Vol. 5, No. 12, December 2024
E-ISSN: 2723 - 6692
P-ISSN: 2723 - 6595
http://jiss.publikasiindonesia.id/
Journal of Indonesian Social Sciences, Vol. 5, No. 12, December 2024 3364
KEYWORDS
ABSTRACT
Online Customer Reviews;
Consumer Satisfaction; eWOM;
MSMEs; Digital Marketing
The development of digital technology has changed the way
businesses interact with consumers, especially through online
customer reviews. These reviews are an important element in the
consumer decision-making process by providing social proof that
strengthens the perception of the product or service. This study aims
to analyze the influence of online customer reviews on consumer
satisfaction in the culinary MSME sector in the city of Bandung. The
research method uses a descriptive quantitative approach with a
purposive sampling technique involving 150 active respondents on
social media. Data was collected through a questionnaire with the
Likert scale. The results of the validity and reliability test show that
the research instrument meets quantitative research standards.
Correlation analysis showed a positive and significant relationship
between online customer reviews and consumer satisfaction with a
correlation coefficient of 0.569. Positive reviews increase consumer
confidence, while negative reviews decrease buying interest
although the impact can be minimized through quick and
professional responses from sellers. In conclusion, online customer
reviews play an important role in creating consumer satisfaction, so
companies need to manage these reviews effectively to maintain
customer loyalty in the digital age.
Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Introduction
In modern marketing, consumers are increasingly intelligent and critical in choosing products
or services (Davenport et al., 2020; Huang & Rust, 2021). They not only rely on information from
traditional advertising, but also look for references from sources that are considered more credible,
such as influencers and fellow consumers. The development of digital technology has drastically
changed the way businesses interact with consumers. In recent decades, social media has evolved
into one of the main marketing channels for many companies, both large and small, that are trying to
reach a wider market. One of them is that online customer reviews also have a crucial role in the
consumer decision-making process. These reviews are considered more objective because they come
from the direct experience of product users, so they can affect consumer perception of the quality of
the product or service. Positive reviews can increase consumer confidence to buy, while negative
The Impact of Online Customer Reviews on Enhancing Consumer
Satisfaction
Roro Arinda Reswanti
Universitas Langlangbuana, Indonesia
Email: roro.arind[email protected]
Correspondence: [email protected]m
*
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reviews can have a huge impact on purchasing decisions and customer loyalty (Cheung & Thadani,
2012; Kotler et al., 2020).
A form of communication between companies or online stores, consumers must also be given a
forum to provide feedback or reciprocity in the form of reviews of the products that have been
purchased. Responses made by consumers are commonly called consumer reviews or Online reviews.
According to Nainggolan and Purba (2019) the Review, it is part of the Electronic Word of Mouth
(eWOM), which is the direct opinion of a person and not an advertisement. Reviews are one of several
factors that determine a person's purchase decision. Online customer reviews for consumers today
are not only a consideration option in buying a product, but also able to describe an expectation for a
product (Mu’nis & Komaladewi, 2020). Online reviews are a form of electronic word of mouth
(eWOM) that refers to content posted by users online or on third-party websites (Fauzi & Lina, 2021).
Based on the explanation of the definitions above, it can be concluded that an Onliner Costumer
Review (OCR) is a review that contains information related to a product or service, based on an
evaluation of a personal experience that can be positive or negative after the consumer has done or
felt the product or service itself.
Customer satisfaction is defined as a subjective feeling experienced by a customer in response
to a product or service that has been consumed. According to Chandra et al. (2019), consumer
satisfaction or dissatisfaction is a consumer response to the evaluation of perceived
nonconformity/disconfirmation between previous expectations (or other performance norms) and
the actual performance of the product perceived after its use. According to Indahningwati (2019),
further elaborates that consumer satisfaction is a feeling of happiness or disappointment that arises
after comparing the performance or results of a product against the expected performance or results.
Specifically, if the performance falls below expectations, consumers experience dissatisfaction; if the
performance meets expectations, consumers feel satisfied; and if the performance exceeds or exceeds
expectations, consumers feel very satisfied or happy. In summary, customer satisfaction can be
defined as the customer's subjective evaluation of their feelings regarding a product, service, or
service provided by a seller, which can be classified as either satisfactory or unsatisfactory, depending
on whether the customer's expectations were met or exceeded.
In the context of consumer satisfaction, online customer reviews have a significant
contribution. Influencers often have a strong emotional connection with their followers, which allows
them to influence consumer perception and experience directly (Maulana et al., 2021; Saputra, 2021).
Meanwhile, customer reviews provide social proof that helps potential consumers in evaluating
products or services. Therefore, it is important to understand how these two elements work
synergistically in creating better consumer satisfaction.
This research aims to analyze the relationship between influencer marketing and online
customer reviews in increasing consumer satisfaction. With a focus on MSME products, this research
is expected to contribute to the development of more effective marketing strategies for micro, small,
and medium enterprises in the digital era.
