The Effect of Digital Marketing Implementation on Brand Loyalty Was Moderated by Buying Interest: Study on Coffee Shop Business

Nafiah Ariyani1, Mira Septiani2

1,2Faculty of Economics and Business, Sahid University

INTRODUCTION

In conditions of increasingly fierce competition and the increasingly popular use of digital marketing in today’s business, building consumer buying interest and maintaining brand loyalty is both a necessity and an opportunity (Rahman Khan & Aminul Islam, 2017). The development of digital communication technology has not only changed consumer behavior, especially in seeking information (Yasmin et al., 2015), but also has facilitated consumers with various information in the form of reviews or comments of people on the buying experience, all of which work wonders in the minds of consumers and consumers. form buying interest (Alharbi & Alhider, 2018). On a wider spectrum, the development of digital technology has changed the marketing management landscape through the application of digital marketing (Hutter et al., 2013). 

Corresponding Author: Nafiah Ariyani

*Cite this Article: Nafiah Ariyani, Mira Septiani (2022). The Effect of Digital Marketing Implementation on Brand Loyalty Was Moderated by Buying Interest: Study on Coffee Shop Business. International Journal of Social Science and Education Research Studies, 2(6), 217-227

The application of digital media has changed the context of interaction between marketers and consumers as well as with other consumers (Desai, 2019), and created a wide scale between mass communication methods and interpersonal communication (Geçti & Gümüş, 2013).

Digital marketing is the use of digital technology to help manage marketing by increasing knowledge about customers (Deekshith & Kinslin, 2016); and improve relationships, and encourage purchases (Bala & Verma, 2018). On digital marketing, marketers can interact and communicate directly and allow reaching and interacting with customers through extensive purchase tracing (Choedon & Lee, 2020). Digital marketing facilitates marketers to promote and distribute offerings through portals so that real-time exchange of information can be transmitted anywhere and anytime to customers and helps build brand sustainability (Confos & Davis, 2016).

Digital marketing not only sells products but also develops brand loyalty (Laksamana, 2018). When the brand is captured by consumers in an exclusive, positive, and prominent way in their minds, the brand becomes irreplaceable and will win consumer loyalty (Kotler & Keller, 2016). Social media marketing and brand loyalty become very crucial dimensions of consumer brand resonance and symbolize the ultimate relationship with customers and increase identification with the brand. As a result, conventional promotion is no longer the preferred source of information for consumers and is no longer effective as a means of persuasion to seduce consumers (Chaffey & Chadwick, 2016). The main advantages of digital media include demassification, interactivity, and synchronicity (Ariel & Avidar, 2015).

Compared to conventional marketing, digital marketing has several advantages, including helping communication to many targets related to its very large level of connectivity, completing product sales on time, relevant, specific, and cost-effective manner (Yasmin et al., 2015). Digital marketing enables twenty-four hour services and purchases at transparent prices (Voramontri & Klieb, 2019), lower costs, is efficient, motivates customers to buy more and improves customer service (Lou & Koh, 2018). From the aspect of digital marketing promotions, it can reduce phenomenal advertising costs and increase the multipliyer effect (Ahmed et al., 2019).

Digital marketing consists of search engine optimization (SEO), search engine marketing (SEM), content marketing, influencer marketing, content automation, e-commerce marketing, social media marketing, direct email marketing, electronic advertising displays, e-books, optical discs, and games (Chaffey & Chadwick, 2016). Digital marketing also includes the use of channels that do not require internet use such as mobile phones (both SMS and MMS), social media marketing, display advertising, search engine marketing and other forms of digital media (Yasmin et al., 2015).

As a dynamic approach, digital marketing effectiveness measures are quite diverse. (Dara, 2016) stated that these measures include: newness of information about products, greater involvement, clarity of information about products, ease of comparison with other products, convenience of shopping, sharing product and service content, price clarity, and enabling instant purchases. others emphasize aspects of entertainment, interaction, trendiness, customization (Laksamana, 2018). In particular, Dave Chafeey, et al explained that the effectiveness of digital marketing is determined by: emotional connection, online experience, responsive service nature trust, and fulfillment (Chaffey & Chadwick, 2016). The effectiveness of social media advertising is determined by the brand’s content features, uniqueness, clarity, and interactivity perceived by consumers (Lou & Koh, 2018), as well as empathy, persuasion, impact, and communication (Putra & Lisdayanti, 2020). If digital media is used properly, apart from encouraging buying interest and building loyalty, it also supports the efficiency of promotional costs which will become one of the sources of company competitiveness (Aji et al., 2020).

