Factors Influencing Brand Loyalty in the Distribution of Indonesian FMCG Product

Abstract

Objective: In Indonesia's dynamic FMCG industry, establishing brand loyalty is crucial. This study examines the impact of marketing strategies such as digital advertising, sales promotions, and effective distribution logistics on brand loyalty through customer satisfaction, focusing on the Wafer Tango brand. Methodology: Using a quantitative survey methodology, research finds that marketing strategies and distribution logistics influence customer satisfaction, with perceived quality having the most substantial effect. Customer satisfaction acts as a mediator, linking these strategies to brand loyalty. Findings: Prioritizing customer satisfaction is essential for fostering brand loyalty in Indonesia's FMCG market. Effective digital advertising, appealing sales promotions, and efficient distribution enhance customer satisfaction and brand loyalty. Maintaining high perceived quality is critical for brand success. Conclusion: The implications of this research are significant for FMCG companies in Indonesia, as it highlights the importance of customer satisfaction as a mediator in the relationship between marketing strategies and brand loyalty. Sales promotions significantly drive brand loyalty, while perceived quality influences it indirectly through customer satisfaction. Surprisingly, digital advertising lacks a statistically significant direct effect on brand loyalty or customer satisfaction. The study underscores the importance of effective distribution strategies to ensure marketing efforts reach the intended audience.

1. Introduction

In the era of technological advancement, the Fast-Moving Consumer Goods (FMCG) industry has emerged as a critical component of the global economy. FMCG products are characterized by their rapid sales, driven by affordable prices (Thain & Bradley, 2014).

The FMCG sector constitutes a distinct industrial segment that significantly contributesto a country’s economy. Products in this category are characterized by a short shelf life, driven by two primary factors: high consumer demand, which accelerates products turnover, and their perishable nature, making them prone to damage or spoilage shortly after production (Thain & Bradley, 2014).

The FMCG industry in Indonesia is experiencing rapid growth, attracting both local and multinational companies. It appeals to a wide range of job seekers, from fresh graduates to experienced professionals. A key draw of the FMCG industry lies in the prominence of renowned companies operating within. As the FMCG industry continues to grow, companies face increasing competition to attract and retain customers. One common strategy for gaining competitive edge is through innovation and the expansion of the distribution network (Sinurat & Dirgantara, 2021).

In 2022, Figure 1 depicts the GDP of Indonesia's non-oil and gas processing industry, which accounts for 16.10% of the national GDP and serves as a crucial indicator for assessing the country's economic performance. The food and beverage industry dominatesthis sector, contributing 38.35% to its overall GDP. This highlights the significant role of the food and beverage industry in shaping Indonesia's economic landscape, contributing over one-third of the sector’s total GDP (Statistics Indonesia, 2023).

Figure 1: Gross Domestic Product (GDP) of Indonesia’s Non-oil and Gas Processing Industry in 2022

One example of a company in Indonesia in the Fast-Moving Consumer Goods (FMCG) industry isthe Orang Tua Group, which operates in various FMCG fields, including food, beverages, and personal care distribution. Founded in 1948, the Orang Tua Group entered the consumer goods industry in 1984. By 2004, the company had expanded its operations to include business units in various sectors, such as food (wafers, biscuits, chocolate, candy), beverages (ready-to-drink beverages, health beverages), and personal care (oral care, hand soap, bath soap, hand sanitizer).

In the modern era, marketing has significantly transformed, with digital advertising emerging as a key component. This strategy leverages digital platforms such as social media, apps, browsers, and blogs to promote products or services and drive consumer purchases.

Wafer Tango integrates digital advertising with a brand ambassador, Vanesha Prescilla, to enhance brand equity awareness. This strategy underscores their commitment to innovation, reinforcing Wafer Tango’s market position and enhancing consumer engagement.

Sales promotions, such as Tango and Indomaret collaboration, play a crucial role. This partnership offers consumers discounts on cooking oil at Indomaret with every Tango bouquet purchase, a cleverstrategy to enhance product appeal and create cross-selling opportunities.

