174 American Journal of Economic and Management Business p-ISSN: XXXX-XXXX e-ISSN: 2835-5199 Vol. 3 No. 7 July 2024 The Influence of Product Quality, Price, Brand Image and Excellent Service on Consumer Satisfaction (Study on Aqua Products in Malang City) Cindy Seftya Rahma1*, Lailatul Farida2 Maulana Malik Ibrahim State Islamic University, Malang, East Java, Indonesia1,2 Email: cindyseftya221@gmail.com1*, ellyfarida.fia@gmail.com2 Abstract The purpose of this study is to examine the relationship between product quality, price, brand image, and service excellence on consumer satisfaction with AQUA products. Using partial least squares (PLS) as the data analysis technique, we analyzed responses from a sample of 240 respondents. The results indicate that product quality, price, and service excellence do not significantly influence consumer satisfaction with AQUA products. In contrast, brand image positively influences customer satisfaction. Based on these findings, we recommend improving product quality and adjusting pricing strategies. Although customer service is not a primary factor in consumer satisfaction, companies should ensure a consistent and positive experience at every touchpoint to maintain a strong brand image. Keywords: Product Quality, Price, Brand Image, and Excellent Service, Customer Satisfaction. INTRODUCTION Indonesia is experiencing increasing population growth every year. Demographic data by age group for the 2020-2023 Provisional Population estimate is provided by the SP2020 Population Administration on the basis of the Central Statistics Agency, which shows a population of 278,696.2 people. Humans have many needs to survive, such as food, clothing, and shelter. Water is the main need of living things, and because it is so important for daily activities, the government has made water a top priority in the national development program. The number of households with access to proper drinking water was 90.78% in 2021, up from 90.21% in the previous year (Ali, 2022). The graph of potable water needs from 2011 to 2021 is shown in Figure 1. mailto:cindyseftya221@gmail.com Cindy Seftya Rahma, Lailatul Farida 175 Source: Indonesia.id Data (2022) Figure 1. Percentage of Households With Decent Drinking Water in Indonesia (2011-2021) For 45 years, Aqua has been one of the main brands of bottled drinking water (AMDK) in Indonesia. With a market share of more than 40%, Aqua dominates the drinking water market in Indonesia. Aqua is produced by the "Aqua Group" consisting of PT. Aqua Golden Mississipi, PT. Tirta Investama, and PT. Tirta Sibayakindo is the main producer of Aqua. They have a strategic partnership with Danone, which now owns a majority stake in Aqua Group. Currently, Aqua operates 17 factories in various locations in Indonesia. Aqua products are sold in various packaging, one of which is aqua PET bottles 600ml, and 1500ml, at very affordable prices. Aqua also demonstrates its commitment to the environment through its Aqua Lestari program, which includes recycling, reuse, and carbon emission reduction practices through reducing packaging weight (Aqua, 2017). Databoks noted that in December 2022 there were 74.9% of consumers of mineral water with the aqua brand who named mineral water with the aqua brand as the most preferred bottled mineral water in Indonesia (Annur, 2022). Based on a survey conducted by Jajak aka JakPat on September 26, 2022 to identify consumer preferences for mineral water brands in Indonesia. Of the 1,434 respondents involved, the survey found that Aqua became the most preferred mineral water brand with a percentage of 74.9%. Followed by Le Minerale with a percentage of 62.1%, ranking second. Nestle and Vit ranked third and fourth with 23.6% and 21.6%, respectively. Meanwhile, Crystalline and Cleo have percentages of 17.3% and 17.2%, respectively. Ades, on the other hand, ranks at the bottom with a percentage of 15.3%. This survey shows an overview of consumer preferences for mineral water brands in Indonesia, which can be an important reference in marketing strategies and product development for mineral water producers (Annur, 2022). The bottled drinking water (AMDK) business is increasingly attractive because the demand for drinking water continues to increase in line with population growth. More and more companies are involved in the