Chapter 4 Results

Chapter Four: Analysis and Findings 4.1: Introduction The results from statistical analysis are presented in this chapter together with the measurement of accuracy. This includes the reliability of data collection instrument and determining whether data normality assumption for parametric methods such as correlation and multiple regressions were violated in the study. The demographic profile of respondents and statistical analysis for answering the research questions are logically presented for consequential interpretation. 4.2: Measurement of Accuracy 4.2.1: Internal Reliability Test Table 4.1 shows the variable items and Chronbach’s alpha for internal reliability for the measurement scales for each study variable. There are five variable each with five items Table 4.1: Chronbach’s Alpha Variable No. Of Items Chronbach’s Alpha Service quality 5 0.76 Interactivity 5 0.91 Convenience 5 0.73 Customization 5 0.84 Security 5 0.65 Mean Value 25 0.78 The results indicate that all scales used to measure all the variables of study except security have sufficient internal consistency. Accordingly, the interactivity component of m CRM had the most reliable scales/items with 0.91 Chronbach's Alpha followed by customization at 0.84 while customization and convenience scales had .84 and .73 on Chronbach’s Alpha. However, measures of security components did not have adequate internal consistency hence the scales were not reliable. However, deleting one item from variable increased the Alpha to 0.72, hence making it a reliable measure. Overall, all the variables used to examine the effects of m CRM on customer satisfaction and competitive advantage are reliable with a mean Chronbach’s Alpha of 0.78 which is higher the recommended value of 0.70. In conclusion, the questionnaire was a reliable measure of the effects of m CRM on customer satisfaction and competitive advantage. Content and face validity of the questionnaire was ensured through the research and CRM experts. The experts reviewed the questions to ensure they can capture the correct information for answering the research questions. Furthermore, most questions were sourced from prior studies where possible to improve the validity of the questionnaire instrument. Some questions were based on the product/service quality “RATER” model (tangibility, reliability, responsiveness, assurance and empathy) that has been used in numerous studies. The draft instrument was eventually subjected to pilot study to Samsung customers in the neighbouring country Qatar to identify any ambiguity in the questions or statements as well as proper use of grammar. The results from the pilot study were used to improve the contents of the questionnaire to guarantee valid and consistent results. 4.2.2: Normality Testing Data normality is an assumption for parametric methods such as regression and correlation analysis. Testing for data normality was done using Shapiro Wilk statistics which applies to a small data between 50 and 2000 respondents. The study variables with a p-value greater than 0.05 are said to have a normal distribution whereas those with a p-value less than 0.05 do not have a normal distribution. The results indicate that all variables in the study have normal distribution hence did not violate normality assumption. Therefore, it was appropriate to apply parametric tests such as multiple regressions model, correlation analysis and ANOVA to test the impact of m CRM adoption by Samsung to boost customer satisfaction and competitive advantage. Table 4.2: testing normality of research data Variable Statistics d.f Sig. Service quality 0.158 5 0.267 Interactivity 0.563 5 0.519 Convenience 0.257 5 0.434 Customization 0.694 5 0.247 Security -0.175 5 0.558 4.3: Demographic Variables The major demographic attributes believed to influence m CRM satisfaction were analyzed and since the selection was through probability random sampling techniques, the proportion of customers in the survey are generalized to the actual Samsung customers. The results indicate that surveyed male was more than female at 54 and 46 per cent respectively. Age-wise, the results suggest that Samsung customers are middle-aged adults concentrated in the 26-35 and 36-45 age brackets with 27 and 23 per cent respectively. The least number of customers are those aged above 55 years with 14% representation in the survey as participants Concerning the marital status, the results suggest that most customers are married with 47 per cent representation in the survey followed by unmarried singles with 30% representation. The least represented group was widowed with 7 per cent while separated or divorced were 16 per cent in the survey. Education-wise, the primary level had the least representation, and this is proportional to their representation in the general population. However, college graduates had the most representation in the study accounting for 49% followed by postgraduate and high school graduates with 25 and 23 per cent respectively. Regarding the occupational status of Samsung customers, the