malaysia, the Philippines, Singapore, Thailand, and Vietnam in June 2018, an increase of 90 million from 2015 (Temasek, 2019). The massive group of Indonesian Internet users is often characterized by consumption which brings excellent opportunities for developing Indonesia's digital economy. It is worth mentioning that Indonesia's economic growth rate in 2019 was higher than other ASEAN countries. As the region's most significant and fastest-growing Internet economy, Indonesia is expected to break the US$130 billion mark in 2025 (Google et al., 2019). In particular, the e-commerce sector is overgrowing, driven by intense competition between Indonesian people and Indonesian or regional players. The chart below (Figure 2) shows that the Internet economy continues to grow in Southeast Asia, particularly in Indonesia (Google et al., 2019).
Figure 2. SEA Internet Economy (GMV, $B) Source: Google, Temasek, & Bain (2019)
Figure 3. Indonesia Internet Economy (GMV, $B) Source: Google, Temasek, & Bain (2019)
In Indonesia, online purchases are dominated by millennial consumers, a unique generation who tend to spend their income shopping online daily (Salim et al., 2019, p. 41). It is recorded that consumers aged 26-35 years, or the millennial generation are still the largest contributors to the proportion of e-commerce transactions throughout 2022, reaching 46.2%. However, the trend has tended to decrease in the last two years. Indonesian millennials are constantly developing themselves to anticipate changes brought about by technological advances, and this is an opportunity for online sellers to increase interest in buying online among Indonesian millennials. Among Indonesia's various growing Internet economies, the e-commerce sector has experienced significant growth rates from 2015 to 2019. It is expected to reach USD 82 billion in 2025 (Figure 3).
Indonesia's internet economy is also overgrowing, with a growth of 152 million internet users in Indonesia in 2019 (Google et al., 2019). The e-commerce sector dominates Internet economic growth, and the increasing penetration of smartphones and the Internet and increasing middle-class consumers, coupled with a young, technology-savvy population, is one of the main determinants of e-commerce growth (Country & Soesilowati, Year 2021). The e-commerce industry in Indonesia is increasingly driven by the rapid development of non-cash payment infrastructures such as Ovo, GoPay, DANA and ShopeePay (Negara & Soesilowati, 2021).
Internet users in Indonesia have grown significantly, according to Association of Indonesian Internet Service Providers (APJII, 2023), internet users in Indonesia are equivalent to 78.19% of Indonesia's total population, but not comparable to the average amount of shopping or online (e-commerce) purchases, with a weekly online purchase, still far below neighboring countries such as Singapore, Thailand, Malaysia, Singapore and Philippine (Report Data, 2022). The complete data is in Figure 4 below.
Purchasing behavior in Indonesia is in line with the consumption tendencies of the Indonesian people and a large number of smartphone users. Consumer behavior is the process by which consumers seek, buy, use, evaluate, and act after consuming products, services, and ideas expected to satisfy consumer needs and wants (Muslikh et al., 2017). Competition between e-commerce companies in Indonesia is very competitive in attracting customers to visit websites (e-commerce) and make purchases. Various innovations and strategies are implemented to attract customers to shop online. Following (Table 1) is the development of the number of monthly visitors for the five largest e-commerce sites in Indonesia (Iprice Insights, 2020).
Figure 4. Weekly Online Purchase Source: Datareportal (2022)
Table 1. Number of Monthly Visitors of the Five Largest E-Commerce in Indonesia (In million rupiah)
Online Store December 2018 December 2019 September 2020
Tokopedia 168 68 85
Bukalapak 116 39 31
Shopee 68 73 97
Lazada 58 28 22
Blibli 43 26 18
Table 2. Pre-survey Result
Variable Question Answer
Yes No
Perceived Digital Communication
E-commerce displays advertisements along with featured product links on all digital platforms
46,7% 53,3%
E-commerce displays ads in a clear and
understandable way for readers on all digital platforms.