bottled water business, but Aqua remains the market leader as the largest and first drinking water producer in Indonesia. To maintain its position, Aqua is committed to always offering the best quality to consumers, ensuring customer loyalty to the Aqua brand. There are American Journal of Economic and Management Business Vol. 3 No. 7 July 2024 176 many factors that affect consumer satisfaction, one of which is product quality. Consumers usually always expect quality products that can last for a long time (Novianti and Purba 2020). Quality is a type of product or service that can be measured by the level of reliability, additional features, taste, content, and performance function of a product in meeting consumer expectations. While a product is something that will be presented to the market to be appreciated, watched, and purchased to meet customer needs or desires, product quality greatly affects consumer satisfaction. The higher the quality of a product, the more satisfied the customer is with the product (Foroudi et al., 2020). A study conducted by Afshar (2011) revealed that product quality has a significant impact on consumer satisfaction. The relationship between product quality and customer satisfaction is closely linked. If a company offers a superior product and exceeds consumer expectations, it is likely that consumers will feel satisfied with the product after purchasing and using it. Conversely, if the consumer's experience when using the product tends to be disappointing, they may look for alternatives from other brands. Consumer satisfaction itself is the result of the quality presented by the company. The higher the quality, the greater the potential to get more customers (Azzahra & Fachira, 2022). Therefore, companies must continue to maintain or improve the quality of their products so that consumers are not tempted to switch to competing brands and remain loyal to the brands offered. However, a study conducted states that product quality is not able to have a significant impact on consumer satisfaction. This is due to various different perceptions from consumers regarding the level of satisfaction they have. In addition to product quality, companies must consider brand image when delivering a product to build consumer satisfaction with the product purchased. Brand Image, according to Parris et al. (2023) is a set of beliefs, ideas, and impressions that a person has about a brand. Therefore, consumer attitudes and actions towards a brand are mainly determined by the product's Brand Image. If the Brand Image of a product increases, it will display a more positive consumer perception of the company's products. The brand is the consumer's perception of the brand as a reflection of the association that exists in the consumer's mind or mind (Alić et al., 2020). However, by definition (brand image) can be said to be a kind of association that occurs in the minds of consumers when they remember a certain brand. This association can occur in the form of certain thoughts and images associated with a brand, and when thinking about the Image of others (Sangadji & Sopiah, 2013) Meanwhile, (Prawira and Yasa 2013) Brand Image is the perception and belief of a large set of brand associations that come to the mind of every consumer. Diputra et al., (2021) stated that Brand Image has a positive impact on customer satisfaction. Brand Image is an inherent representation or image in the consumer's mind. If consumer perception of the company's Brand Image is positive, the level of consumer satisfaction will increase. On the other hand, consumers' satisfaction will decrease if the Brand Image is considered bad. Therefore, an effective strategy in introducing a brand is important. The first step is to build a positive Brand Image in the minds of consumers. With a positive Brand Image, the brand will be famous and Cindy Seftya Rahma, Lailatul Farida 177 popular as a brand that provides the best quality. This positive image will be the main consideration for consumers in choosing the products they buy. However, it is not always the brand image that influences customer satisfaction, as the results of research conducted  state that brand image has no effect on customer satisfaction. This can happen because customer expectations also play an important role. If expectations are too high as a