Product quality is crucial in shaping consumer perceptions and fostering brand loyalty. Perceived quality, as understood by customers, is a key factor in FMCG assessments. Tango’s perceived quality enhances the brand’s reputation, driving return on investment and fostering brand loyalty (Baumann, 2019).

Customer satisfaction is essential for market share and brand loyalty. It serves as a key indicator of how well a product or service meets consumer expectations. It influences brand loyalty, where satisfied customers tend to remain loyal, contributing to long-term growth (Ha & Park, 2012).

The focus on Wafer Tango stems from its significant presence in Indonesia’s FMCG sector and its innovative use of digital advertising and sales promotions. The research was conducted from 2022 to 2024.

The research focuses on investigating whether factors such as digital advertising, sales promotion, and perceived quality influence brand loyalty through customer satisfaction, within the context of distribution logistics. Given the high competition in Indonesia’s FMCG sector, brand loyalty is a critical determinant ofsuccess. Understanding the interaction between marketing strategies and distribution logistics in affecting customer satisfaction and brand loyalty is vital for businesses in this market. This study aims to explore these dynamics, emphasizing the role of effective distribution strategies in enhancing the reach and impact of marketing efforts. By integrating logistics and trade aspects into the analysis, the research provides valuable insights into how robust distribution channels can support high-quality products and strategic promotions, ultimately fostering long-term brand loyalty.

This research is novel in its uniqueness in the integration of marketing strategies and distribution logistics on brand loyalty, mediated by customer satisfaction. Given the rapid growth and intense competition in Indonesia’s FMCG market, understanding these dynamics is crucial for businesses aiming to sustain and expand their market share.

2. Literature Review

2.1. Elaboration Likelihood Model (ELM) Theory

The Elaboration Likelihood Model (ELM), developed by Richard E. Petty and John T. Cacioppo, explains when and how individuals may and may not be persuaded by a message. ELM proposes two routes of persuasion that can influence consumer behavior enhancement and adaptation: the central route and the peripheral route. The central route involves persuasive functions that require active participation in a thoughtful, wise, and concentrated understanding process. In contrast, the peripheral route relies on psychological cues and emphasizes non-content elements when processing conveyed messages (Petty & Cacioppo, 1986).

According to ELM, individuals utilize two paths to process a persuasive message:

a) Central Route: This path is taken when individuals have both the motivation and ability to deeply process a message. In this route, individuals actively elaborate on the message by evaluating the presented arguments and their relevance to their needs and beliefs.

b) Peripheral Route: This path is taken when individuals have low motivation and ability to deeply process a message. In thisroute, individuals are more easily influenced by peripheral factors, such as the communicator’s attractiveness, source credibility, or the message’s alignment with social norms.

c) Several studies have found that the most effective factors in ELM influencing long-term persuasion are consumers' ability to elaborate and understand the conveyed persuasion. This is due to consumers’unrestricted freedom to publish content, making the quality and credibility of persuasive messages critical and deserving attention (Giantari et al., 2020).

2.2. Distribution Channel

In the theoretical framework outlined in “Distribution Channels: Understanding and Managing Channelsto Market,” distribution channels are defined as the routes or intermediaries that ensure products and services reach the market. This framework covers the entire process, which includes:

● Market and customer access and services.

● Brand control.

● Creation of differentiation.

● Enhancement of business distribution models.

This approach highlights not only the pathways through which products move but also the management of relationships with the various parties involved. Understanding the business models of each intermediary is essential for optimizing distribution channels and fostering effective business relationships (Keating, 2010).

2.3. Social Media

Social media is a commonly used term to describe a type of new media that involves interactive engagement. The evolution of media is typically divided into two distinct eras: the broadcast era and the interactive era. During the broadcast era, media was primarily centralized, with a single entity— such as a radio or television station, newspaper company, or film production studio—disseminating messages to a broad audience. Feedback to the media was generally indirect, delayed, and impersonal (Manning, 2014).