43,3% 56,7%
The data above shows that Tokopedia, Bukalapak, and Shopee compete to attract visitors. As can be seen, Tokopedia became the ruler of the online marketplace in December 2018 before being replaced by Shopee in 2019 and remains the most significant marketplace to date. Tokopedia is one of the markets abandoned by customers in 2019. Although it increased by 25% in 2020 (Iprice Insights, 2020), the number of visitors fell by 59.5% (Iprice Insights, 2020), which of course, has to the company to evaluate its strategy and the factors that caused Tokopedia's online buying behavior to decline.
The author tries to study digital communication factors that can influence online buying behavior, which has been proven by previous literature studies on digital communication (Samson et al., 2014). The following findings are based on researchers'
observations of 30 respondents who shop online.
Based on the results of the pre-survey above (Table 2), it is indicated that it is necessary to carry out research related to perceived digital communication. Efforts to increase public participation in online shopping require a product marketing strategy by providing various information (advertisements) to the public. One of the advances in information technology is the creation of e-commerce, which provides services to buyers online through a computer network (Batu et al., 2018). Due to the advantages of digital communication over analogue communication, the most excellent form of communication is robust because it is unaffected by channel interference and distortion (Ahmed et al., 2016).
Digital marketing involves the promotion of goods and services via an e-commerce platform that responds to an internet connection in real-time (Dastane, 2020). Digital communication is essential in today's marketing. However, some clients still see digital communication as a challenge and barrier because they do not see the need to receive critical information in digital form or experience difficulty or disinterest in using digital tools, which can generate resentment and suspicion—more about the information received (Krotel, 2019), thus it is important to carry out studies to fill the knowledge gap above, especially to find the relationship between digital communication and online buying behavior. Digital marketing communications through website media, search engine marketing, web banners, social media, affiliate marketing, and email marketing positively and significantly impact online purchasing decisions (Batu et al., 2018).
From various previous research studies, research on perceived digital communication directly on online purchase behavior is still rare. Online buying behavior for online stores. This research was developed on the effect of perceived digital communication on online purchase behavior online purchases through Tokopedia e-commerce for Millennials in Indonesia, for which the research title was used: The Impact of Digital Communication on Online Purchasing Behavior among Indonesian Millennials: A Case Study of Tokopedia.
Online Purchase Behavior
The development of the internet has brought changes in consumer buying behavior, from traditional to internet based. Consumer behavior is defined as the behavior consumers display when they attempt to purchase, use, evaluate, and dispose of products and services that they expect to satisfy their needs (Schiffman & Kanuk, 2013). Conceptually, consumer behavior focuses on how individuals buy goods related to consumption or needs. Consumer purchasing decisions are buying favourite brands from various existing alternatives, but there may be two factors between purchase intention and purchase decision (Kotler & Armstrong, 2018). When making customer decisions, models (depicted in Figure 5 below) can be developed based on the following considerations.
From pre-purchase to post-purchase, the consumer buying decision-making process is divided into five stages (Kotler & Armstrong, 2018), namely:
1. Problem recognition. Problems arise from within the consumer in the form of needs driven by the buyer's internal or external stimulation. Another way to put it is that the buyer's awareness of his requirements—which can be brought on by internal and external factors—becomes the catalyst for his efforts to satisfy those demands.
Companies must gain a better understanding of the issue of consumer needs to do this. Indicators like online shopping requests and goals can be used to quantify this element.
2. Search for information. After knowing that there is a problem in the form of a need, consumers will look for information about objects that can fulfil their desires.
Through this information, consumers will learn about competing brands and
understand the qualities and characteristics of the brands. Information search depends on the strength of the desired need, and the information obtained is then evaluated. The amount of information that consumers have about these products will direct consumers to make a final decision. This aspect can be measured by indicators such as the degree of attention to online shopping information and the degree of interest in online shopping information.
3. Assessment of alternatives. Based on the information obtained, consumers will be faced with choices that can be considered for purchase. Consumers will evaluate products that suit their needs and expectations through this selection. The process of consumer evaluation in decision-making is usually cognitive; that is, consumers are assumed to make rational and conscious evaluations of products. This aspect can be measured by indicators such as online shopping scores and online product reviews.