result of the brand image that is built, then there is a risk of dissatisfaction if the product or service received does not meet those expectations. Furthermore, consumer satisfaction can be influenced by price factors. Price, according to the explanation (Kotler 2022) , is the amount of money that must be paid by consumers to obtain a product or service. More broadly, price also includes all the value that consumers value in benefiting from owning or using the product. Research by Prabowo (2020), which is titled Price as one of the variables shows a positive influence on consumer satisfaction as a bound variable. The same thing is also found in research conducted, which states that the simultaneous test (F test) shows that price, as one of the variables, significantly influences customer satisfaction. In addition, the results of the partial test (t-test) also show that individual prices significantly influence customer satisfaction. However, the research conducted (Putra et al. 2023) stated that price cannot have a significant influence on consumer satisfaction. Although consumers prefer products at low prices, this does not necessarily bring satisfaction among consumers. Some consumers do not get satisfaction because they have different points of view, so the level of satisfaction among consumers is not evenly distributed with price as a benchmark. In addition, service is also one of the factors that may influence consumer satisfaction. Practical needs include value that is perceived through a physical form that can be seen by the customer. Superior service makes customers or consumers feel appreciated. Superior service is the act of serving customers with a friendly, precise, and fast attitude. Superior service prioritizes customer satisfaction and considers customers as partners. According to (Alhanani and Santoso 2023) Excellent Service, it has an influence on customer satisfaction because customer satisfaction is a feeling of joy or disappointment that arises when someone compares the performance of the product (or result) he feels with his expectations. Therefore, there is excellent service provided by a person to another person who is able to meet and even exceed the expectations of the person who receives the service. However, according to (Baiti, Saroh, and Hardati 2020) Excellent Service, it has no influence on consumer satisfaction because consumers prefer to see the products they feel rather than the services they provide. Consumer Satisfaction is the level of consumer feelings after comparing a performance or perceived result with their expectations, according to (Danang 2012) Consumer satisfaction is influenced on three levels. (1) If the performance is far from expectations, customers will be disappointed. (2) if the performance meets customer expectations, the customer will be satisfied, and (3) if the performance exceeds customer expectations, the customer will be very satisfied and happy. With the difference in the results of previous research that has been carried out, namely product quality, price, brand image and excellent service on customer satisfaction, the researcher wants to confirm the results of the research again by conducting a re-research by changing the American Journal of Economic and Management Business Vol. 3 No. 7 July 2024 178 object and location of the research, namely using the city of Malang chosen as the research site because the city of Malang is one of the cities that has a very high population density. According to information obtained from the Central Statistics Agency (BPS) of Malang City, the population of this city is dominated by Generation Z with a percentage of 25.44%, followed by the millennial generation, which reaches 25.21% of the total population. Table 1. Number of Population in Malang City in 2023 No. Districts in Malang City Population 1. Kedungcage 209.372 2. Breadfruit 196.860 3. Klojen 93.990 4. Blimbing 182.851 5. Lowokwaru 847.182 Source: Central Statistics Agency 2023 The table above shows the number of residents in each sub-district in Malang City in 2023. Kedungkandang District has a population of 209,372 people, while Sukun District recorded 196,860 people. Klojen District has 93,990 people, Blimbing District has 182,851 people, and Lowokwaru District has the largest population with 847,182 people. With this