Social media marketing leverages internet technology to promote business products or services through social media platforms and websites. The growth of social media marketing enables two-way communication between sellers and buyers, facilitating the exchange of information online. Selecting the appropriate social media marketing platform is crucial for organizations, as it must align with the target market and foster customer engagement and purchase intentions. The chosen platform significantly impacts the success of the marketing strategy and requires thorough data analysis to inform the strategy's direction and objectives. Social media marketing enables organizations to engage directly with customers, address their issues and complaints, and provide immediate solutions. It also offers opportunities for direct product sales and the promotion of new products or services through customer networks (Tarigan, 2024).

2.4. Digital Advertising

Digital advertising encompasses marketing strategies utilized by companies or brands to publicize their products or services through digital platforms or the internet. The goal of digital advertising is to quickly and broadly reach consumers or potential customers. According to Rodgers and Thorson, digital advertising leverages technological advancement and the digital landscape to deliver promotions or with subtle impact. Platforms such as Facebook, YouTube, Instagram, and other social media are commonly utilized in digital advertising (Rodgers & Thorson, 2017).

2.5. Sales Promotion

Sales promotion is a marketing communication method aimed at attracting new consumers, encouraging new product trials, stimulating additional purchases, responding to competitors’ promotional activities, enhancing impulse buying, or strengthening partnerships with retailers. Although sales promotion techniques typically yield short-term effects, they are a crucial component of marketing strategy, comprising a series of short-term incentives designed to encourage faster purchases of specific products or services by consumers or retailers (Kotler & Keller, 2016).

Ratih and Rahanatha (2020) identify three dimensions of sales promotion used in the research: discounts, price packs, and loyalty programs. Discounts are incentives given to consumers by reducing the price of a product orservice. Price packs are incentives given to consumers by offering a product or service at a lower price. Loyalty programs are programs that provide special benefits to consumers who make repeated purchases (Ratih & Rahanatha, 2020).

2.6. Perceived Quality

Perceived quality refers to customers’ assessment of the overall quality or superiority of a product or service in comparison to others, based on their expected needs (Kotler & Keller, 2016). This perception arises from customers’ observations and interpretations of the visible or tangible aspects of the product or service.

Perceived quality, also referred to as the perception of quality, is the customers’ assessment regarding the overall quality or excellence of a product or service in relation to their expectations(Aaker, 2009). Customer expectations play a crucial parameter in shaping their perceptions of a product. Therefore, perceived quality is not solely linked to the physical quality of a product but also associated with customers’ expectations and desires.

In general, perceived quality encompasses customers’ perceptions of product quality and prestige, including factors such as price and corporate responsibility. These perceptions are subjective and closely tied to customers' perceptions and interests.

2.7. Brand Loyalty

In Aaker's book Managing Brand Equity, brand loyalty represents consistent purchasing behavior over time and a positive attitude towards the brand. Brand loyalty develops when a brand aligns with the consumer’s personality or self-image, or when it delivers satisfaction and unique benefits that meet consumers’ needs (Aaker, 2009).

On the other hand, Giddens and Hoffman define brand loyalty as a consumer’s preference for a specific brand over othersin a particular product category (Giddens & Hofmann, 2002). This decision is influenced by the consumer’s perception that the brand offers appropriate product features, image, or quality in relation to its price.

Loyal customers often prioritize a product when needed and are inclined to recommend it to others. Brand loyalty generates positive information about the products. On social commerce websites, loyal customers are likely to repurchase, create content, and share positive reviews (Tarigan, 2024).

2.8. Customer Satisfaction

Although the term ‘customers’ and ‘consumers’ are often used interchangeably, they hold a slight distinction. A customer is the individual who initiates the purchase of a product or service. In contrast, a consumer refers to the one who ultimately uses or consumes the product.

