DOI: 10.
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Building Marketing Communication Mix to Increase Consumer Loyalty Oppo Mobile Phones of Students of STIE Dharma Putra Pekanbaru Indriaty STIE Dharma Putra.
Pekanbaru.
Indonesia Email: indriatywibowo@gmail.
Yudho Wibowo STIE Dharma Putra.
Pekanbaru.
Indonesia *Email: yudhowibowo@stiedharmaputra.
Bayu Sedih Nanda Ria STIE Dharma Putra.
Pekanbaru.
Indonesia Email: bayu_snr@gmail.
ARTICLE INFO :
Keywords:
Marketing Communication Mix.
Consumer Loyalty.
Oppo Mobile Phones.
--------------------------Article History :
Received :2024-09-28 Revised : 2024-11-03 Accepted :2024-12-18 Online :2024-12-20 ABSTRACT This study aims to determine the effect of marketing communication mix on the loyalty of Oppo mobile phone consumers among STIE Dharma Putra Pekanbaru students.
The marketing communication mix variables consist of Advertising.
Sales Promotion.
Personal Selling.
Public Relations, and Direct and Digital Marketing.
The population in this study were STIE Dharma Putra Pekanbaru students and used a judgmental sampling technique totaling 42 respondents.
The results of the study showed that the variables of advertising.
Sales promotion.
Personal Selling.
Public Relations, and Direct and digital marketing had a partial effect on Oppo Mobile Phone Consumer Loyalty and the Marketing Communication Mix Variable had a simultaneous effect on Consumer Loyalty.
The results also showed that the contribution of the marketing mix influenced Oppo Mobile Phone Consumer Loyalty by 8%, the rest was influenced by other variables not examined in this INTRODUCTION The use of mobile phones in Indonesia has increased in recent years and has established itself as one of the largest smartphone usage shares in the world after China.
India, and the United States.
Various mobile phone manufacturers present in Indonesia in Indonesia originating from China.
South Korea, and America, including brands that are widely circulated and occupy a large market share are Samsung.
Xiaomi.
Oppo.
Vivo.
Iphone.
Realme.
In a mobile phone market research.
Canalis officially released its latest report regarding the condition of the mobile phone market share in Southeast Asia, including Indonesia in the third quarter of 2024.
In the period calculated from July to September 2024.
Canalys placed the Oppo mobile phone brand in first place in Indonesia with a market share of around 22%.
Then followed by the Xiaomi brand with a market share of 19%.
Transsion .
combined brand of Infinix.
Tecno, and Ite.
with a market share of 18%.
Samsung which has a market share of 16%, and Vivo at 16 percent.
532 Page This is an open access article under the CC BY- SA license Corresponding Author : Yudho Wibowo DOI: 10.
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According to data from DataReportal, the number of active smartphone users in Indonesia has increased consistently every year.
In 2015, there were around 54 million active users.
This number jumped drastically to 209.
3 million in 2023.
(Goodstats, 2.
The very high increase in mobile phone usage among Indonesian people has opened up opportunities for new brands to gain market share and has led to increasingly tight competition for both old and new brands in the mobile phone industry market.
Figure 1.
Graph of Mobile Phone Users in Indonesia Source: Goodstats .
Marketing communications are the means by which firms attempt to inform, persuade, and remind consumers directly or indirectly about the products and brands they sell.
In a sense, they represent the voice of the company and its brands.
they are a means by which the firm can establish a dialogue and build relationships with consumers.
By strengthening customer loyalty, they can contribute to customer equity (Kotker & Keller, 2.
Marketing communications also work by showing consumers how and why a product is used, by whom, where, and when.
Consumers can learn who makes the product and what the company and brand stand for, and they can become motivated to try or use it.
Marketing communications allow companies to link their brands to other people, places, events, brands, experiences, feelings, and things.
They can contribute to brand equity by establishing the brand in memory and creating a brand image as well as drive sales and even affect shareholder value.
(Kotker & Keller, 2.
Marketing communication activities in every medium contribute to brand equity and drive sales in many ways: by creating brand awareness, forging brand image in consumers' memories, eliciting positive brand judgments or feelings, and strengthening consumer loyalty.
(Kotker & Keller, 2.
Loyalty Status Marketers usually envision four groups based on brand loyalty status (Kotker & Keller.