population density, the need for drinking water is a top priority. Based on data from (BPS 2023) the majority of the main sources of drinking water for the people of Malang City are Branded Bottled Water/Refillable Water with a percentage of 43.63%, Plumbing Water 33.37% and the rest are wells. The research aims to comprehensively investigate how product quality, price, brand image, and excellent service collectively contribute to consumer satisfaction with Aqua products in Malang City. Specifically, it seeks to determine the individual impacts of product quality, pricing strategies, brand perception, and the quality of customer service on consumer satisfaction levels. By conducting a case study focused on Aqua products in Malang City, the study intends to provide insights into the relative importance of each factor in shaping consumer satisfaction within the local market context, thereby contributing to a deeper understanding of consumer preferences and behaviors in relation to bottled water products. RESEARCH METHODS This research uses a quantitative method based on the philosophy of positivism, with the aim of investigating a specific population or sample. The research process involves collecting data using questionnaires, observations, or experiments, which are then statistically analyzed to test the hypothesis that has been formulated. Quantitative methods emphasize the collection of concrete data, such as numerical data or variables that can be measured objectively (Sugiyono, 2019). The object of this research is consumers of Aqua brand mineral water products in Malang City, East Java, which was chosen as the location of the research because it has a wide market potential and a significant population for these products. The primary data source in this study is primary data Cindy Seftya Rahma, Lailatul Farida 179 obtained directly from respondents through the distribution of questionnaires, allowing researchers to observe and record the answers to the research object directly (Sugiyono, 2019). The population of this study is consumers of Aqua products domiciled in Malang City. Based on Supriyanto & Ekowati (2019) and Sugiyono (2018), a population is defined as a collection of subjects or objects that have special characteristics that can be investigated. This study considers the population of Aqua consumers as an infinite population because the number cannot be known for sure. The research sample is a small subset of the population that is systematically selected. According to Ferdinand, the sample size needed in this study is 240 respondents, calculated based on the number of indicators used (24 indicators x 10). The data collection technique used is a survey using a questionnaire as a research instrument, which is disseminated online through Google Forms to make it easier for respondents to fill in. The sampling technique used combines probability sampling and non-probability sampling techniques, with the criteria of respondents who have bought Aqua products at least 2-3 times, are 16-50 years old, and live in Malang City. Data analysis was carried out using Structural Equation Modeling (SEM) based on Partial Least Squares (PLS) and tested using the SmartPLS version 4 program. This analysis includes the evaluation of the outer model to measure the validity and reliability of the model, as well as the evaluation of the inner model to describe the relationship between latent variables. Convergent validity is measured using a loading factor, while the validity of discrimination is measured by cross-loading. Reliability was tested using composite reliability and Cronbach's Alpha. The inner model was evaluated using the R-Square value and the path coefficient, and hypothesis testing was carried out by looking at the t-statistical value of the bootstrapping procedure in SmartPLS software (Ghozali & Latan, 2015; Abdullah & Hartono, 2015). With this approach, the research is expected to provide an objective and accurate picture of the characteristics of Aqua consumers in Malang City and the factors that influence their purchase decisions. RESULT AND DISCUSSION Outer Model The outer model is used to assess its validity and reliability. The validity test measures the confidence that the research instrument can measure the object being studied. In contrast, the reliability test measures