formal sectors account for the majority of Samsung customers while others had the least representation in the survey with just 8 per cent. Finally, those in the informal sector and those owning business accounts for 31 and 26 per cent of Samsung customers respectively. The summarized demographic results are shown in Table 4.3 below. Table 4.3: Analysis of Demographic profile of respondents Variable Item % Gender Male 54 Male 46 Age bracket 15-25 19 26-35 27 36-45 23 46-55 17 Over 55 14 Marital Status Single 30 Married 47 Widowed 7 Separated/Divorced 16 Education Primary level 3 High school 23 College/University 49 Post-graduate 25 Occupation Formal 35 Informal 31 Own business 26 Others 8 Description of Samsung’s m CRM technology Table 4.1 shows the description of m CRM technology as used by Samsung from the participant’s view in terms based on the customization, interactivity, service quality, security, and convenience. The results Table 4.4: Participants’ description of RM technology Description Frequency % The m CRM technology has enhanced interaction with customers 235 94 Samsung’s Service quality has improved using m CRM technology 191 76 The m CRM technology has fostered customization of services 217 87 The m CRM technology has enhanced the security of customer information 184 74 The m CRM technology has enhanced convenience in handling of customers 208 83 The study results have confirmed that all components of m CRM technologies benefit Samsung. Accordingly, 94% of the participants in the survey concurred that m CRM technology fosters close and frequent interaction between Samsung personnel and customers. The use of m CRM technology in fostering quality service was seconded by 76% of the customers in the survey while 87% agreed that m CRM promotes customization of services. The customers further confirmed that m CRM technology makes it possible for Samsung to secure customer information and also generated convenient ways of handling customers. 4.4.1: Impact of m CRM on Customer Satisfaction It was essential to examine the impact of m CRM components on the satisfaction of customers. The study participants were asked to rate their opinion on the impact of each component on customer satisfaction on a scale of 1-5 where 1 indicates strong disagreement and 5 indicate string agreement with statement. Table 4.4: Impact of m CRM on Customer Satisfaction Components N Mean Std Error S.d Service quality through m CRM improves customer satisfaction 250 3.095 0.167 1.267 The m CRM interactivity leads to higher customer satisfaction 250 4.361 0.715 1.519 The convenience of m CRM improves the satisfaction of customers 250 2.873 0.744 0.834 The customization of m CRM generates higher customer satisfaction 250 3.787 0.417 1.247 Security features of m CRM generates customer satisfaction 250 3.516 0.658 0.558 The results have all m CRM components have a mean value greater than 2.5 (medium mean for neutral) suggesting the positive contribution towards customer satisfaction. Interactivity has the most positive impact of customer satisfaction as shown by the highest mean value (mean =4.361, std error =0.715, and s.d = 1.519). This is followed by m CRM customization (mean = 3.787), security (mean = 3.516) and service quality (mean = 3.095). Therefore, survey respondents agreed that m CRM generates customer satisfaction. The findings are similar to earlier research by Lee, Tsao and Chang (2015) which concluded that mCRM tools provide the most efficient ways to improve customer satisfaction. Further to that, Arcand et al (2017) also noted that mCRM tools are vital for enhancing customer experiences by availing diverse points of view to organizations. A study by Sampaio et al (2017) also observed that increased adoption of mCRM mobile messaging creates a more personalized and unique communication with their clients, which in turn enhances their experiences. However, consistent with Bilgihan, Kandampully and Zhang (2016) findings, this is attained if an organization builds its m-CRM systems to enhance customer satisfaction by customizing the firm’s behaviours based on the information gathered through these systems about their customers. Deng et al (2010) investigation into mobile instant messages (MIM) found that m-CRM platform generates clientele satisfaction. He further found that the M-CRM avenue had helped firms to enhance customer satisfaction and loyalty levels by 3% and concluded that M-CRM platforms, and especially MIM’s enhance customer gratification through improved trust levels among their clients. Therefore, as recommended by San-Martín, Jiménez and López-Catalán (2016), the m CRM provides Samsung with a platform for improving customer gratification improvements through acquisition of customer-related information for designing suitable responses to clientele desires. 