Research Methods
Research Approach
This research approach applies a descriptive quantitative approach. The type of quantitative
research was chosen because this study aims to measure the relationship between independent
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variables and dependent variables using numerical data and statistical analysis techniques with a
double correlation model.
Research Focus
The focus of this research is focused on 2 (two) variables consisting of 1 (one) free variable and
1 (one) bound variable. One independent variable is online Customer Reviews (X1). As a bound
variable, namely Consumer Satisfaction (Y). The relationship between these two variables is shown
in the following figure:
Figure 1. Relationship between Research Variables
Research population and sample
The population of this study is consumers who have purchased products or services from
MSMEs who use influencer marketing and receive online customer reviews, both through social
media and e-commerce platforms. The population is targeted at MSMEs in the culinary sector in the
city of Bandung.
The research sample will be taken using a purposive sampling technique, where respondents
are selected based on certain criteria, such as consumers who are active on social media and have
been exposed to influencer marketing and online reviews. The expected sample size is at least 150
respondents, given the need for robust and representative statistical analysis.
Research Instruments
This study uses a questionnaire as a data collection instrument. The questionnaire was
compiled on a Likert scale of point 1 (strongly disagree) to point 5 (strongly agree), in which
respondents were asked to indicate their level of agreement with statements related to the research
variables.
Hypothesis
There are 2 (two) hypotheses that are provisional answers to problems that will be proven to
be true through this research, which are as follows:
H1: There is a positive and significant correlation between online customer reviews and consumer
satisfaction.
Results and Discussion
Instrument Test Results
The data used in this study is primary data obtained by distributing questionnaires to
consumers who have conducted online research in the marketplace and to find out the influence of
Y
Customer
Satisfaction
X2
Review Customer
Online
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each variable. The following are the results of the validity and feasibility test of the research
questionnaire items before analyzing the results of the next research.
A. Validity Test
Validity Test Results on X Variable Data Instrument
The results of the validity test on variable x, namely online customer reviews on consumers
using SPSS, can be shown in table 1. The following:
Table 1. Results of the Validity Test of the Variable Instrument Online Customer Review
Item
r-Table
X1.1
0,300
X1.2
0,300
X1.3
0,300
X1.4
0,300
X1.5
0,300
X1.6
0,300
X1.7
0,300
X1.8
0,300
X1.9
0,300
X1.10
0,300
Results of Validity Test on Variable Y Data Instrument
The results of the validity test on the Y variable, namely Consumer Satisfaction using SPSS, can
be shown in table 2. The following:
Table 2. Results of the Validity Test of the Consumer Satisfaction Variable Instrument
Item
r-Table
Y1.1
0,300
Y1.2
0,300
Y1.3
0,300
Y1.4
0,300
Y1.5
0,300
Y1.6
0,300
Y1.7
0,300
Y1.8
0,300
Y1.9
0,300
Y1.10
0,300
B. Reliability Test
The reliability test of the instrument was carried out on all valid items using Cronbach's Alpha
values. Testing can be done in whole or per item. An instrument item is declared reliable if the value
of Cronbach's Alpha > 0.6. The following are the results of the global reliability test of each variable
analyzed using SPSS.
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Reliability test results on X Variable Data Instrument
The results of the reliability test on variable x, namely online customer reviews on consumers
using SPSS, can be shown in table 3. The following:
Table 3. Reliability Statistics
Reliability Statistics
Cronbacn’s Alpha
N of Items
.816
10
Based on the results of SPSS, table 3 of reliability coefficients is seen as cronbach's alpha 0.816
> 0.60. It can be concluded that the construct of the question, which is the dimension of the variable
x, is reliable.
Reliability test results on Variable Y Data Instrument
The results of the reliability test on the Y variable, namely Consumer Satisfaction using
SPSS, can be shown in table 4. The following:
Table 4. Reliability Statistics
Reliability Statistics
Cronbacn’s Alpha
N of Items
.801
10
Based on the results of SPSS, the reliability coefficients table is seen as cronbach's alpha 0.801
> 0.60. It can be concluded that the construct of the question, which is the dimension of the variable
x, is reliable.
Data Normality Test Results
Data normality testing was carried out using the Kolmogorov-Smirnov method with the help of
SPSS software. The data is said to be normally distributed if the Significance (Sig) value > 0.05. The
following are the results of the data normality test.
Table 5. Test of Normality,
One-Sampel Kolmogorov-Smirnov Test
Unstandardiz ed
Residual
N
90
Normal Parameters
a,b
Mean
.0000000
Std. Deviation
.35834315
Most Extreme Differences
Absolute
.091
Positive
.091
Negative
-.070
Test Statistic
.091
Asymp. Sig. (2 -tailed)
.066
c
a. Test distribution is Normal.
b. Calculated from data.
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c. Lilieforrs Significance Correlations.
Based on table 5, the results of the Kolmogorov-Smirnov One-Sample Test obtained a
significance value (Asymp. Sig. 2-tailed) of 0.066. The value is greater than the significance threshold
of 0.05 so it can be concluded that the data is normally distributed.