the consistency of the measuring instrument in measuring the concept and the consistency of the respondent in responding to the research instrument (Abdillah & Hartono, 2015). Validity Konvergen (Convergent Validity) The convergent validity test correlates the item score (component score) with the construct score, which then produces a loading factor value. The loading factor value is said to be high if the components or indicators are correlated more than 0.70 (Ghozali, 2015). Table 2. Convergent Validity Test Results American Journal of Economic and Management Business Vol. 3 No. 7 July 2024 180 X1 X2 X3. X4 And. information X1.1 0,952 Valid X1.10 0,935 Valid X1.11 0,946 Valid X1.2 0,968 Valid X1.3 0,965 Valid X1.4 0,955 Valid X1.5 0,960 Valid X1.6 0,962 Valid X1.7 0,955 Valid X1.8 0,926 Valid X1.9 0,963 Valid X2.1 0,962 Valid X2.10 0,974 Valid X2.2 0,959 Valid X2.3 0,966 Valid X2.4 0,970 Valid X2.5 0,977 Valid X2.6 0,965 Valid X2.7 0,965 Valid X2.8 0,960 Valid X2.9 0,969 Valid X3.1 0,946 Valid X3.2 0,968 Valid X3.3 0,961 Valid X3.4 0,949 Valid X3.5 0,962 Valid X3.6 0,956 Valid X3.7 0,951 Valid X3.8 0,971 Valid X4.1 0,960 Valid X4.10 0,953 Valid X4.11 0,940 Valid X4.12 0,959 Valid X4.2 0,945 Valid X4.3 0,957 Valid X4.4 0,958 Valid X4.5 0,952 Valid X4.6 0,956 Valid X4.7 0,955 Valid X4.8 0,952 Valid Cindy Seftya Rahma, Lailatul Farida 181 Source: Processed SMART PLS 4 It is done by calculating the correlation between the construct and the latent variable. The loading factor of each construct indicator is used to test the validity of convergence. A value above 0.7 means that it is acceptable in empirical research (Abdullah & Hartono, 2015). Discriminant Validity The validity test of discrimination is carried out through cross-loading to find out whether the construct has adequate discrimination, namely by comparing the loading value of the intended construct to be greater than the loading value of other constructs. So that the research data can be said to have good discriminatory validity when the correlation value of the indicator to the construct is higher than the correlation value of the indicator with other constructs. The results of the validity test of discrimination are as follows: Table 3. Discriminant Validity Test Results X1 X2 X3. X4 And. X1.1 0,952 0,109 0,018 -0,005 -0,041 X1.10 0,935 0,129 -0,014 -0,026 -0,002 X1.11 0,946 0,107 -0,008 0,000 -0,008 X1.2 0,968 0,131 0,006 -0,025 -0,047 X1.3 0,965 0,126 0,006 0,000 -0,028 X1.4 0,955 0,119 0,009 0,027 -0,059 X1.5 0,960 0,132 0,024 -0,002 -0,051 X1.6 0,962 0,137 0,019 -0,012 -0,030 X1.7 0,955 0,119 0,027 0,020 -0,044 X1.8 0,926 0,115 -0,021 0,019 0,015 X1.9 0,963 0,102 -0,005 -0,002 -0,031 X2.1 0,099 0,962 -0,007 0,076 -0,046 X2.10 0,143 0,974 -0,012 0,092 -0,029 X2.2 0,146 0,959 -0,042 0,060 -0,037 X2.3 0,142 0,966 -0,030 0,068 -0,039 X2.4 0,146 0,970 -0,047 0,045 -0,010 X4.9 0,957 Valid Y.1 0,970 Valid Y.2 0,950 Valid Y.3 0,966 Valid Y.4 0,930 Valid Y.5 0,964 Valid Y.6 0,964 Valid Y.7 0,949 Valid Y.8 0,953 Valid Y.9 0,950 Valid American Journal of Economic and Management Business Vol. 3 No. 7 July 2024 182 X2.5 0,110 0,977 -0,014 0,086 -0,043 X2.6 0,126 0,965 -0,041 0,045 -0,010 X2.7 0,102 0,965 -0,049 0,041 -0,029 X2.8 0,121 0,960 -0,014 0,060 -0,034 X2.9 0,114 0,969 -0,007 0,072 -0,017 X3.1 0,008 -0,040 0,946 -0,005 -0,069 X3.2 0,038 -0,001 0,968 0,016 -0,122 X3.3 0,022 -0,009 0,961 -0,027 -0,146 X3.4 0,010 -0,027 0,949 -0,011 -0,127 X3.5 0,016 -0,025 0,962 0,000 -0,107 X3.6 -0,016 -0,042 0,956 -0,024 -0,098 X3.7 0,003 -0,020 0,951 -0,012 -0,161 X3.8 0,034 -0,041 0,971 0,018 -0,105 X4.1 -0,012 0,087 -0,046 0,960 -0,058 X4.10 0,009 0,073 0,000 0,953 -0,078 X4.11 0,008 0,067 -0,003 0,940 -0,088 X4.12 0,007 0,023 0,014 0,959 -0,083 X4.2 0,016 0,050 0,019 0,945 -0,093 X4.3 0,009 0,070 0,014 0,957 -0,113 X4.4 0,016 0,084 -0,018 0,958 -0,064 X4.5 -0,001 0,079 -0,018 0,952 -0,097 X4.6 -0,018 0,079 -0,027 0,956 -0,100 X4.7 0,029 0,075 -0,009 0,955 -0,101 X4.8 0,001 0,059 -0,014 0,952 -0,039 X4.9 -0,044 0,063 -0,009 0,957 -0,122 Y.1 -0,060 -0,015 -0,097 -0,106 0,970 Y.2 -0,016 -0,080 -0,143 -0,075 0,950 Y.3 -0,045 -0,040 -0,138 -0,117 0,966 Y.4 -0,049 -0,019 -0,112 -0,091 0,930 Y.5 -0,041 0,001 -0,134 -0,102 0,964 Y.6 -0,065 -0,024 -0,108 -0,095 0,964 Y.7 -0,042 -0,044 -0,106 -0,096 0,949 Y.8 -0,057 -0,053 -0,115 -0,084 