4. The purchase decision. Evaluation phase allows consumers to form preferences among alternative product brands. At this stage, consumers will also form considerations to buy the preferred brand, and consumers can also form intentions to buy their favourite products. This aspect can be measured by indicators such as the level of consideration for online shopping and the stability of online shopping.
5. Post-purchase behavior. After buying a product, consumers will experience a certain level of satisfaction or dissatisfaction, influencing the following buying process. It prompts manufacturers to pay close attention to consumer behavior after purchase. If the consumer is satisfied with the product purchased, it is often an excellent tool for marketing the product to others and making repeat purchases.
This aspect can be measured through indicators such as satisfaction with online purchases and recommendations to others.
Figure 5. Models of Consumer Behavior Source: Mothersbaugh & Hawkins (2016) Perceived Micro-targeting
The development of information technology has brought communication transformation from the analogue era to the digital era. This changing trend forces manufacturers to use internet-based digital technology as a communication tool and find creative new ways to appeal to a broader market (Samson et al., 2014). Due to the advantages of digital communication over analogue communication, the most excellent form of communication has become digital communication. Digital
communication is robust because it is immune to channel interference and distortion (Ahmed et al., 2016). Therefore, digital communication techniques are more automatic and use a computer operating system with digital output results, so the object has no tangible or physical form. Considering that the output of digital communication technology can only be presented in digital or virtual form, the involvement of the human senses is minimal. Humans cannot touch or feel and hold the output of digital communication technology in physical or tangible form. Although it does not produce a physical form, digital communication technology is also included in the communication media because of its ability to transfer information from communicator to communicator in digital form.
The subject of digital communication is concerned with the transmission of information in digital form from a source that generates it to one or more destinations;
in this case, a digital communication system can be seen as a medium for various systems and services, for example, digital television, mobile phones or Internet access (Ahmed et al., 2016).
The measure of digital communication perception is adapted from the Promoter's Concept of Digital Marketing Communications (Widyana & Batangriyan, 2020), namely:
1. Website Perception. The website is a link that connects the entire digital world and is perhaps the essential part of the entire digital marketing strategy, where online activities are directed directly to potential customers. Optimum use of the website is an advantage for the company. The following indicators measure this dimension, Web traffic and time spent on the site, and Content Acceptance Rate.
2. Perceived Search Engine Optimization (SEO). One of the essential parts of a website is SEO, or the process of arranging website content so that it is easily found by internet users who are looking for something related to the content on the website and present the content so that search engines can find it easily. search engine. The following indicators measure these dimensions; Speed of Information Acquisition, Ease of access to information.
3. Display on Paid Click Search Ads (PPC Ads). PPC ads (pay per click) allow marketers to purchase pages of internet search results based on selected keywords and phrases. The convenience of being only one click away from an advertisement is something customers expect as it allows them to find products more quickly. The following indicators measure this dimension; Easy ordering via the Internet and Secure ordering via the Internet.
4. Views on affiliate marketing and strategic partnerships. Events partnering with other organizations or companies and websites for mutual benefit through the joint promotion of products or services. The following indicators measure this dimension; Persuasive communication for e-commerce and Marketing through other media platforms. Therefore, perceived digital communication is how customers feel about the company's marketing communications through digital platforms. Perceived digital communication can be measured in four dimensions:
perceived site usage, search engine optimization, paid search click advertising, and affiliate marketing and strategic partnerships.
The Effect of Perceived Digital Communication on Online Purchase Behavior
The digital era has and will continue to change social trends, directly influencing consumer behavior and needs (Meesilapavikka, 2016). Digital promotions offer solutions to design attractive promotional strategies that help attract and penetrate target markets (Borah et al., 2020). Although online digital communication is a powerful tool for conveying information to customers, it is not the most widespread and influential medium (Samson et al., 2014). Digital marketing is a crucial factor that significantly impacts purchase intentions (Dastane, 2020).