4.4.2: Impact of m CRM on Competitive Advantage It was essential to examine the impact of m CRM components on the competitive advantage of Samsung in the telecom industry. The respondents were asked to identify the extent to which m CRM contributes to the competitive advantage of Samsung in the market. The results indicate 90% support for substantial contribution, 10% for partial contribution, and 0% for the little contribution of m CRM to a firm's competitiveness in the market. Overall, these results are consistent with an earlier study linking m CRM and clientele gratification by Kibeh (2013), which found that m CRM tools enhance firm's competitive advantages achieved through improved clientele satisfaction levels among telecom businesses in Kenya. These findings underscore the significant role played by m CRM tools by Samsung to create a competitive advantage over rival firms in the Telecom industry. Figure 4.1: Contribution of m CRM of competitive advantage The study further asked the participants to rate the impact of each component on the competitiveness of Samsung in the market on a scale of 1-5 where 1 = strong disagreement and 5 = strong agreement with the statement. The results from the current study suggest that components of m CRM namely service quality, customization, and security have a mean value greater than 2.5 (medium mean for neutral) an indication of positive contribution towards competitive advantage of the company. The service quality gained through CRM tools in Samsung has the greatest impact on the firm’s competitive advantage as shown by the highest mean value (mean =4.387, and std error = 0.647, and s.d = 1.977). The customization through m CRM had a strong positive correlation with competitive advantage as shown by mean = 3.917, standard error1.025, and standard deviation 0.471. Similar findings were found with interactivity (mean = 3.715; std error = 0.725; s.d = 0.605) while convenient handling of customers via the m CRM tools has positive effects (mean value = 3.370; std error =0914; and s.d = 0.154). The security component of m CRM has the least but positive impact on the firms competitiveness (mean = 3.012; std error = 0.718; and s.d = 0.368). Therefore, the current study has confirmed that indeed m CRM makes a substantial contribution to the competitiveness in the market. Table 4.5: Impact of m CRM on Competitive Advantage Components N Mean Std Error S.d Service quality through m CRM improves efficiency and competitiveness in the market 250 4.387 0.647 1.977 The m CRM interactivity leads to efficiency and competitiveness of Samsung in the market 250 3.715 0.725 0.605 The convenience through m CRM tools improves efficiency in handling customers and the firm's competitiveness 250 1.370 0.914 0.154 The customization through m CRM application has improved the competitive advantage of the firm 250 3.917 1.025 0.471 Security features are enhanced in m CRM tools thus generating customer trust and confidence in the company 250 3.012 0.718 0.368 Relating customization to earlier studies, the findings of the current study are consistent with Cummins, Peltier, and Dixon (2016), which indicates that m CRM technologies facilitate individualized, dynamic, and personalized views depending on previous purchases and current/previous preferences. Accordingly, M-CRM tools facilitate tailoring of products and services to meet customer needs and preferences, leading to situations where customers are fulfilled with their purchase and the attached consumption experiences. A study by Oh and Kim (2017) indicated that m CRM tools are fundamental in generating quality service to customers because the accord organizations sufficient room to provide their clients with services/products that exceed their target client’s expectations. The customization effects of m CRM on customer satisfaction marry that of Ali, Dey and Filieri (2015) study. Hsu and Lin (2008) investigated the opportunities that M-CRM presents for companies to enhance their competitiveness. The study concluded that M-CRM supports customer satisfaction strategies by bringing in the desired changes in their CRM structures eventually culminating in the desired competitive advantage increments. Overall, the study results are consistent with some studies on the linkage between CRM and the competitive advantage of the company. 4.5: Inferential Statistics 4.5.1: Impact m CRM on Customers Satisfaction Chi-Square test is used to determine whether the relationship between categorical variables is statistically significant. It is believed that various components of m CRM are the predicting variables of customer satisfaction. These variables include interactivity, customization, customer data security, service quality, and convenience as well as the outcome variable; customer satisfaction are categorical variables hence the use of chi-square. The chi-square test is relevant in testing the study hypothesis on the relationship between m CRM and customer satisfaction. The level of significance is set at 5% and hence any significance value less than 0.05 is considered significant. The tests results indicate that all the predicting variables are statistically significant as shown by value and very high chi-square values Table 4.6: Chi-Square Test for Hypothesis Testing Variables