0,953 Y.9 -0,035 -0,031 -0,143 -0,064 0,950 Source: Processed SMART PLS 4 The above result is indicated by cross-loading between the indicator and the construct. The construct is higher than the correlation of the construct with other block indicators by more than 0.7. Construct Reliability Unreliable data cannot be passed on for further processing, as the results may be biased. A Cindy Seftya Rahma, Lailatul Farida 183 measurement instrument is considered reliable if it produces stable and consistent results over time. Data reliability testing was carried out by examining Cronbach's Alpha values. If the reliability coefficient of Cronbach's Alpha of a questionnaire is >0.70, it indicates that the individual's answers to the statement are stable and consistent over time, which indicates a reliable instrument. Table 4. Construct Reliability Test Results Cronbach's alpha Composite reliability (rho_a) information X1 0,991 0,997 Reliable X2 0,992 1,021 Reliable X3. 0,987 1,007 Reliable X4 0,991 1,004 Reliable And. 0,988 0,990 Reliable Source: Processed SMART PLS 4 The composite reliability value above produces all constructs very well if > 0.70 so it can be concluded that the construct indicator is reliable or meets the reliability test. Meanwhile, Cronbach's Alpha value can be said to be reliable because of the value of >0.6. Thus, it can be concluded that all constructs are reliable. First-order confirmatory Factor Analysis Table 5. AVE Test Results Cronbach' s alpha Composite reliability (rho_a) Composite reliability (rho_c) Average variance extracted (AVE) X1 0,991 0,997 0,991 0,909 X2 0,992 1,021 0,993 0,935 X3 0,987 1,007 0,989 0,918 X4 0,991 1,004 0,992 0,909 And. 0,988 0,990 0,989 0,912 Source: Processed SMART PLS 4 In this measurement, it can be seen that the value of the loading factor is > 0.70, meaning that the preparation indicator is valid. If the convergent validity is met, it will be found that the loading coefficient of the indicator value is a loading factor above 0.70. When the measure of discriminant validity is met, the measurement results show that the square root value of the AVE is greater than the Corel. Inner Model R-Square Table 6. R-Square Test Results R-square R-square adjusted American Journal of Economic and Management Business Vol. 3 No. 7 July 2024 184 And. 0,029 0,013 The R-Square value above shows a weak model with a value below 0.25, which is 0.029 as a result of a weak model (Ghozali and Latan, 2015). This means that of all the variables studied, only 2.9% have an influence, and the rest are explained by other variables that are not examined in this study. Uji Hipotesis Hypothesis testing is carried out by comparing the statistical t-value with the t-table value. In this case, the t-table value is 1.98. If the statistical t-value is greater than the t-table value (1.98), then there is a significant influence between the variables. Conversely, if the statistical t-value is smaller than the t-table value of 1.98, then there is no significant influence between the variables. Table 7. Hypothesis Test Results Origina l sample (O) Sample mean (M) Standard deviation (STDEV) T statistics (|O/STDEV|) P values X1 -> Y. -0,042 -0,031 0,088 0,479 0,632 X2 -> Y. -0,027 -0,025 0,076 0,354 0,723 X3. -> Y. -0,129 -0,133 0,064 2,032 0,042 X4 -> Y. -0,096 -0,101 0,074 1,292 0,197 Based on the data of Table 7 above, shows that the four hypotheses proposed by the researcher, can be explained as follows: 1. H1: Product quality cannot have a significant effect on consumer satisfaction, with a P value of 0.632> 0.5, then it is concluded that H1 is rejected 2. H2: Price cannot have a significant effect on consumer satisfaction. with a P value of 0.723> 0.5, it is concluded that H2 is rejected 3. H3: Brand Image can have a significant effect on consumer satisfaction. with a P value of 0.042 < 0.5, it is concluded that H3 is accepted 4. H4: Excellent service cannot significantly affect consumer satisfaction. With a P value of 0.197> 0.5, it is concluded that H4 is rejected. Discussion The Effect of Product Quality on Consumer Satisfaction The first hypothesis in this study states that product quality affects consumer satisfaction. However, the results of this study show that product quality cannot have a significant effect on consumer satisfaction because the P value is 