Hard-core loyals: Consumers who buy only one brand all the time Split loyals: Consumers who are loyal to two or three brands Shifting loyalty: Consumers who shift loyalty from one brand to another Switchers: Consumers who show no loyalty to any brand The purpose of this study is to determine the influence of marketing communication mix variables .
sales promotion.
personal selling.
public relation.
direct and digital marketin.
on the loyalty variable of Oppo cellphone users among students of STIE Dharma Putra Pekanbaru.
533 Page This is an open access article under the CC BY- SA license Corresponding Author : Yudho Wibowo DOI: 10.
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LITERATURE RESEARCH
Loyalty Loyalty a commitment to rebuy or repatronize a preferred product or service.
(Kotker & Keller, 2.
Customers who are considered loyal to a brand have the willingness to endorse and recommend the brand to their friends and family.
Loyalty was often defined as retention and repurchase.
In the connectivity era, loyalty is ultimately determined as the willingness to advocate a brand.
A customer might not need to continuously repurchase a particular brand .
g, due to a longer purchase cycl.
or might not be able to .
g, due to unavailability in certain But if the customer is happy with the brand, he or she will be willing to recommend it even when not currently using it.
The new customer path should be aligned to this new definition of loyalty.
(Kotler.
Kartajaya & Setiawan, 2.
Marketing Communication Mix Marketing communications mix: The specific blend of promotion tools that the company uses to engage consumers, persuasively customer value, and build customer communicate relationships.
(Armstrong et al.
Marketing communications mix consists of the specific blend of advertising, public relations, personal selling, sales promotion, and direct marketing tools that the company uses to engage consumers, persuasively communicate customer value, and build customer relationships.
The five major promotion tools are defined as Advertising: Any paid form of nonpersonal presentation and promotion of ideas, goods, or services by an identified sponsor.
Sales promotion: Short-term incentives to encourage the purchase or sale of a product or service.
Personal selling: Personal customer interactions by the firm's sales force for the purpose of making sales and building customer relationships.
Public relations: Building good relations with the company's various publics by obtaining favorable publicity, building up a good corporate image, and handling or heading off unfavorable rumors, stories, and events.
Direct and digital marketing: Engaging directly with carefully targeted individual consumers and customer communities to both obtain an immediate response and build lasting customer Conceptual Framework Figure 2.
Conceptual Framework Advertising (X.
Sales promotion (X.
Personal selling (X.
Loyalty (Y) Public relations (X.
Direct and digital marketing (X.
Source: Research Data .
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METHOD
Population and Sampling Methods A population element is the individual participant or object on which the measurement is taken.
It is the unit of study.
A population is the total collection of elements about which we wish to make some inferences.
(Cooper and Schindler, 2.
In the research conducted, the population was all STIE Dharma Putra Pekanbaru A sample is a subset of the population.
It consists of some members selected from it.
In other words, some, but not all, elements of the population form the sample.
(Sekaran and Bougi, 2.
Sample a group of cases, participants, events, or records consisting of a portion of the target population, carefully selected to represent that population (Cooper and Schindler, 2.
This research uses a nonprobability sample type of purposive sampling with the Judgment sampling type which occurs when a researcher selects sample members to conform to some criterion.
The criteria used were Oppo user students, totaling 42 students.
Research Variables And Measurement This research used quantitative methods.
Quantitative research attempts precise measurement of In business research, quantitative methodologies usually measure consumer behavior, knowledge, opinions, or attitudes.
Such methodology answer questions relate to how much, how often, how much, when, and who.
(Cooper and Schindler, 2.
The purpose of this method is to determine the influence that occurs between independent variables on dependent variables.
Researchers summarize the measurement of research variable data using a Likert The Likert scale is designed to examine how strongly subjects agree or disagree with statements on a five-point scale (Strongly Disagree.
Disagree.
Neither Agree nor Disagree.
Agree, and Strongly Agre.
(Sekaran and Bougi, 2.
Table 1.
Measurement of Variables No Variable Scale of measurement Loyalty Likert scale Advertising Likert scale Sales promotion Likert scale Personal Selling Likert scale Public Relations Likert scale Direct and digital marketing X 5 Likert scale Source: Research data, 2024 For this study we used descriptive ststistical and Multiple Regression, by first testing the research data instrument, namely testing the validity of the data and the reliability of the data.
Descriptive Statistical Statistics such as frequencies, the mean, and the standard deviation, which provide descriptive information about a set of data.
(Sekaran and Bougi, 2.
Descriptive statistical measures are used to depict the center, spread, and shape of distributions and are helpful as preliminary tools for data (Cooper, 2.