Customer Satisfaction Chi square values Sig. (2 tailed) Interactivity 41.265 0.01 Customization 105.696 0.00 Service quality 97.875 0.00 Data security 41.543 0.00 Convenience 98.321 0.00 Accordingly, the interactivity component has chi-square value = 41.265 and p values 0.01, hence the correlation between interactivity through m CRM and customer satisfaction is significant. The current study thus confirmed the hypothesis that m CRM interaction is positively and significantly related to customer satisfaction. Since the p values are less than 0.05, these results confirm the hypothesis that m CRM interactivity is positively and significantly impacts customer satisfaction Customization component has chi-square value = 105.696 and p-value 0.00 implying a strong significant relationship between m CRM customization and customer satisfaction. Therefore, with p-value less than 5% value, we confidently accept the hypothesis that m CRM customization has positive and significant impacts on customer satisfaction is confirmed by the current study. The chi-square value for service quality through m CRM tools was 97.875 and p-value was 0.000 which reveal a significant relationship between customization and customer satisfaction. With a very low p-value less than 5%, we are 95% confident that CRM service quality is positively and significantly correlated with customer satisfaction. Therefore, we reject the null hypothesis that m CRM service quality is not correlated with customer satisfaction in telecom industry The convenience brought by m CRM tools had a chi-square value of 98.321 and p-value 0.000, an indication of a strong positive relationship between the convenience variable and satisfaction of clients. With such a low p-value less than 5%, we are 95% confident that convenience gained through m CRM tools is directly and significantly correlated with customer satisfaction. We, therefore, reject the null hypothesis that no significant relationship exists between m CRM convenience and customer satisfaction. Customer data security via the m CRM was also significant with chi-square value 41.543 with a p-value of 0.04. The p-value for the security variable is less than the recommended 5% margin of error; hence we can confidently conclude that the relationship between these variables is significant. Therefore, we confidently reject the null hypothesis that security via the m CRM tools is not significantly related to customer satisfaction in telecom market. In summary, all the predicting variables of customer satisfaction are statistically significant, hence m CRM has a significantly positive impact on customer satisfaction in the UAE telecom market. Therefore, Samsung must strive to ensure that m CRM tools can to gain higher interactivity and customization, secure customer data, improve convenience, and gain quality service to gain a higher level of customer satisfaction. 4.5.2: Impact m CRM on Firm’s Competitive Advantage Chi-Square test is used to determine whether the relationship between categorical variables is statistically significant. It is believed that various components of m CRM are the predicting variables for a firm's competitive advantage. These include interactivity, customization/personalization, customer data security, service quality, and convenience as well as the outcome variable; customer satisfaction are categorical variables hence the use of chi-square. The chi-square test is relevant in testing the study hypothesis on the relationship between m CRM and a firm's competitive advantage. The level of significance is set at 5% and hence any significance or p-value less than 0.05 is considered statistically significant. The test results indicate that all the variables except convenience and data security have a significant relationship with the competitive advantage of Samsung in the telecom market. This as shown by p-value less than 5% and very high chi-square values as summarized in table 4.7 below. Table 4.7: Chi-Square Test for Hypothesis Testing Variables Customer Satisfaction Chi square values Sig. (2 tailed) Interactivity 29.562 0.02 Customization 43. 941 0.04 Service quality 79.587 0.03 Data security 14.354 0.47 Convenience 89.132 0.16 According to the study results, the interactivity component has chi-square value = 29.562 and p values 0.01. The low p-value less than 5%, this is a confirmation that m CRM interaction is positively and significantly related to competitive advantage. We are therefore 95% confident that these variables are significant hence the null hypothesis that there is is no significant relationship exists between interactivity and m CRM is rejected. Therefore, interaction with customers through m CRM tools is paramount in gaining competitive advantage in the telecom market. Customization component has chi-square value = 43.941 and p-value 0.04 implying a strong significant relationship between m CRM customization and competitive advantage. Therefore, with p-value less than 5% value, we reject the null hypothesis that m CRM customization has no positive and significant