The increasing use of digital media has also led to major changes in the way brand awareness and purchase intention are built (Pütter, 2017). Purchase intention is the tendency of consumers to buy a brand or take actions related to purchases as measured by the level of possibility of consumers to make a purchase (Kotler & Keller, 2016). Buying interest is a motivating factor that influences behavior; indicates how hard people are willing to try and how much effort they plan to put in (Choedon & Lee, 2020). Purchase intention indicates the likelihood that the consumer will plan or be willing to purchase the product in the future (Peña-García et al., 2020), and the likelihood that the consumer will in the near future (Hutter et al., 2013). Purchase intention reflects the strength of the consumer’s desire to buy a product (Ahmed, Mirza, 2014). Consumers who use social media tend to be exposed to suggestions from their close circle of friends, and recommendations from friends have reduced self-control in choosing products (Wilcox & Stephen, 2013). Social media advertising is considered to be able to stimulate brand purchase intention and intention to share brand information (Lou & Koh, 2018).

In marketing, customer loyalty is seen as the most important issue affecting the way business is conducted (Alharbi & Alhider, 2018). Consumer loyalty becomes a strength for companies against attacks from other companies (Deekshith & Kinslin, 2016). A person who repurchases from the same company and tells by word of mouth to potential customers is called a loyal customer (Mishra & Prasad, 2014).

Customer loyalty is also defined as a psychological character formed by consumer satisfaction formed by service providers that leads to willingness and consistency in establishing relationships (Wong, 2014). While brand loyalty is defined as a deep commitment to repurchase the brand that is his preference consistently in the future despite situational influences and marketing efforts that can lead to behavioral shifts (Handayanto, 2016). Brand loyalty is important because it can create barriers to entry for competitors, avoid threats from competitors, and increase sales and revenue (Ahmed et al., 2019). In addition, loyal customers are less sensitive to price (Erdoğmuş & Çiçek, 2012). Maintaining consumer loyalty to the brand is a strategic effort that is more effective than attracting new customers (Ioanăs & Stoica, 2020). Loyal customers will form recommendations to others and result in financial shares and higher customer retention rates (Zoubi & Al-Harazneh, 2019). In addition, loyal customers will generate sales revenue and profits, and help the company grow or at least survive (Alam Kazmi et al., 2018); (Siby, 2021).

The relationship between brands and consumers develops significantly over time (Sharma et al., 2021). Companies that have successful brands have the power to change value systems and consumer behavior and even create entirely new lifestyles (Grubor & Jakša, 2018). This strength comes from loyal consumers who permanently follow their favorite brands and often identify strongly with that brand (Benoit-Moreau & Parguel, 2011).

Brand loyalty can be measured in various ways: brand-choice sequence, proportion of purchase, brand preference, and brand commitment (Saif et al., 2018). The determinants of brand loyalty consist of: brand experience, (2) brand commitment, ( 3) affective commitment, these three factors will lead to the desire to maintain a brand relationship, and continuance commitment (Maheshwari et al., 2014).Brand loyalty on social media has a positive effect when: the brand offers a profitable campaign, offers relevant content, offers popular content, appearing on various platforms, and offering applications on social media (Erdoğmuş & Çiçek, 2012).

One of the businesses that faces stiff competition and must strive to retain customers is the coffee shop business through the application of digital marketing. The coffee-drinking lifestyle, which is becoming a trend among the people, has helped grow the coffee shop industry. The number of coffee shops in Indonesia is increasing rapidly. In the last three years, the increase has tripled from 1,083 outlets in 2016 to 3,000 outlets in 2019 (https://www.beritasatu.com/economy/601687/2020-kedai-kopi-dipredik-tumbuh-15). Until the end of 2019, the growth reached 15%-20% compared to 2018 which was only 8%-10%. The spread of the coffee shop business extends not only in cities, but also in rural areas. The existence of edai coffee is spread in the shopping center area to the villages.

In the highly competitive coffee shop business, the development of communication technology has changed the way companies serve purchases where consumers generally can order via digital media. On the other hand, coffee shop offerings are now increasingly being done through several online media channels such as marketplace, Instagram, Facebook and other social media. Coffee shop managers expect the use of online media to be the right approach in responding to changing consumer behavior in the face of technological developments. However, how the effectiveness of using online media needs to be explored, especially in building buying interest and brand loyalty.

This study aims to determine the effect of digital marketing implementation in shaping buying interest and brand loyalty in the coffee shop business and to determine the causal relationship model between these variables. The parameters used to measure the variables in this study are quite comprehensive based on literature studies and observations of digital marketing practices on research objects where these measurements have never been used by other researchers. The use of Structural Equation Modeling assisted by Partial Least Square (SEM PLS) software version 3.0 to analyze data is the right method to analyze variables that are constructs that have abstract indicators. Finally, the results of the study will greatly assist coffee shop managers in formulating effective online media communication strategies so that they can determine consumer behavior and be able to attract and retain consumers in this highly competitive era.