0.632> 0.5, and it is concluded that H1 is rejected. The quality of AQUA's products has been very standardized and consistent, so consumers consider it normal and no longer a significant differentiating factor. In a highly competitive market, product quality may no longer be the main differentiator as consumers pay more attention to Cindy Seftya Rahma, Lailatul Farida 185 aspects such as product innovation and sustainability (Prahitaningtyas et al., 2023). Finally, consumer expectations for the quality of AQUA products are already very high, so quality improvement no longer has a significant impact on their satisfaction because it is in accordance with their basic expectations. The results of this study are in line with the research conducted by (Putra, Hamdun, and Subaida 2023) which states that product quality is not able to have a significant impact on consumer satisfaction. This is due to various different perceptions from consumers regarding the level of satisfaction they have. The Effect of Price on Consumer Satisfaction The second hypothesis in this study states that price affects consumer satisfaction. However, the results show that price cannot have a significant effect on consumer satisfaction. If the P value is 0.723> 0.5, then it is concluded that H2 is rejected. Expensive prices can create the perception that AQUA does not provide value that matches their spending, especially if they find a competitor's product that is more affordable. Additionally, consumers who are highly price-sensitive may feel burdened with additional costs, which ultimately affects their satisfaction with the product. The results of this study are in line with the research conducted, which (Putra et al. 2023) stated that price cannot have a significant influence on consumer satisfaction. Although consumers prefer products at low prices, this does not necessarily bring satisfaction among consumers. Some consumers do not get satisfaction because they have different points of view, so the level of satisfaction among consumers is not evenly distributed with price as a benchmark. The Influence of Brand Image on Consumer Satisfaction The third hypothesis in this study states that brand image has an effect on consumer satisfaction. The results of this study show that brand image can have a significant effect on consumer satisfaction because the P value is 0.042 < 0.5, so it is concluded that H3 is accepted. A strong brand image reflects the trust and credibility that AQUA has built over the years, making consumers feel more satisfied because they use trustworthy products. Second, AQUA may have positive associations in consumers' minds, such as health, freshness, and quality, which create a positive emotional experience and increase their satisfaction. In addition, a good brand image often results in high brand loyalty, where loyal consumers tend to be more satisfied because they have an emotional connection and preference for the brand. This result is in line with research conducted by Istiqomah et al. (2023), which states that brand image has an influence on consumer satisfaction. The Effect of Excellent Service on Consumer Satisfaction The fourth hypothesis in this study states that Service excellence affects consumer satisfaction. However, the results show that Service Excellence cannot significantly affect consumer satisfaction. This can be seen from the P value of 0.197> 0.5. Therefore, it is concluded that H4 is rejected. Aqua consumers will mostly not experience much direct interaction with customer service due to the wide distribution of products and ease of access, so the service aspect is not the main factor in determining their satisfaction. The results of this study are in line with the research American Journal of Economic and Management Business Vol. 3 No. 7 July 2024 186 conducted by (Baiti, Saroh, and Hardati 2020). Excellent Service, has no influence on consumer satisfaction because consumers prefer to see the products they feel rather than the services they provide. CONCLUSION Based on the research and discussion, several conclusions can be drawn. First, product quality, despite its high standardization and consistency in AQUA products, does not significantly influence consumer satisfaction, as it is perceived as a normal attribute. 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