impact on competitive advantage. We are 95% confident that customization through m CRM has a significantly positive effect in competitiveness of Samsung in the market. The chi-square value for service quality through gained through the implementation of m CRM tools was 79.587 and p-value was 0.03 which reveal that a significant and positive relationship exists between customization and competitive advantage. With a very low p-value less than 5%, we are 95% confident that CRM service quality is positively and significantly correlated with a firm's competitive advantage. Therefore, we reject the null hypothesis that m CRM service quality is not correlated with the competitiveness of Samsung in the UAE telecom industry The convenience in dealing with customers through m CRM tools had a chi-square value of 89.132 and p-value 0.47, indicating that the relationship between convenience and competitive advantage is not statistically significant. With such a high p-value greater than 5%, we are 95% confident that convenience gained through m CRM tools is not correlated with the competitiveness of Samsung in the market. We, therefore, accept the null hypothesis that no significant relationship exists between m CRM convenience and competitive advantage. Customer data security via the m CRM was also not significant with the firm’s competitiveness. This variable had a chi-square value 14.354 with p-value of 0.16. The p-value for the security variable is greater than the recommended 5% margin of error; hence we can confidently conclude that the relationship between these variables is not statistically significant. Therefore, we confidently accept the null hypothesis that the security of customer data gained via the m CRM tools is not significantly related to the competitiveness of Samsung in the telecom market. In summary, customization, service quality, and interactivity variables have a significant relationship with the competitive advantage of Samsung. However, security and convenience variables have no significant relationship with the competitiveness of Samsung in the telecom market. 4.6: Regression Analysis 4.6.1: Impact m CRM on Customers Satisfaction The multiple regression analysis was conducted with customization, service quality, convenience, security, and interactivity as the predictor variable of customer satisfaction. This was important is in assessing whether these variables through m CRM are statistically significant in predicting customer satisfaction as the outcome variable of the study. The regression results in table 4.8 have R squared of 49% implying the model as a whole account for 49% changes in customer satisfaction. This means m CRM components contribute 49% to changes in customer satisfaction hence their adoption is paramount in fostering customer satisfaction. With significance value at 0.00, the regression model as a whole is significant. Table 4.8: Regression model Model Unstandardized Coefficients t Sig. B Std. Error (Constant) 0.657 0.116 4.349 0.001 Interactivity 1.152 0.659 1.924 0.008 Customization 2.891 1.223 9.979 0.003 Convenience 1.525 0.442 3.658 0.009 Data security 0.351 0.716 0.107 0.026 Service quality 0.477 1.196 2.924 0.001 F (5, 250) = 23.356; Sig (F) =.000; R Square = .432; Adjusted R Square = .491; Dependent Variable: Customer Satisfaction The model coefficient in table 4.8 indicate that all variables; interactivity, customization, service quality, convenience, and data security have a positive coefficient; hence they have a positive impact on customer satisfaction. The result is consistent with the chi-square test as shown by all variables having a significant correlation with the satisfaction of customers. Accordingly, customization and convenience have the highest coefficient at 2.891 and 1.525 respectively while interactivity, service quality, and data security have 1.152, 0.477, and 0.351 respectively. Regarding significant, the p values for interactivity, customization and service quality are 0.008, 0.003, and 0.001 respectively. Convenience and data security have an insignificant impact on customer satisfaction as shown by p values 0.009 and 0.026 respectively. These findings imply that m CRM can better improve customer satisfaction if they foster interactivity, customization, convenience, data security, and service quality. Therefore, m CRM tools should be designed to improve these attributes if they seek to gain a high level of customer satisfaction. The model from the results is thus formulated as: Y = 0.657+1.152X1+2.891X2+1.525X3+0.351X4+0.477X5 + e Where Y is the customer satisfaction, X1, X2, X3, X4, X5 represent interactivity, customization, convenience, data security, service quality and 0.657 is the Y-intercept. The y-intercept of 0.657 implies a change in customer satisfaction if all independent variables are zero. Similarly, when data security, service quality, customization, and convenience are held constant, there will be a change of 1.152 in customer satisfaction due to a unit change in interactivity. Accordingly, when all the other variables are