Classic Assumtion Test Also conducted a classical regression assumption test:
Normality Test According to Ghozali .
the normality test is a test that aims to determine whether the independent and dependent variables have a normal distribution or not.
This study uses the Kolmogorov Smirnov test to test the normality of the data.
In this test, if the probability is > 0.
05, the distribution of the regression model is normal and if the probability is <0.
05, the distribution of the regression model is said to be abnormal.
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Multicollinearity Test Multicollinearity test is conducted to determine whether there is multicollinearity between independent variables or not.
A good regression model should not have correlation between independent variables.
If there is correlation between variables, it is called multicollinearity.
The basis for making decisions on multicollinearity tests are: 1.
If the Tolerance value is > 0.
10 and the VIF value is < 10, it can be concluded that there is no multicollinearity.
If the Tolerance value is < 0.
10 and the VIF value is > 10, it can be concluded that there is multicollinearity.
Heteroscedasticity Test This heteroscedasticity test aims to test whether in a regression model there is inequality of variance from residuals in one observation to another.
A good regression model is one that does not have To predict whether or not heteroscedasticity occurs by looking at the scatterplot There are several provisions, namely: 1.
If there is a certain pattern, such as the existing points form a certain regular pattern, then Heteroscedasticity occurs.
If there is no clear pattern or the points are spread above and below the number zero .
on the Y axis, then there is no Heteroscedasticity or Homoscedasticity occurs.
Hypothesis Test The regression equation Y= a b 1 X 1 b 2 X 2 b 3 X 3 b 4 X 4 b 5 Information:
b 1, b 2, b 3, b 4, b 5 Loyalty Constant/Slope Coefficient regression Advertising Sales promotion Personal Selling Public Relations Direct and digital marketing t-Test Priyatno .
said that the t-test is used to test the influence of the independent or free variable (X) partially on the dependent or bound variable (Y).
The t-test testing criteria are as follows:
- If the significance value < .
Ha is accepted and Ho is rejected, meaning that the independent variable has a significant effect on the dependent variable.
- If the significance value > .
Ho is accepted and Ha is rejected, meaning that the independent variable does not have a significant effect on the dependent variable.
F Test Priyatno .
said that the F test is used to test the influence of independent or free variables (X) simultaneously on the dependent or bound variable (Y).
The F test criteria are as follows:
- If the significance value < .
Ha is accepted and Ho is rejected, meaning that the independent variables simultaneously have a significant effect on the dependent variable.
- If the significance value > .
Ho is accepted and Ha is rejected, meaning that the independent variables simultaneously do not have a significant effect on the dependent variable.
Correlation and Determination Coefficient.
The Correlation Coefficient (R) is used to determine the level of closeness or strength of the relationship between the independent variables and the dependent variables.
Used to measure the closeness of the relationship of the model used.
The coefficient of determination (R2 ) is a number that shows the magnitude of the ability of variance or distribution of independent variables that explain the dependent variable or a number that shows how much the dependent variable is influenced by the independent variable.
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RESULTS AND DISCUSSION
Descripive Respondent The research results based on respondent characteristics are summarized in the table below:
Table 2.
Descriptive Respondent Category Frequency Percentage Gender Man Woman Duration of Use < 6 months 6 Ae 12 months 12 Ae 18 months >18 months Reasons to buy Economical price Feature Durability Life style Source: Processed data .
It can be seen in the table above that the number of male respondents is greater than the number of female respondents.
Based on the length of use of Oppo cellphones above 18 months dominates with a value 2% and based on the reasons for buying Oppo cellphones, it is more based on the feature variable, which 2%, this feature that is attached to Oppo cellphones is more dominant in the camera feature.
While other reasons for buying are because of the economical price .
%), lifestyle .
%) and because of durability .
3%).
Instrument Test Validity Test.
The results of the validity test based on the results of the respondents' answers to the questionnaire are summarized in the table below.
Table 3.
Results of Research Data Validity Test
Question Items Corrected Item-Total R critical Category Correlation X 11
Valid
X 12
Valid
X 13
Valid
X 14
Valid
X 21
Valid
X 22
Valid
X 23
Valid
X 24
Valid
X 25
Valid
X 31
Valid
X 32
Valid
X 33
Valid
X 34
Valid
X 35
Valid
X 41
Valid
X 42
Valid
X 43
Valid
X 44
Valid 537 Page This is an open access article under the CC BY- SA license Corresponding Author : Yudho Wibowo DOI: 10.
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X 45
X 51
X 52
X 53
X 54
Source: Processed data .