Understanding customer satisfaction is crucial. It reflects a customer's emotional response after using a product or service, based on a comparison between their expectations and the perceived performance. According to Kotler and Keller (2016), customer satisfaction arises from evaluating the gap between a customer’s expectations and the actual performance delivered by the product. Kotler and Armstrong (2023) further refine this definition, suggesting customer satisfaction depends on whether a product’s performance meets the buyer’s expectations. When performance falls short, dissatisfaction results. Conversely, meeting or exceeding expectationsresults in satisfaction, or even delight.

Customer satisfaction is assessed at the time of purchase, during product or service usage, and throughout the overall acquisition or service experience. It reflects the level of enjoyment customers derive from services that meet their needs and expectations (Yoo & Park, 2020).

In essence, both definitions highlight the critical importance of customer experiences. Positive customer responses and experiences after using a product are key factors that determine a company’s success, influencing its ability to establish, maintain, and grow its business.

Table 1: Theoretical Background of Previous Studies

3. Research Method and Materials

This research is a continuation of previous existing research related to factors influencing brand loyalty.

In quantitative research, theory testing is utilized to explain or predict responses to research inquiries. A vital aspect involves presenting the theory that forms the research framework. Thistheory serves as an explanatory or predictive tool for understanding relationships among variables in the study. Consequently, establishing a theoretical foundation and identifying variables is essential, as it facilitates the formulation of research questions and hypotheses. The application of this theory helps establish connections among variables in the research (Creswell, 2014).

In this study, the research follows the positivist paradigm, which viewsresearch as adhering to conventional approaches that prioritize scientific methods and an empirical analysis. From this perspective, it is asserted that identifiable causes influence outcomes, guiding research to focus on identifying and evaluating these causal factors (Littlejohn & Foss, 2009).

This study employed quantitative research, defined as the use of theory testing to clarify or predict responses to research inquiries. A critical aspect of this approach involves presenting the theory forming the research framework. This theory serves as an explanatory or predictive tool for understanding relationships among variables in the study. Therefore, establishing a theoretical foundation and identifying variables is essential for formulating research questions and hypotheses. Applying this theory facilitates bridging the relationships among variables in the research (Creswell, 2014).

This study employed quantitative methodology, utilizing Likert scale questionnaires asthe primary data collection tool. Quantitative approaches enable the assessment of objective theories by examining relationships among measurable variables. These variables, typically present on instruments, can be quantified and analyzed using statistical methods (Creswell, 2014).

This research employed a nonprobability sampling technique, specifically the purposive sampling method, where samples are selected based on predetermined criteria (Creswell, 2014).

This approach was adopted due to specific requirements, such as the recent purchases of “Wafer Tango” products and active Instagram use for daily interactions. The purposive sampling technique included a detailed selection process using a questionnaire to identify suitable respondents. The sample size was determined using Taro Yamane's formula, resulting in 399 respondents, which was deemed adequate for the study (Yamane, 1967).

This research ensured that all participants provided informed consent. Ethical considerations included maintaining participant confidentiality and ensuring data privacy. This research analyzed whether digital advertising, sales promotion, and perceived quality of Wafer Tango consumers have positively affected brand loyalty, with customer satisfaction serving as an intermediary variable.

Figure 2: Research Framework

Based on the conceptual framework and the identified variables—X1 (Digital Marketing), X2 (Sales Promotion), Z1 (Customer Satisfaction), and Y1 (Brand Loyalty), a hypothesis test is essential to explore potential relationship between the independent and the dependent variables. According to Creswell, a hypothesis serves as a provisional response to the formulation of research problems, representing a temporary assumption regarding the variables under examination. Given its hypothetical nature, the hypothesis should provide clear implications for testing the specified relationships (Creswell, 2014).

Consequently, the research hypotheses are reformulated as follows: H1: Digital Marketing has a positive and significant impact on Customer Satisfaction. H2: Sales Promotion exhibits a positive and significant influence on Brand Loyalty. H3: Perceived Quality demonstrates a positive and significant effect on Brand Loyalty. H4: Customer Satisfaction exhibits a positive and significant influence on Brand Loyalty. H5: Digital Advertising has a positive and significant effect on Brand Loyalty. H6: Sales Promotion exhibits a positive and significant influence on Brand Loyalty. H7: Perceived Quality has a positive and significant effect on Brand Loyalty.