held constant, a unit increase in customization leads to a 2.8 change in the level of customer satisfaction while a unit change in convenience generates 1.525 changes in the level of customer satisfaction. Similarly, when interactivity, service quality, customization, and convenience are held constant, there will be a change of 0.351 in the level of customer satisfaction due to a unit increase in data security while a unit increase in service quality will generate a change of 0.477 in the level of customer satisfaction. Hypothesis Testing The test results lead to the acceptance or rejection of the null hypothesis. Hypothesis Test results H01: The relationship between m CRM interactivity and customer satisfaction is not significant Rejected H02: There is no significant relationship between m CRM customization and customer satisfaction Rejected H03: The relationship between m CRM convenience and customer satisfaction is not significant Rejected H04: The relationship between m CRM data security and customer satisfaction is not significant Rejected H05: There is no significant relationship between m CRM quality service and customer satisfaction Rejected Conclusively, all components m CRM have positive contribution to customer satisfaction. The study results have confirmed that interactivity, customization, convenience, data security, and service quality components of m CRM have a significant contribution to the satisfaction of customers in the telecom market. Therefore, m CRM is an important strategy for improving the satisfaction of Samsung customers in the market 4.6.2: Impact m CRM on Competitive Advantage The multiple regression analysis was conducted with customization, service quality, convenience, security, and interactivity as the predictor variable of competitive advantage. This was important is in assessing whether these variables through m CRM are statistically significant in predicting the firm's competitiveness as the outcome variable of the study. The regression results in table 4.9 have R squared of 42% implying the model as a whole account for 42% changes in the level Samsung’s competitiveness in the market. This means m CRM components contribute up to 42% of changes in the competitive advantage of Samsung hence their adoption is paramount in fostering its business competitiveness. With significance value at F = 0.00, the regression model as a whole is significant. Table 4.9: Regression model Model Unstandardized Coefficients t Sig. B Std. Error (Constant) 0.756 0.146 4.349 0.006 Interactivity 2.514 0.579 1.924 0.001 Customization 3.752 1.113 9.979 0.000 Convenience 0.934 0.572 3.658 0.109 Data security 0.841 1.716 0.107 1.026 Service quality 0.774 0.196 2.924 0.004 F (5, 250) = 27.652; Sig (F) =.000; R Square = .394; Adjusted R Square = .428; Dependent Variable: Customer Satisfaction The model coefficient in table 4.9 indicate that all variables; interactivity, customization, service quality, convenience, and data security have a positive coefficient; hence they have a positive impact on competitive advantage of the company. The result is consistent with the chi-square test as shown by all variables except security and convenience having a significant correlation with the level of a firm's competitiveness. Accordingly, customization and interactivity have the highest coefficient at 3.752 and 2.514 respectively while convenience, service quality, and data security have .934, 0.774, and 0.841 respectively. Regarding the significance of the variables, the p values for interactivity, customization and service quality are 0.000, 0.000, and 0.004 respectively. However, convenience and data security have insignificant impact on customer satisfaction as shown by p values 0.109 and 1.026 respectively. These findings imply that m CRM tool can better improve customer satisfaction if they foster interactivity, customization, and service quality. However, security and convenience have positive but insignificant effects on customer satisfaction. The model from the results is thus formulated as: Y = 0.756+2.514X1+3.752X2+0.934X3+0.841X4+0.774X5 + e Where Y is competitive advantage, X1, X2, X3, X4, X5 represent interactivity, customization, convenience, data security, service quality and 0.756 is the Y-intercept. The Y-intercept of 0.756 implies a change in competitive if all independent variables are held constant. Similarly, when data security, service quality, customization, and convenience are held constant, there will be a change of 2.514 in the firm’s competitiveness due to a unit increase or decrease in the level of interactivity. Accordingly, when all the other variables are held constant, a unit increase in customization leads to a 3.752 change in the level of competitive advantage while a unit change inconvenience from m CRM generates a change of .934 in the firm's competitiveness in the telecom market. Similarly, when interactivity, service quality, customization, and convenience are held constant, there will be a change of 0.841 in the level of competitive advantage resulting from a to a