Figure 1. Online Customer Review Variable Scatter Diagram (X)
Based on the scatter chart image, the data shows a distribution pattern that is consistently
scattered around a regression line or diagonal that represents a normal distribution. The distribution
of data that is not too far from the diagonal line reinforces the conclusion that the data tends to follow
a normal distribution pattern.
1. Results of Descriptive Analysis
The descriptive discussion in this study aims to describe the condition of the variables and
identify the highest and lowest perception values. This data is used as a basis for formulating
conclusions and recommendations. The following are the results of the recapitulation of the
descriptive analysis.
Table 6. Results of Descriptive Analysis of Both Variables
Variable
N
Mean
Category
Online
Customer
Reviews
90
3,2
Quite Good
Customer
Satisfaction
90
3,5
Good
Based on the results of the descriptive analysis, the Online Customer Review variable has an
average value (Mean) of 3.2, which is included in the Quite Good category. Meanwhile, the Customer
Satisfaction variable has an average value of 3.5, which is included in the Good category. These results
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show that respondents' perception of online customer reviews is quite positive, and the level of
customer satisfaction is also considered to be in the good category.
2. Results of Correlative Analysis
In this study, Pearson Product Moment correlation analysis was employed to evaluate the
relationship between the independent variables studied, namely the online customer review variable
and consumer satisfaction. This analysis aims to measure the strength and direction of the
relationship between variables before proceeding to the further analysis stage. The correlation value
of each variable is the basis for assessing the extent to which these variables are interconnected, thus
providing an initial overview of the dynamics between variables in this study. The ensuing results,
delineated in Table 7, provide a comprehensive overview of the observed interconnections between
the variables in this study.
Table 7. Correlations
Correlations
PRO
KK
Spearman’s rho
PRO
Correlation Coefficient
1.000
.569
**
Sig. (1-tailed)
.
.000
N
90
90
KK
Correlation Coefficient
.569
**
1.000
Sig. (1-tailed)
.000
.
N
90
90
**
, Correlations is significant at the 0.01 level (1-tailed)
Based on the results in table 7 Correlations, a Sig value of 0.000 < 0.05 was obtained, which
means that there is a relationship between Online Customer Reviews and Consumer Satisfaction. The
magnitude of the Correlation Coefficient is 0.569, so that when consulted the interpretation of the r
value (correlation) in the table, it has a fairly strong (moderate) and unidirectional relationship level
because the value is positive. The positive relationship between these variables can be translated as
if the Online Customer Review is one unit, the meal will be followed by an increase in the amount of
Consumer satisfaction by 0.569 units.
Based on the results of data analysis and hypothesis testing in this study, the results were
obtained that Online Customer Reviews have a significant impact on Customer Satisfaction. The
magnitude of the impact that this variable contributes to customer satisfaction is 32%, which is a
combination of direct and indirect impacts. Online customer reviews are important for companies to
pay attention to in making online sales because consumers cannot check a product directly. This is in
line with the research of Zhang et al. (2023) which showed a significant influence of positive reviews
on consumer trust and satisfaction. In contrast, negative reviews lower trust by 65%, with 30% of
consumers canceling a purchase after reading a negative review. These results are supported by the
findings of Park and Lee (2023) which show the influence of negative reviews in decreasing consumer
confidence. In addition, 81% of respondents in this study felt more comfortable when sellers
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responded quickly to negative reviews, in line with research conducted by Chen et al. (2024) which
highlighted the importance of seller responsiveness in increasing consumer satisfaction.
Conclusion
The results of this study show that positive reviews play a role in strengthening consumer trust
and creating higher expectations for products or services. On the other hand, negative reviews have
the potential to damage trust and reduce buying interest, although overall ratings are still good.
However, the seller's prompt and professional handling of negative reviews can restore consumer
perception and increase their satisfaction. Therefore, an effective review management strategy is an
important element in maintaining and increasing customer loyalty in the digital era.
Suggestions Sellers or business owners can take advantage of positive reviews by highlighting
customer testimonials on various platforms, such as social media and official websites, to build trust
and strengthen brand image. Additionally, providing incentives such as discounts, reward points, or
vouchers to customers who are willing to leave a review can increase the number of positive reviews.
To manage negative reviews, sellers need to respond quickly, professionally, and provide concrete
solutions, such as apologies and corrective steps. Handling negative reviews well not only helps
minimize their impact, but it can also improve relationships with customers.
Business actors are also advised to take advantage of technology such as social listening tools
or review monitoring software to monitor customer reviews in real-time, so that they can respond
more effectively. In addition, customer reviews, especially those that contain criticism, should be used
as a source of input to improve the quality of products and services. Constructive criticism can help
sellers identify areas that need improvement. With these measures, consumer satisfaction can be
improved, and customer loyalty to the product or service can be maintained in an increasingly
competitive business competition.
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