4. Results and Data Finding

4.1. Reliability and Validity Assessment

This study included a total of 45 items: 18 for Digital Advertising (X1), 6 for Sales Promotion (X2), 11 for Perceived Quality (X3), 7 for Brand Loyalty (Y1), and 3 for Customer Satisfaction (Z1). The model evaluation involved assessing loading factors, Cronbach’s alpha, composite reliability, and average variance extracted (AVE), as depicted in Table 2.

Table 2: Reliability and Validity Estimates for Constructs of the Model

Validity assessment is performed using convergent validity within the reflexive model, focusing on loading factor values. An observed variable is deemed valid if its loading factor exceeds 0.5. The table indicates that all loading factor values excluding X2.4 surpass this threshold, signifying a strong relationship between observed variables (manifest) and their dimensions.

Furthermore, Table 2 presents AVE, composite reliability, and Cronbach alpha values. According to a study by Chin and Newsted (1999), AVE should exceed 0.5, composite reliability should surpass 0.7, and Cronbach alpha should be above 0.7 (Chin & Newsted, 1999). The results confirm that AVE, composite reliability, and Cronbach alpha meet the validity criteria.

4.2. Structural Model Analysis

This study employed the Partial Least Square (PLS) method. The following image presents the calculation results of the initial model, processed using the SmartPLS 3.0 application. As the X2.4 loading factor values do not exceed the validity threshold, this variable will be excluded from the model below.

As depicted in the structural model equation (Figure 3), sales promotion shows a path coefficient of 0.578 in relation to brand loyalty. This represents a notably robust correlation between sales promotion and brand loyalty, characterized by a positive directional relationship. An increase in sales promotion value corresponds to a heightened level of brand loyalty.

Figure 3: Structural Model

Sales promotion also demonstrates a path coefficient 0.279 in relation to customer satisfaction, indicating a positive value. Perceived quality shows a path coefficient of 0.466 with customersatisfaction and 0.051 with brand loyalty. This indicates a very strong relationship between perceived quality and brand customer satisfaction, suggesting that the higher the perceived quality leads to greater customer satisfaction.

Digital advertising through brand loyalty shows a path coefficient of -0.054 on brand loyalty. Meanwhile, digital advertising towards customer satisfaction shows a path coefficient of 0.072.

Following the evaluation of the outer model, the next step involves testing the inner model, which outlines the connections between latent variables in the structural model. This model explains the relationships between latent variables based on the underlying theory. The assessment of the inner model encompasses R-square determination coefficients and conducting hypothesis testing, with a focus on the endogenous constructs detailed in the provided table.

An R-square value of 0.75 indicates a strong model, 0.50 indicates a moderate model, and 0.25 indicates a weak model.

Table 3: R-Square Value Evaluation

Based on the table above, digital advertising, sales promotion, and perceived quality account for 49.7% of the effect on brand loyalty. Additionally, these factors influence brand loyalty through customer satisfaction by 45.1% and the remaining 54.6% attributed to other factors.

In summary, the model explains 49.3% of the variance in brand loyalty directly through the effects of digital advertising (path coefficient = -0.054), sales promotion (path coefficient = 0.578), and perceived quality (path coefficient = 0.051). These variables exhibit positive/negative and statistically significant direct effects on brand loyalty.

Sales promotion demonstrates the strongest direct effect on brand loyalty, highlighting its importance in driving brand loyalty.

Customer satisfaction plays a mediating role. The initial variables also influence brand loyalty indirectly through customer satisfaction (R-square for customer satisfaction = 0.451). While the R-square doesn't directly capture this indirect effect, the path coefficients provide a more comprehensive view (Table 4).