unit increase in data security while a unit increase in service quality will generate a change of 0.774 in the level of competitive advantage of the firm in telecom market Hypothesis Testing The test results lead to the acceptance or rejection of the null hypothesis. Hypothesis Test results H01: The relationship between m CRM interactivity and customer competitive advantage is not significant Rejected H02: There is no significant relationship between m CRM customization and competitive advantage Rejected H03: The relationship between m CRM convenience and competitive advantage is not significant Accepted H04: The relationship between m CRM data security and competitive advantage is not significant Accepted H05: There is no significant relationship between m CRM quality service and competitive advantage Rejected Conclusively, the study results have confirmed that interactivity, customization, and service quality components of m CRM have a significant contribution to the competitive of customers in the telecom market. However, despite their positive contribution to the firm’s competitiveness in the telecom sector, convenience and data security of m CRM tools, their contributions are insignificant. Therefore, Samsung can gain competitive in the market by ensuring that m CRM tools facilitate interactivity, customization, and foster quality service 4.7: Qualitative Analysis The interviews with key customers of Samsung were conducted to unravel insightful information for the study. A total of 10 customers were drawn based on the volume of purchases from Samsung. This information was complemented by information from previous studies on the subject of study. 4.7.1: Components of m CRM technology The first objective of the study was to identify innovative components of m CRM technology that generate customer satisfaction and competitive advantage and several studies were reviewed. A study by Sapolsky et al (2018) and Olatokun and Ojo (2016) carried out a study relying on theoretical frameworks that focused on innovative mCRM components such as security of customer data and interactivity. Some studies on CRM such as Aziza, Oubrich and Søilen (2015) and Soltani & Navimipour (2016) went a step further to include the aspect of tracking customer interactions and managing customer accounts. Nonetheless, presents the need for CRM approaches allow organizations to keep track of their interactions with clients. Another study by Zameer et al (2015) observed that firms can enhance customer experiences based on convenience, security, service, customization, and interactivity. Therefore, the m CRM components unravelled through secondary data include interactivity, customization, security, convenience, and service quality. Interview with customers was conducted to obtain their view on how m CRM components impact customer satisfaction and firm’s competitiveness in the market. Accordingly, all interviewees acknowledged that adoption and implementation of m CRM program enhances the levels of process efficiency. When probed further to identify areas improved by m CRM tools, the collection of customer data emerged as the main theme followed by customization of business services especially in marketing messages to the needs of customers. 4.7.2: Impact of m CRM on Customer Satisfaction The second objective sought to determine the impact of m CRM components on customer satisfaction. Consistent with quantitative analysis, the interview results indicate that m CRM tools have improved customer satisfaction. Here are some quotes from customers on the overall benefits of m CRM technologies on customer satisfaction. ‘I am so happy to Samsung because they respond quickly to my inquiries, complaints and suggestions. When I place an order, the response comes promptly and able to track the movement of my orders through mobile applications’. The messaging I get from customers are always in tandem with my needs and they make it easier to make a purchase decision This statement from a customer is a clear indication of how m CRM applications have improved service delivery to customers. The target marketing through m CRM is aimed at meeting the needs of customers thus enhances the satisfaction of customers Customization Regarding the impact of customization on customer satisfaction, it was noted from the interviews that m CRM facilitates customization of an organization's behaviours inconsistent with clientele experiences foster customer satisfaction. Consequently, customization makes influence consumers into developing positive perceptions and attitudes towards the business in appreciation to the sensitivity of the company towards the interests and aspirations of the customers. When probed to identify key areas where Samsung has customized services to the needs of customers, marketing messaging emerged as the main theme. Therefore, the provision of customized, superior value services generates a high level of customer satisfaction. This assertion by interviewees supports the earlier study by Sampaio et al (2017) who observed that increased