Furthermore, digital marketing communications significantly impact the purchasing decision process (Rao & Ratnamadhuri, 2018). Thus, the hypothesis can be formulated; Perceived digital communication has a positive and significant effect on online purchase behavior.
Research Methods
This research employs quantitative methods to test hypotheses using statistical analysis of data collected from various samples (Sekaran & Bougie, 2016; Cooper &
Schindler, 2014). It analyzes perceived digital marketing communication, focusing on website usage and affiliate marketing (Widyana and Batangriyan, 2020; Ahmed et al., 2016). The study's dependent variables are online shopping behaviors, investigated through stages like problem awareness and choice evaluation (Mothersbaugh &
Hawkins, 2016). The population targeted is Indonesian millennials who shop on Tokopedia.com, chosen due to a significant decrease in visitor numbers amid intense e-commerce competition. The sample represents key characteristics of this population.
The sample size used in this study was 210 respondents. It is determined by the Formula (1) (Hair et al., 2014);
n = 5-10 × Indicator (1)
n = 5 × 42 (indicator) n = 210 respondents
Determination of the sample is done by a simple random sampling technique based on the characteristics of members of a homogeneous population. Simple Random Sampling is taking sample members from a population that is done randomly, regardless of the strata in that population (Sekaran & Bougie, 2016). Researchers collected data by distributing questionnaires to research subjects directly, with questionnaires developed from the dimensions and indicators of each research variable and measuring the questionnaire using a Likert scale with a score of 1 (Strongly Disagree) to 5 (Strongly Agree).
Data analysis was performed using a structural equation model, resulting in a more complex structural model due to the use of intervening variables. Structural equation modelling analysis using the partial least squares (PLS) method. The analysis model is shown in the Figure 6 below:
Figure 6. Analysis Model Results
Perceived Digital Communication
Digital communication perception variables cover four aspects: website user perceptions, SEO perceptions, pay-per-click perceptions, affiliate market perceptions, and strategic partnerships. Overall Perceived Digital Communication by Tokopedia is considered very good, with an average score of 4.27 which indicates that many respondents gave answers that agreed and even strongly agreed with the Perceived Digital Communication variable statement. Even so, the PDC4 code has the lowest average score for the indicator of 4.18, so Tokopedia needs to improve the accessibility of various product information in the storefront.
Perceived Digital Communication
Online Purchase Behavior
Online Purchase Behavior
Online shopping behavior variables include four aspects, namely problem awareness, information search, evaluation and selection of alternative programs, outlet selection, and purchases. Overall, Tokopedia's online buying behavior was considered very good, with an average score of 4.46, indicating that many respondents gave answers that agreed and even strongly agreed with the statement of the variable online buying behavior. This high average score indicates that respondents in this study have high online shopping behavior through the Tokopedia platform.
Analysis Partial Least Square
PLS, analysis tests the hypothesis regarding the assumption of direct and indirect effects. When conducting a PLS analysis, the first step is to evaluate the model to understand how well it is developed and how effective it is. Model evaluation can be done by analysis using the following PLS algorithm approach. Through the PLS Algorithm method, analysis results such as loading factor, r-square, and path coefficient values are obtained, which can be evaluated as follows. External models are used to assess the validity and reliability of indicators in measuring research variables, as described below.
Validity Convergent Test
Convergent validity testing on PLS with reflective indicators is assessed based on the loading factor, declared valid if the loading factor value is > 0.7. The test results are as follows. The test results show that the factor loading score for each indicator exceeds the limit (> 0.7), so it can be said that the indicators for each variable are convergent and effective. These results are strengthened by extracting the value of the average variance (AVE) > 0.5 (Hair et al., 2014), as shown in Table 3 below. The test results show that the AVE value for each variable exceeds the specified limit so that the indicators for each variable are declared valid.
Table 3. Convergent Validity Test
Variable AVE Criteria Result
Online Purchase Behavior 0,854 > 0,5 Valid
Perceived Digital Communication 0,778 > 0,5 Valid
Discriminant Validity
Discriminant validity is related to the principle that different construct measures should not have high correlation values. A discriminant validity test can be done using the Fornell Larcker criterion test by comparing the AVE value's square root with the correlation of latent variables. The test results are shown in the Table 4 below.