Table 4: Path Coefficients

The structural equation modeling (SEM) analysis provides nuanced insights into the hypothesized relationships between variables, with the significance of these relationships assessed using both T statistics and p-values. When examining the relationship between digital advertising (X1) and brand loyalty (Y1), the non-significant p-value of 0.601 suggeststhat the observed relationship may be due to random chance. This interpretation is supported by the T statistic of 0.524, which represents the ratio of the path coefficient to its standard deviation. A T statistic close to 0 indicates that the relationship is not statistically significant.

Conversely, the significant relationship between digital advertising (X1) and customer satisfaction (Z1) is demonstrated by the p-value of 0, providing strong evidence against the null hypothesis of no relationship. The T statistic of 1.231 further supportsthis, indicating a moderate strength of the relationship relative to its standard deviation.

Similarly, the significant relationship between sales promotion (X2) and brand loyalty (Y1) is confirmed by the p-value of 0 and the high T statistic of 10.616, indicating a robust and statistically significant relationship between these variables.

Furthermore, the relationship between perceived quality (X3) and brand loyalty (Y1) is not statistically significant, with a p-value of 0.256. This suggests insufficient evidence to establish a direct relationship between the two variables. The T statistic of 1.137 confirms this interpretation, indicating a relationship of moderate strength relative to its standard deviation.

Additionally, the significant p-value of 0 for the relationship between perceived quality (X3) and customer satisfaction (Z1) indicates a substantial direct impact of perceived quality (X3) on customersatisfaction (Z1), further supported by the high T statistic of 10.096. Finally, the significant relationship between customer satisfaction (Z1) and brand loyalty (Y1) is confirmed by the low p-value of 0 and the moderate T statistic of 3.631, suggesting a notable direct impact of CS (Z1) on BL (Y1).

In summary, the combination of p-values and T statistics provides a comprehensive understanding of the significance and strength of the relationships between variables within the structural equation model, helping to clarify the underlying mechanisms driving the observed associations.

Next, the F Square value which is used to examine the effect of predictors of latent variables at the structural level. An F Square value of 0.02 indicates a small effect, 0.15 represents a medium effect size, and 0.35 indicates a large effect size. Based on the results of testing with SmartPLS., the F Square results are as follows:

Based on table 5, digital advertising (X1) has minimal impact on both brand loyalty (Y1) and customer satisfaction (Z1). In contrast, sales promotions (X2) show a strong influence on brand loyalty, but a lesser effect on customer satisfaction (Z1). However, perceived quality (X3) has a weak direct effect on brand loyalty (Y1) but a more moderate influence on customer satisfaction (Z1).

Table 5: F-Square Value Evaluation

Interestingly, customersatisfaction plays a moderate role in driving brand loyalty (Y1). In summary, while digital advertising appears less effective, sales promotions directly enhance loyalty, and perceived quality indirectly influences loyalty through its impact on customer satisfaction.

The next phase involves examining the Q-square predictive relevance for the construct model. The Q-square test assesses the alignment between the observed values generated by the model and its parameter estimations. A Q-square value greater than zero indicates that the model has predictive relevance, while a value below zero suggests a lack of predictive relevance (Aniq & Indra, 2022).

Using the R² value from the table above, the following Q-square calculation results are obtained:

Table 6: Q-Square Value Evaluation

The analysis reveals promising results. AQ-square value greater than zero indicates that the model effectively captures the relationships between variables, making it relevant for predictions. This value also reflects the model's ability to explain the observed measures of the endogenous latent variables (variables influenced by other variables in the model).

In this case, the Q-squared value suggests that the model explains 72.4% of the variance in the observed measures of these endogenouslatent variables. The remaining 27.6% can be attributed to model error or unexplained factors. In simpler terms, the model successfully reconstructs most of the observed data, explaining 72.4% of the variation in the endogenous latent variable measurements. However, there is still some room for improvement, as 27.6% remains unexplained.