RESEARCH METHODS

Operational Variables

This study is an associative quantitative study to examine: 1. causality relation between digital marketing (independent variable/exogenous variable) on purchase intention (dependent variable 1/endogenous variable 1) and brand loyalty (dependent variable 1/endogenous variable 2), and 2: examine the effect of buying interest on brand loyalty in the coffee shop business. To carry out the research, the variables were operationalized based on several research results that have been described in the literature review, as presented in Table 1.

Table 1. Operational Variables

Based on the operationalization of the research variables, the framework of thinking as well as the initial model of this research is shown in Figure 1.

Figure 1. Initial Model of Causality Relationship Between Digital Marketing with Purchase Intention and Brand Loyalty

Population and Sampling

The population of this study were consumers of 136 (one hundred and thirty-six) coffee shops in the Greater Jakarta area with a total sample of 154 people, which were determined based on the convenience sampling method. By the rules of determining the minimum sample in the Structural Equation Model (SEM) analysis method which is the approach in this study, the minimum sample size in this study) is 150 people, which is five times the number of questions analyzed (Sarstedt et al., 2020), so that the number of research samples meets the requirements.

Data Collection Method

The research data was collected using a structured questionnaire using a Likert scale of 1-5. Submission of questionnaires to respondents was done online using Google Form. To test the questionnaire, 30 respondents were tested for validity and reliability. Using the Cronbach Alpha and rho-A values (α > 0.70), the results of the questionnaire test on all questionnaire items were valid and reliable, as shown in Table 2.

Table 2. Cronbach Alpha and rho_A values

Data Analysis Method

Analysis of the research data using the Structural Equation Modeling (SEM) method assisted by Smart PLS software 3.0 version. The steps of analysis carried out in this study are as follows:

1. Design a measurement model by making a path diagram.
2. Test the outer model
3. The inner model test
4. Conclusion

RESULTS AND DISCUSSION

• Descriptive Statistics

The number of coffee shops becoming the object of this research was 136 coffee shops, with three favorites in order: “Kopi Kenangan”, “Starbucks”, and “Janji Jiwa”. The digital marketing technique used by the research object is Instagram social media the most, while Facebook is the least. The complete digital media used by the research object is presented in Figure 2

Figure 2. The Digital Media Used by The Research Object

                                                       Source: Primary Data

Respondents’ assessment of digital marketing performance at coffee shops visited in the last six months is shown in Table 3. From Table 3 it is known that the best digital marketing performance is on the trendiness dimension, while the lowest performance is on the customization dimensions.

Table 3. Respondents’ Assessment towards Digital Marketing Variable Performance

              Source: Primary Data, 2021

• Measurement Model

Before testing hypotheses to predict causality relationship between latent variables in the structural model, the measurement model is previously evaluated to verify indicators of latent variables (outer model). Using PLS processes and procedures assisted by SmartPLS software, an initial model of causality is generated between digital marketing variables on buying interest and brand loyalty along with the loading factor value as shown in Figure 3.

Figure 3 is a path diagram specifying the relationship between latent variables and their indicators. The loading factor value shows the indicator variance that can be explained by the latent variable. This value is also used to test the reliability of each indicator, where a reflective indicator must be eliminated from the measurement model if the loading value (λ) is less than 0.7. From Figure 3 it can be seen that there is one indicator that has a loading factor of less than 0.7, namely the F1 indicator (I got what I ordered from the Kedai Kopi X website) so it was omitted from the research model.

Figure 3. Initial Model of Causality Relationship between Digital Marketing with Purchase Intention and Brand Loyalty with Loading Factor

After the F1 indicator is eliminated, the research model is retested and produces a new path diagram value along with the loading factor as presented in Figure 4.

Figure 4. Second Model of Causality Relationship between Digital Marketing with  Buying Intention and Brand Loyalty with Loading Factor

Based on Figure 4, it is known that more than 70% of the variance on 21 (two recovered one) indicators, namely C1, C2, C3, C4, Ex1, Ex2, Ex3, F2, QI1, QI2, QI3, R1, R2, R3, RE1 , RE2, T1, T2, TR1, TR2, and TR3 can be explained by digital marketing variables. Meanwhile, the buying interest variable can explain the variance of the PI1, PI2, PI3, and PI4 indicators, each of which is more than 70%. While the brand loyalty variable is able to explain the three indicators, namely BL1, BL2 and BL3 each above 70%. So, overall, each variable has been able to explain the variance of each of the indicators that measure it.

In addition to the above criteria, the feasibility of a measurement model can be seen from the composite reliability and convergent validity (AVE) values presented in Table 4.

Table 4. Composite Reliability and Convergent Validity (AVE) values

The composite reliability value presented in Table 4 shows that the three latent variables have a composite reliability value above 0.6. That is, the indicators that have been set have been able to measure each latent variable (construct) well or it can be said that the three measurement models are reliable. The value of convergent validity shows the correlation between indicators, where the higher the correlation between the indicators that make up a construct, the better the model. The AVE value shown in Table 4 shows that the three latent variables have an AVE value above the minimum criteria, namely 0.5 so that the convergent validity measure is good or it can be said to have met the convergent validity criteria.