Valid Valid Valid Valid Valid Valid Valid Valid Valid Validity testing uses the Corrected Item-Total Correlation value which is then compared with the critical R value of 0.
3 (Sugiyono, 2.
If the Corrected Item-Total Correlation value is above the critical R value, the statement item can be categorized as valid and vice versa.
From table 3 above, it can be seen that all statement items in the questionnaire are greater than 0.
3 so it can be concluded that this research data is valid.
Reliability Test Reliability testing is useful to determine whether the instrument in this case the questionnaire can be used more than once or many times which show the same results.
Reliability testing based on respondents' answers to the questionnaire that has been distributed gets the results as in table 3 below.
Table 4.
Results of Research Data Reliability Test Variables Cronbach's Alpha Critical Value Category Reliable Reliable Reliable Reliable Reliable Reliable Source: Processed data .
The reliability testing criteria can be seen from the comparison of Cronbach's Alpha value compared to its critical value of 0.
The questionnaire can be said to be reliable if the Cronbach's Alpha value is greater than 0.
6 and vice versa.
In Table 3 above, it can be seen that the overall Cronbach's Alpha value is 6 and it can be concluded that the questionnaire used in this study is reliable.
Classical Assumption Test Normality Test The normality test carried out using the Kolmogorov Smirnov analysis tool can be seen in table 4 Table 5.
Normality Test Results One-Sample Kolmogorov-Smirnov Test Unstandardized Residual Normal Parameters Mean Std.
Deviation Most Extreme Differences Absolute Positive Negative Test Statistics Asymp.
Sig.
-taile.
Test distribution is Normal.
Calculated from data.
Lilliefors Significance Correction.
This is a lower bound of the true significance.
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The results of the normality test using the Kolmogorov-Smirnov statistical test in the table above show a significance value of 0.
200, which means that this value is greater than 0.
05 and it can be concluded that the research data is normally distributed.
Multicollinearity When two or more explanatory variables move together, we say that the regression suffers from In this case, it is difficult to distinguish which variable affects the dependent variable.
Therefore, a multicollinearity test is needed to determine whether the research instrument experiences multicollinearity or not.
Table 6.
Multicollinearity Test Results Model Collinearity Statistics Tolerance VIF (Constan.
Advertising Sales promotion Personal selling Public relations Direct and digital marketing 1,749 1,895 1,845 1,499 Source: Processed data .
Based on the table above, it can be seen that all values in the tolerance column are greater than 10 and all values in the VIF column are less than 10.
So it can be concluded that the regression model is free from multicollinearity.
Heteroscedasticity The goal is to test whether in a regression model there is inequality of variance of residuals from one observation to another.
A good regression model is one in which there is no heteroscedasticity.
Figure 3.
Scatter Plot Source: Processed data .
In the image above, it can be seen that the points are spread randomly and are spread both above and below the number 0 on the Y axis and do not form certain patterns, so it can be concluded that the regression model in this study is free from heteroscedasticity.
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Multiple Linear Regression Equation Table 7.
Results of Multiple Linear Regression Coefficient Calculations Coefficients Unstandardized Standardized Coefficients Coefficients Model Std.
Error Beta (Constan.
Advertising Sales promotion Personal selling 3,524 Public relations 5,494 Direct and digital 2,522 Dependent Variable: Loyalty Source: Processed data .
Sig.
The following is the equation obtained from the results of multiple linear regression calculations using SPSS version 23:
Y = 9.
517X 1 0.
437X 2 0.
422X 3 0.
774X 4 0.
339 X 5 e Hypothesis Testing t-test The t-test is used to determine the partial significant level of the influence of the independent variable on the dependent variable.
The hypotheses presented above, namely H1 .
H2 .
H3 .
H4 and H5 , are tested using the t-test.
H 1 : Advertising has an influence on consumer loyalty to Oppo brand mobile phones.
In table 5, the significance value obtained by the advertising variable is 0.
001, this value is smaller than the alpha value .
This means that hypothesis one (H.
can be accepted or the advertising variable partially influences consumer loyalty to the Oppo brand cellphone.
H 2 : Sales promotion has an effect on consumer loyalty to Oppo brand mobile phones.
In table 5, the significance value obtained by the sales promotion variable is 0.
003, this value is smaller than 0.
This means that hypothesis two (H.
an be accepted or the promotion variable partially influences consumer loyalty to the Oppo brand cellphone.
