Methods. and Schnieder, Reichheld and Sasser, Knight, Gans, Koole, and Mandelbaum, and others.

Transcription

1 Methods The link between positive call center service and high levels of customer satisfaction has been established through numerous studies such as Genyses, Right Now Technologies, McColl and Schnieder, Reichheld and Sasser, Knight, Gans, Koole, and Mandelbaum, and others. Further, it has been established that the level of CSR job satisfaction, training and call center culture are critical to ensuring high levels of customer satisfaction. For the purposes of this study, quantitative research methods were used to measure independent and dependent variables for this study. This section reviews the population being studied, the make up of the polling group, a discussion of the instrument used, and the sources used to develop the survey tool. Subject Selection and Population Description The sample population was made up of 500 randomly selected current and past customers of XYZ Company, an online retailer that has an in-house, centralized customer service call center. The only criterion of the random selection was that each person had to have had a documented interaction with the customer service call center at some point in their relationship with XYZ Company. Of the 500 surveys distributed, 100 were completed. The gender split of the respondents was 83% male and 27% female and of that, 78% were between the ages of 25 to 54. Residentially, 76% of respondents lived in America and 24% lived outside of the United States but did not specify a country of origin. Respondents, in general, were well-educated with 70% reporting the completion of a 4-year college education. The survey tool was developed using WorldAPP s Key Survey enterprise data collection software. Flexibility of the tool allowed for intuitive question presentation based on consumer responses to core questions. This enabled the collection of deeper insights into attitudinal views

2 on the customer service experience and what drives individual perceptions of good and bad service. Instrumentation The survey instrument was developed using questions derived from the SERVQUAL service quality framework. Developed in the 1980s by Zeithaml, Parasuraman, and Berry, the SERVQUAL scale measures direct and indirect variables on customer satisfaction. Once the core base of questions was established, research topics were grouped under the following categories: CSR competence, telephone etiquette, adherence to protocol, and knowledge in relation to perceived customer satisfaction. The four groups allowed for deeper questions to be asked based on respondent answers and this helped to improve analysis of the data collected so a deeper understanding of customers, their attitudes, and perceptions about themselves and CSRs during CSR interactions could be better examined and interpreted. Data Collection Procedures A 29 question survey with up to 30 hidden sub-questions based on taker response was developed under the four categories listed above. Two days in advance of the survey being sent, an was sent by XYZ Company to the randomly selected pool letting them know a survey was coming to help provide a higher level of customer satisfaction and asking for their participation. On the third day, the survey was sent electronically to the randomly selected pool of 500 past and present customers along with a message from XYZ Company that asked, again, for their participation in collecting data on customer satisfaction. Survey participants were also assured that the confidentiality of their information was secure and no data collected would be used for anything other than the stated intent. A 10 day time frame was provided for the survey to be

3 taken and at Day 5 and Day 10; reminders were automatically generated to non-respondents to encourage participation. At the end of Day 10, the survey automatically closed and no other responses were accepted. In all, 100 current and former customers (20%) participated in the voluntary online survey. Data Analysis Descriptive statistics were used to analyze the results of the survey for central tendency and variation. The data collected by the study was analyzed using POLYSTAT statistical software. Limitations There are several customer satisfaction measures not included in the survey that could be critical to CSR employees, management, and leadership in measuring customer satisfaction. For an example, CSR training, income, and reward systems may have a direct impact on variables associated with the ability to motivate a CSR to produce higher levels customer satisfaction. This requires an internal survey mechanism as the external respondents cannot know what the true inner workings of the call center are. Two-pronged research that allows for a 360 degree view of the internal and external pressures of ensuring the delivery of high customer satisfaction provides a promising line of future research. It is assumed the respondents are being honest in their responses about their views on their interaction with a call center customer service representative. However, there are many variables that may impact the degree of honesty that cannot be controlled outside of this study. If a customer was unhappy with the company and has taken his or her business elsewhere, there could be bad feelings and the respondent could be harsher in judgment of the CSR interaction.

4 Gender was not taken into consideration in developing the questions but there could be skewing of data results based on gender and the fact that the majority of respondents were male. More research would need to be done to see if gender impacted the rate of response and the actual survey answers provided. Lastly, survey respondents were from multiple countries including the U.S. Respondent country, culture, and values were not taken into consideration in this study. In fact, foreign respondents did not supply their country of origin which makes it impossible to even compare responses based along national and international borders. Results The purpose of this research was to identify areas of concern which impact customer satisfaction in U.S based customer service call centers for online retailers. This study included a series of 5-point Likert scale questions. The ordinal scales was anchored by strongly agree and strongly disagree. Sociodemographic (e.g. age, gender, education) and other background (i.e.: years spent as a customer of XYZ Company) questions in the survey were included to validate the results of the study as well. Using descriptive statistics this data provides the following information:

5 5. As soon as I talk to an employee, I notice the employee knows me as a customer As soon as I talk to an employee, I notice that the employee knows me as their customer. Mean Standard Deviation Coefficient of Variation According to the mean table for statement 5, the mean of 2.69 implies that customers surveyed neither agree nor disagree that CSRs knew the caller as a customer. The data produced a standard deviation of and a coefficient variation of.477. The coefficient of variation shows that.447 of the data varied from the mean of This variation can be explained by a strong amount of neither agree / disagree responses. There is a moderate variation of the data because of the number of neutral responses was 29 out of 100 customers surveyed.