Table 4. Discriminant Validity Test
Online Purchase Behavior
Perceived Digital Communication Online Purchase Behavior 0,924
Perceived Digital
Communication 0,751 0,882
Reliability Test
The reliability test is used to test the reliability of research indicators' consistency or level of reliability. Tested with Cronbach's alpha and composite reliability, the test is declared reliable if Cronbach's alpha and composite reliability have a value of > 0.70.
The test results are shown in the Table 5 below. The results of the reliability test showed that the value of Cronbach's alpha and composite reliability was greater than 0.70 so they were declared reliable.
Table 5. Reliabilty Test
Cronbach's
Alpha
Composite
reliability Result
Online Purchase Behavior 0,976 0,979 Reliable
Perceived Digital
Communication 0,959 0,966 Reliable
Inner Model Evaluate
Structural modelling is a measurement phase that describes the relationship between structures (variables). The PLS evaluation model of the structural model (internal model) can be evaluated by looking at the following measurements.
R Square Evaluation. The R Square value serves as a measure of the feasibility of the model to scan the affected variables. The test results are shown in the Table 6.
The R Square value as a measure of model feasibility can be described as follows. The R Square value of 0.866 means that the variance of the digital communication perception variable helps explain 86.6% of the variance of the online buying behavior variable.
Table 6. R Square Evaluation
R-square R-square adjusted
Online Purchase Behavior 0,866 0,863
Q. Square Evaluation. The Q Square test is performed with an eye patch procedure.
Q Square value > 0 indicates that the model is predictively relevant. The test results are shown in the Table 7. The analysis results show a Q-squared value > 0 (0,729), so it can be concluded that the model links perceived micro-goals and digital communication variables to online buying behavior by mediating the variables of trust and perceived behavioral control. Subjective norms have an influence—a strong correlation with forecasts regarding the state of field data.
Table 7. Q Square Evaluation
SSO SSE Q Square
Online Purchase Behavior 800,000 216,506 0,729
Perceived Digital Communication
800,000 800,000
Hypothesis Test
Figure 7. Hypothesis Test
Figure 7 shows that testing the hypothesis by bootstrapping produces coefficient values, t-statistics, and p-values. At a significance level of 5%, the t-statistic value >
1.96 and the p-value < 0.05 have a significant effect when making assumptions based on t-statistics (Hair et al., 2014). The results of testing the hypothesis of the influence of variables are detailed in Table 8:
Table 8. Hypothesis Test
b t
statistic p values Perceived Digital Communication → Online Purchase
Behavior
0,175 3,924 0,000
Based on the direct effect test results, it can be explained further by testing the following hypothesis; Perceived digital communication has a positive and significant effect on online purchase behavior. The results of the t-statistical test obtained a calculated t-value of 3.924 with a significant probability of 0.000. It can be seen that the t count > 1.96 and the p-value < 0.05, then H8 is declared accepted, meaning that perceived digital communication has a significant effect on increasing online purchase behavior.
The effect of Perceived Digital Communication on Online Purchase Behavior
The results of the H-test are statistically accepted, it can be seen from the t-statistic value of 3.924 > 1.96 and the p-value of 0.000 <0.05. Thus, the perception of digital communication positively and significantly affects Tokopedia's online buying behavior. The digital era has and will continue to change social trends, directly influencing consumer behavior and needs (Meesilapavikka, 2016). Digital promotions offer solutions to design attractive promotional strategies that help attract and penetrate target markets (Borah et al., 2020). Although online digital communication is a powerful tool for conveying information to customers, it is not the most widespread and influential medium (Samson et al., 2014). Digital marketing is a critical factor that significantly impacts purchase intentions (Dastane, 2020). Furthermore, digital marketing communications significantly impact the purchasing decision process (Rao
& Ratnamadhuri, 2018).