H 3 : Personal selling has an effect on consumer loyalty to Oppo brand mobile phones.
Table 5 shows the magnitude of the significance value obtained by the personal selling variable is 006, this value is smaller than the alpha value .
This means that hypothesis three (H .
can be accepted or the personal selling variable partially influences consumer loyalty to the Oppo brand H 4 : Public relations have an influence on consumer loyalty to Oppo brand mobile phones.
In table 5, the significance value obtained by the public relations variable is 0.
000, this value is smaller than the alpha value .
This means that hypothesis four (H4 ) can be accepted or the public relations variable partially influences consumer loyalty to the Oppo brand cellphone.
H 5 : Direct and digital marketing have an influence on consumer loyalty to Oppo brand mobile phones.
Table 5 shows the magnitude of significance value obtained by direct and digital marketing is 0.
this value is smaller compared to the alpha magnitude .
This means that the five hypothesis (H.
can be accepted or the direct and digital marketing variables partially influence consumer loyalty of Oppo brand cellphones.
F Test 540 Page This is an open access article under the CC BY- SA license Corresponding Author : Yudho Wibowo DOI: 10.
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The F test basically shows whether all independent or free variables entered in the model have a joint influence on the dependent variable.
In this research model, it will answer the sixth hypothesis (H .
Marketing communication has an effect on consumer loyalty of Oppo brand cellphones.
Table 8.
F Test
ANOVA
Model Sum of Squares Mean Square Sig.
Regression 414,033 82,807 8,474 Residual 342,016 9,772 Total
756,049
Dependent Variable: Loyalty Predictors: (Constan.
Direct and digital marketing.
Sales promotion.
Public relations.
Advertising.
Personal selling Source: Processed data .
The result in table 6 of the F test in table 6 above, the magnitude of the significance value is 0.
This value is smaller than the alpha value of 0.
005, so that Hypothesis six (H6 ) can be accepted or the marketing communication variable has a simultaneous influence on consumer loyalty of the Oppo brand Correlation and Determination Coefficient The correlation coefficient in question is the magnitude of the correlation that occurs between independent variables on the dependent variable.
While the determination coefficient is intended to determine the magnitude of the contribution of independent variables on the dependent variable.
Table 9.
Multicollinearity Test Results Model Summary b Adjusted R Std.
Error of the Model
R Square Square Estimate Durbin-Watson
1,643
Predictors: (Constan.
Direct and digital marketing.
Sales promotion.
Public relations.
Advertising.
Personal selling Dependent Variable: Loyalty Source: Processed data .
The magnitude of the correlation coefficient value shown in table 7 can be seen in the R value, which is positive at 0.
The correlation that occurs in the marketing communication variable with the loyalty variable is closely positively correlated.
The magnitude of the determination coefficient value shown in table 7 can be seen in the R Square value (R ) which is 0.
This means that the contribution of the marketing communication variable is 54.
to the loyalty variable.
While the remaining 45.
2% is contributed by other variables.
not examined in this Marketing communication plays a role in maintaining consumer loyalty, in this study the results of the F test show that marketing communication has an effect on consumer loyalty of Oppo brand mobile phones.
This influence is quite large and has a positive effect, meaning that if marketing communication can be improved, consumer loyalty will also increase.
This is evidenced by the results of the correlation between marketing communication and consumer loyalty of Oppo brand mobile phones, which is closely positively correlated, also seen from the value of the determination coefficient which is quite high, reaching more than Marketing communication mix variables that shown Oppo brand mobile phones have advantages in public relations variables.
This advantage needs to be maintained and preserved through various ways in building excellent communication in managing product information and product complaints.
Then followed by the variables Advertising, sales promotion, personal selling and direct and digital marketing.
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The direct and digital marketing variables have the lowest influence on the marketing communication This can happen because the portion of advertising that is still given is greater so that it can socialize information about product advantages through major media such as television as if consumers can interact directly with the product and it is easier to form perceptions.
Therefore, the direct and digital marketing variables can be given a larger budget portion to try on the e-commerce sector within its reach in the mobile phone market by focusing more on the current generation in forming perceptions following the lifestyle patterns that are formed.
CONCLUSION
It has been proven that the loyalty of Oppo mobile phone users among STIE Dharma Putra students is influenced by the marketing communication mix using the multiple linear regression method and it is also proven that the marketing communication mix has a contribution in building and increasing the loyalty of Oppo mobile phone users.
Some things that need to be considered for further researchers are trying to do it on a wider scope.
BIBLIOGRAPHY