5. Discussion

These findings provide invaluable insights for businesses aiming to establish long-lasting customer relationships. They highlight the significant impact of sales promotions in fostering loyalty, emphasizing the importance of strategic implementation to maintain brand value over time. Moreover, perceived quality emerges as a key factor in the loyalty equation. By prioritizing the delivery of high-quality products or services, businesses can enhance customer satisfaction and strengthen brand loyalty.

The findings align with the Elaboration Likelihood Model (Petty & Cacioppo, 1986), where customer satisfaction, influenced by perceived quality and effective distribution logistics, serves as a central route to enhance brand loyalty. This supports previous research that highlights the importance of high-quality products and strategic promotions (Ha & Park, 2012).

Although digital advertising in this analysis did not directly influence loyalty, its potential role in shaping customer perceptions and brand image warrants further investigation. Future research could explore the indirect effects of digital advertising on brand loyalty through its impacts on perceived quality or customer satisfaction.

This study also underscores the critical role of distribution logistics in the FMCG sector. Efficient and consistent distribution strategies ensure that marketing efforts effectively reach the intended audience, providing products accessibility and enhancing the visibility of promotions. This accessibility is crucial for boosting customer satisfaction and, subsequently, brand loyalty. The integration of robust distribution channels with high-quality products and strategic promotions is essential for sustaining brand loyalty in Indonesia's competitive FMCG market.

In summary, this study provides a foundation for understanding the complex dynamics between marketing strategies, customer satisfaction, perceived quality, distribution logistics, and brand loyalty.

This research highlights the pivotal role of customer satisfaction in enhancing brand loyalty, suggesting that FMCG companies should invest in quality improvements and efficient distribution logistics. Policymakers can leverage these insights to support regulations that promote fair and effective distribution practices.

Future research could further explore these relationships, uncovering additional insights and opportunities for businesses to strengthen customer loyalty. Key areas for future exploration include:

a) Segmenting the Data: Analyzing the effects across different customer segments to tailor marketing strategies for specific groups.

b) Including Additional Variables: Exploring the influence of other factors, such as brand image, customer experience, and social media engagement.

c) Employing Longitudinal Data: Investigating how these relationships evolve over time to gain a more comprehensive understanding of customer loyalty development.

Building on these findings and exploring new avenues, businesses can refine their marketing and distribution strategies to create a more holistic approach that fosters long-term customer loyalty. This research emphasizes the importance of integrating effective distribution logistics with marketing efforts to achieve sustained brand loyalty in the FMCG sector.

6. Conclusion

This study explored the factorsinfluencing brand loyalty in the distribution of Indonesian FMCG products, focusing on digital advertising, sales promotions, perceived quality, customer satisfaction, and distribution logistics. Through the analysis of path coefficients, we identified the direct effects of various marketing efforts on these key metrics.

The analysis revealed some noteworthy findings. Sales promotions emerged as a significant driver of brand loyalty, showing a strong positive effect, indicating that promotional activities are powerful tools for fostering customer loyalty. Perceived quality had a more indirect influence; although its direct effect on brand loyalty was weak, it significantly impacted customer satisfaction, which in turn positively influenced brand loyalty. Interestingly, digital advertising, based on this data, did not have a statistically significant direct effect on either brand loyalty or customer satisfaction.

Moreover, the study emphasizes the critical role of efficient distribution logistics in enhancing brand loyalty. Effective distribution strategies ensure that marketing efforts reach the intended audience, making products more accessible and promotions more visible. Consistent and widespread distribution improves customer satisfaction by ensuring product availability and reliability. Therefore, integrating robust distribution channels with high-quality products and strategic promotions is essential for building and sustaining brand loyalty in Indonesia's competitive FMCG sector. This research underscores the pivotal role of logistics and trade in the overall marketing strategy, highlighting their value in driving customer reach and brand success.

One limitation of this study is its focus on a single brand within the Indonesian FMCG sector, which may limit the generalizability of the findings. Future research could examine multiple brands and incorporate longitudinal studies to assess changes over time. Additionally, investigating the impact of emerging digital marketing trends could provide deeper insights into brand loyalty dynamics.