adoption of mCRM mobile messaging creates a more tailored and unique communication with their customers to enhance positive experiences. However, this can only be attained if an organization designs its m-CRM systems to customize the firm’s behaviours based on the information gathered through these systems about their customers Interactivity M - CRM interactivity is depicted through the sustenance of two-way communications between marketers and customer segments (Wang, 2016). The interviews examined how this interactivity impacts the satisfaction of customers and hence competitive advantage. Most respondents revealed 'obtaining additional information from businesses relating to their interests and expectations as the main benefit of frequent and close interaction through m CRM tools. Quoting some scripts from customers: The continuous interaction enhances the envisaged value proposition of the business as it develops a better understanding of the expectations of customers. "I often obtain the information I need from Samsung through a mobile phone. However, some messages can be annoying especially if they are sent repeatedly”. The variety of interaction was sought, and the most prevalent include social network interaction via m CRM strategy, the provision of m provision messages via the phone, and direct sending of messages to customers. However, some customers had issues with frequent communication especially the promotion messages claiming some are annoying. It is hence vital for marketers to watch out to avoid annoying messages by sending only customized and relevant messages to customers. Convenience Convenience is another component of m CRM believed to generate customer satisfaction and a firm's competitiveness. It was noted by Chikweche and Fletcher (2013) that m CRM tools simplify the service by making it user-friendly in a way that improves accessibility by customers. In assessing the benefits, some interviewees acknowledged that m CRM programs are automated thereby add customer convenience enhancing the levels of efficiency in service delivery. The researcher probed further to identify m CRM tools that facilitate convenience in services. The mobile applications that promote mobile payments rather than the use of cash or debit and credit cards emerged as the leading tool. Mobile banking was has become an important tool for paying for goods and services. Security The interviews indicate that data security through m CRM tools develops trust and confidence with marketers thus enhancing their satisfaction and loyalty to the brand. These sentiments were echoed across the participants interviewed. Similar observations were noted from the review of secondary. For instance, Deng et al (2010) found that the M-CRM tools enhance customer satisfaction and loyalty levels by 3% and concluded that M-CRM platforms, and especially MIM’s enhance customer gratification through improved trust levels among their clients. The author further notes that various processes of the mCRM combine to enhance the quality of relationships with customers thus contributing to greater levels of customer satisfaction and the firm’s competitiveness. Therefore, as Saleem and Rashid (2011) observed, organizations seeking to secure higher levels of clientele satisfaction should focus on designing M-CRM systems and applications that enhance customers trust 4.7.3: Impact of Customer Satisfaction on Competitive Advantage Customer satisfaction is believed to impact the firm's competitiveness in the market. It was important to examine different ways through which these variables are interconnected. Customer loyalty and retention emerged as the common theme with most participants stating the higher customer satisfaction translates to brand loyalty and retention of customers. In view of Zablah et al (2016) a satisfied customer often sticks to a particular company longer and this loyalty has significant influences on the profitability of the company. Further to that, loyal customers are less sensitive to price, hence the company can charge premium pricing to gain a higher profit margin than competitors without fear of losing customers. The second theme was repeat purchase from satisfied customers which improves sales and financial performance of the firms. Word of mouth promotion was also noted from the interview script, which leads to increase customer and market size for the company. This assertion is consistent with Magatef and Tomalieh (2015) findings indicating that satisfied clients would often recommend the brans/products/services to their peers, family, friends, and relatives through word of mouth. Hussain (2016) viewed customer gratification as a formidable competitive tool because the kind of competitive advantages that stem from clientele fulfilment is not easy for other competing firms to duplicate. It was further noted that m CRM tools contribute towards customer satisfaction and hence competitive advantage of the company. However, work and thorough planning are needed to turn customer satisfaction into a competitive advantage.