Conclusion
Based on the results of this study, the theoretical implications are described as follows, perceptions of digital communication have a positive and significant effect on online buying behavior on the Tokopedia platform. Also, these findings suggest that perceptions of digital communication play an essential role in influencing online buying behavior, thereby contributing to communication theory. This enriches our understanding of the role of digital communication in online shopping.
In developing a more comprehensive communication theory, it is necessary to consider the role of digital communication perceptions as a factor influencing consumer behavior. These findings suggest that perceived digital communication has a positive and essential impact on online buying behavior, strengthening consumer behavior theory. This shows that the perception of individuals of the digital communications they receive influences their intention and behavior to make online
Perceived Digital Communication
Online Purchase Behavior
t: 3,924 p Value: 0,000
purchases. Perceived digital communication thus becomes a relevant factor in understanding consumer behavior in the online environment. These theoretical implications can influence the development of a more comprehensive and relevant model of consumer behavior. By incorporating perceptions of digital communication and online buying behavior into models of consumer behavior, further research can identify more complex relationships between these variables and other factors that predict online buying behavior. This can help us better understand how perceptions of digital communications influence online purchasing decisions. Perceived digital communication positively and significantly affects online purchase behavior on the Tokopedia platform.
Based on the findings above, Tokopedia management can develop digital communications for application users or customers to increase the effectiveness of Tokopedia's communications based on the analysis of the findings of this study:
1. Optimize web traffic and time spent on the site: The Tokopedia website needs to be maintained to be easy to navigate and attractive to visitors. This can increase surfing time for visitors to create buying opportunities for them.
2. Increase the acceptance rate of content: The content and messages displayed on the site must be relevant, interesting, and easy for visitors to understand. This can also increase visitor interest so that it has the opportunity to increase visitor buying interest.
3. Accelerating information accessibility: Information for visitors must be easily accessible and easy to find on the Tokopedia website. Accelerating and facilitating visitors' access to this information can increase visitor satisfaction, increasing their chances of purchasing.
4. Use effective persuasion communication: Use effective persuasion communication techniques to convince visitors to buy on the site. This can increase the purchase conversion rate.
5. Take advantage of marketing through other media platforms: Using and utilizing other media platforms, such as social media, can expand your reach in marketing products. This can increase brand visibility and increase the chances of attracting more visitors to the site.
The study suggests that optimizing web traffic, increasing content acceptance, accelerating information accessibility, using effective persuasion communication, and utilizing marketing through other media platforms can improve the effectiveness of digital communication strategies and enhance customer experience. In order to improve customer experience and boost revenue, other e-commerce businesses with operations in Indonesia and other emerging regions should give priority to strengthening their digital communication strategy.
Limitation and Recommendation
In conducting this study, some limitations for future research were considered to develop a more refined model. Depending on the limitations of the research, suggestions for further research can be made as follows; Future research is expected to be able to carry out this research even more broadly and in depth, one of which is by increasing the population or research sample, especially in the sample population of adults and older adults in order to obtain broader findings. It is recommended that further research be able to add other data collection methods besides the methods used in this study, namely direct observation, or interviews with management, to obtain more accurate and in-depth data to understand the implementation and application of digital communication strategies.
Implications
Perceived digital communication among millennials in Indonesia has a favorable and significant impact on their online purchasing behavior. This finding shows that e- commerce businesses can use perceived digital communication to affect consumer behavior. As a result, other e-commerce businesses might create digital communication strategies that emphasize convenience, such as making it simple for customers to find their ideal products and have easy access to information about a variety of products in the storefront. The following recommendations can be made for other companies to improve their digital communication strategies to enhance customer experience and drive sales:
1. Develop digital communication strategies that prioritize convenience, such as easy access to information on various products in the storefront and ease for users to find their dream products.
2. Use chatbots, personalized messaging, and social media marketing to engage with customers and enhance their online shopping experience.
3. Pay attention to post-purchase behavior and use customer satisfaction to market products to others and make repeat purchases.
4. Use persuasive communication for e-commerce and marketing through other media platforms, such as affiliate marketing and strategic partnerships.
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