6 6. As soon as I talk to an employee, I notice that the employee immediately has my data at his disposal As soon as I talk to an employee, I notice that the employee immediately has my data at his disposal. Mean Standard Deviation Coefficient of Variation According to the mean table for statement 6, the mean of 2.89 implies that customers surveyed neither agree nor disagree that the CSR immediately knew the customer s on-file data and history with the company. The data produced a standard deviation of and a coefficient variation of.411. The coefficient of variation shows that.411 of the data varied from the mean of 2.89.

7 16. The employee I talk to listens well The employee I talk to listens well. Mean Standard Deviation Coefficient of Variation According to the table above, the mean of 2.53 suggests that most customers strongly agree and agree that the CSR listens well. The data produced a standard deviation of and a coefficient variation of.548. The coefficient of variation shows that.548 of the data varied from the means of This variation of.548 can be explained by the large amount of strongly agree and agree responses. 23. The company employees have the knowledge to answer my questions.

8 The company employees have the knowledge to answer my questions. Mean Standard Deviation Coefficient of Variation According to the mean table for statement 23, the mean of 2.57 implies that customers surveyed neither agree nor disagree that the CSR has knowledge needed to answer the consumer s questions. The data produced a standard deviation of and a coefficient variation of.432. The coefficient of variation shows that.432 of the data varied from the mean of This variation can be explained by a strong amount of neither agree / disagree responses. There is a moderate variation of the data because of the number of neutral responses was 34 out of 100 customers surveyed. 24. The company employees properly handle any problems that arise.

9 The company employees properly handle any problems that arise. Mean Standard Deviation Coefficient of Variation According to the table above, the mean of 1.95 suggests that most customers strongly agree and agree that the CSR they speak to properly handles any problems that arise. The data produced a standard deviation of.998 and a coefficient variation of.512. The coefficient of variation shows that.512 of the data varied from the means of This variation of.512 can be explained by the large amount of strongly agree and agree responses. 25. The company employees comply with my requests.

10 The company employees comply with my requests. Mean Standard Deviation Coefficient of Variation According to the table above, the mean of 3.26 suggests many customers (51%) disagree or strongly disagree that the CSRs comply with their requests. The data produced a standard deviation of and a coefficient variation of.417. The coefficient of variation shows that.417 of the data varied from the mean of This moderate variation can be explained by large numbers of disagree and strongly disagree. Additionally a two-tail upper critical-score and two-tail lower critical z-score hypothesis test for a one-population mean was conducted on the population mean of 79% of consumers will take their buying power elsewhere because of poor customer call center experience with a significance level of.05. The sample population produced a mean of.81 with a standard deviation of 1.81 of a sample size of 100. This data produced a z-score of with a two-tail upper and lower critical z-score of 1.96 / The outcome of the data stated that two-tail

11 upper and lower critical z-score allowed me to reject the null. Further the data produced an upper one tailed critical z-score of 1.64 also confirming the H1 and a rejection of the null. A single variable correlation output report was also conducted on customer perception on length of knowledge gained based on employment length of a CSR. A correlation coefficient R of.482 with a coefficient of determination R-square of 23.19% with a adjusted R-square of 22.41%. The number of observations was 100 with a level of significance of.05. The t-score result was The information supports the rejection of the null. A hypothesis test for two population means was conducted in the validity of H1. Sample population 1 produced a 3.51 mean, standard deviation of 1.41 with a sample size of 100 participations. Sample population 2 produced a mean of 2.06, standard deviation of 1.30 with a sample size of 100. The significance level is.05. The results yielded a t-score of 7.557, with 198 degrees of freedom and a pooled variance of Both two-tail upper and lower critical scores are 1.97 / As a result of the analysis null hypothesis was rejected. Lastly, the data produced an upper one tail critical score of 1.65 allowing the rejection of the null. Conclusion The most significant trend overall was the tendency toward neutral responses. This trend may be explained as different satisfaction levels reflect different issues and, therefore, require different actions. All questions surveyed were directly tied to scales that had a very high degree of validity. Since the scales and survey questions are valid and the survey results yield multiple discrepancies, a larger sample population may be needed. US-based online retailer employee training and employee satisfaction may have a direct impact of US based online

12 retailer call center customer satisfaction. Further study should be done to determine the meaning, extent, and impact on this.