To determine the validity of the research construct, a discriminant validity test was conducted. Discriminant Validity is useful for knowing the correlation between manifest variables and their constructs by looking at the cross loading value of each construct. A measurement model has good discriminant validity if the correlation between the construct and its indicators is higher than the correlation with indicators from other constructs. The cross loading value is shown in Table 5, which shows it is higher than 0.5 so that it meets the discriminant validity criteria.

Table 5. Relationship Values Between Digital Marketing, Purchase Intention and Brand Loyalty

• Structural Model

The structural model (inner model) is a model describing the relationship between latent variables that is evaluated using the path coefficient, R2 and GoF. The results of the path coefficients and T-statistic values obtained through the bootstrapping process with 5000 repetitions are shown in Figure 5.

Figure 5. Bootstrapping Calculation Results Between Digital Marketing with Purchase Intention and Brand Loyalty

In the structural model test, the feasibility of a measurement model can be determined from the t-statistic value of the loading results. A model is said to be good if the t-statistic value is greater than the critical t value of 1.65 (2-tailed) at a significance level of 10%. The loading results along with the t-statistic values obtained from the bootstrapping process are shown in Table 6 and Table 7.

Table 6. T-Statistic Test Results of Measurement Model Loading Value

                *) Significant with significance level 10%

From Table 6, it is known that all manifest variables have values above 1.65 so they are significant. While the results of the path coefficients and t-statistic values obtained through the bootstrapping process are shown in Table 7.

Table 7. Path Coefficient Values

From Table 7, it is known that the effect of digital marketing on buying intentiont is 0.619, which means that there is a positive influence of digital marketing on buying intentetion. With a t-statistic value of 11.870 and a P value of 0.000, the influence of digital marketing on buying interest is significant.

The causal relationship between digital marketing and brand loyalty is 0.269 which means that there is a positive influence between digital marketing and brand loyalty. The t-statistic value is 11,927 with P Values of 0.000, the relationship between digital marketing and brand loyalty is significant. While the causal relationship between buying intention with brand loyalty is 0.640, which means that there is a positive influence between buying interest and brand loyalty. The t-statistic value of 16.870 with P Values of 0.000 indicates that the effect of buying interest on brand loyalty is significant.

Furthermore, the feasibility test of the model is carried out using the R Square and R Square Adjusted values as shown in Table 8.

Table 8. R Square and R Square Adjusted Values

From Table 8 it is known the R Square value assessing how much influence digital marketing (X1) and buying interest (X2) have on brand loyalty (Y) is 0.696 with an adjusted r-square value of 0.692. Therefore, it can be explained that all exogenous constructs (X1 and X2) simultaneously affect Y by 0.692 or 69.2%. Because Adjusted R Square is more than 33%, the effect of all exogenous constructs X1 and X2 on Y is strong (Ghozali & Latan, 2015).

Meanwhile, the simultaneous influence of digital marketing and brand loyalty on purchase intention is 0.383 with an Adjusted R Square value of 0.379. These results indicate that the influence of digital marketing and brand loyalty simultaneously affects buying interest by 37.9%, which is moderate effect.

To find out whether or not there is a significant relationship between variables can assess the magnitude of the influence between variables and Size Effect or F-square. It can be stated that the relationship between digital marketing and brand loyalty is very strong (0.811), and the relationship between buying interest and brand loyalty is weak (0.147) while the relationship between digital marketing and buying interest is strong (0.622) (Sarstedt et al., 2020).

CONCLUSIONS AND RECOMMENDATIONS

This study has shown all indicators (manifest variables) of the research variables tested can describe their constructs. From the hypothesis test, it is known that digital marketing has a significant positive effect on buying interest by 61, 9% and on brand loyalty has a significant positive effect of 26,9%, while the effect of buying interest on brand loyalty is 64 %. The relationship between digital marketing and buying interest, with brand loyalty, is a significant positive. Likewise, the relationship between buying interest and brand loyalty is significantly positive. These results as a whole strengthen the results of previous research on the effect of digital marketing on buying interest and brand loyalty. The results of this study can be a reference for coffee shop managers to strengthen the quality and role of digital marketing in increasing buying interest and brand loyalty, as a source of competitive advantage.

Suggestions for further research should be able to use a larger sample size so that a more suitable model is produced. In addition, it is necessary to re-examine the significance of one of the website indicators, namely that buyers get what they ordered through the website as a manifest variable of digital marketing. Further marketing can also add other variables related to changes in consumer behaviour, especially concerning technological advances and an in-depth study of the selection of indicators is needed.

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