Updated:

Computer R Us Company: Initiatives for Improving Customer Satisfaction Case Study

Exclusively available on Available only on IvyPanda® Made by Human No AI

Introduction

The Computer R Us Company received numerous complaints about the services offered in their CompleteCare division.

After thorough investigations into the complaints, the management established that the division was experiencing problems as a result of inadequacy of trained operators and problems with distribution and availability of parts.

In response to these problems, the management came up with four initiatives that aimed at improving customer satisfaction. In this paper, analysis will be carried using various tools to establish the effectiveness of the initiatives that were put in place.

Research design

Sampling technique

This research was conducted using research survey study approach. Data was collected using a questionnaire that had three sections. The first part required personal information, that is, age and gender. In the second section a Likert scale of ten points was used to collect some data.

The final section focused on determinants of customer satisfaction. Four questions were asked in this section and each had a Likert scale of ten points. The random sampling technique was used to select a sample of 500 customers (Kothari, 2004). The questionnaires were sent to the 500 customers and only 420 responded.

In order to collect the data necessary for this study, several steps will be taken to ensure that appropriate care is taken to protect the participants. There are no universally accepted determinants of customer satisfaction ((Verbeek, 2008).

Besides, the results of previous studies do not give conclusive result on the most effective determinant. Therefore, the attributes used by the management of Computer R Us to improve the level of customer satisfaction are a sample of what other companies use (Zikmund, Babin, Carr, Griffin, 2012).

Hypothesis testing

Does the current level of customer satisfaction differ from management’s goal of 6 out of 10?

Hypothesis

H0: The current level of customer satisfaction = 6.

H1: The current level of customer satisfaction ≠ 6.

Statistical technique

In this case a one sample t-test will be used to test the hypothesis.

Justification

One sample t-test is most suitable for evaluating a hypothesis that compares the actual mean and hypothesized mean.

Results of the test

Variable 1Variable 2
Mean4.4880952386
Variance5.5058245260
Observations420420
Pearson Correlation
Hypothesized Mean Difference0
df419
t Stat-13.20498454
P(T<=t) one-tail7.85063E-34
t Critical one-tail1.64849841
P(T<=t) two-tail1.57013E-33
t Critical two-tail1.965641842
t Stat-13.20498454
t Critical two-tail1.965641842
P(T<=t) two-tail1.57013E-33

Interpretation

The results show that t-calculated is greater than t-critical. Also, the p-value (1.57013E-33) is less than alpha (5%). Therefore, the null hypothesis will be rejected at the 95% confidence level. This implies that the current level of customer satisfaction differ from management’s goal of 6 out of 10.

Is there any difference between the overall satisfaction of male and female customers at Computers R Us?

Hypothesis

H0: Overall satisfaction of male customers = overall satisfaction of female customers at computer R Us.

H1: Overall satisfaction of male customers ≠ overall satisfaction of female customers at computer R Us.

Statistical technique

In this case, a paired sample t-test will be used to test the hypothesis.

Justification

A paired sample t-test is the most suitable for testing hypothesis that compared the mean of two related variables.

Results of the test

t-Test: Two-Sample Assuming Equal Variances

FemaleMale
Mean3.5894308945.75862069
Variance4.275642944.507873231
Observations246174
Pooled Variance4.371757391
Hypothesized Mean Difference0
Df418
t Stat-10.47338477
P(T<=t) one-tail2.98994E-23
t Critical one-tail1.648507149
P(T<=t) two-tail5.97988E-23
t Critical two-tail1.965655464

Interpretation

In the results, the mean and variance of overall satisfaction for the male is greater than that of the female group. Further, t-calculated is greater than t-critical. Also, the p-value is less than alpha (5%). Therefore, the null hypothesis will be rejected at the 95% confidence level. This implies that there is a difference between the overall satisfaction of male and female customers of the company.

Are there any differences in the overall customer satisfaction across the following age groups: under 20, 21-30, 31-40, 41-50, 51 and over?

Hypothesis

H0: There is no difference in the overall satisfaction across the various age groups.

H1: The overall satisfaction of at least one age group is different from the others.

Statistical technique

In this case, analysis of variance (ANOVA) will be used to test the hypothesis.

Justification

ANOVA is the most suitable technique for testing hypothesis that entails comparing mean for more than one group. One way ANOVA will be used because there is only one independent variable.

Results of the test

Anova: Single Factor
SUMMARY
GroupsCountSumAverageVariance
Under 20471803.8297876.579093432
21-301095014.596336.150356779
31-401054664.4380955.786996337
41-501074854.532714.647504849
over 50522534.8653854.236425339
ANOVA
Source of VariationSSdfMSFP-valueF crit
Between Groups29.5228247.3807051.3449411240.2524922.393438
Within Groups2277.4184155.487753
Total2306.94419

Interpretation

In the results above, the value of F-calculated is less than the F-critical. Besides, the p-value is greater than alpha (5%). Therefore, the null hypothesis will not be rejected at the 95% confidence level. This implies that there is no difference in the overall satisfaction across the various age groups.

Are there any differences in the gender compositions across the five age groups?

Hypothesis

H0: There are no differences in gender composition across the five age groups.

H1: Gender composition is different in at least one of the age groups.

Statistical technique

Analysis of variance (ANOVA) will be used to test the hypothesis.

Justification

ANOVA is the most suitable technique for testing hypothesis that entail comparing mean for more than one group. One way ANOVA will be used because there is only one independent variable (Verbeek, 2008).

Results of the test

Anova: Single Factor
SUMMARY
GroupsCountSumAverageVariance
Under 2047200.4255320.249769
21-30109470.4311930.247537
31-40105430.4095240.244139
41-50107410.3831780.238582
over 5052230.4423080.251508
ANOVA
Source of VariationSSdfMSFP-valueF crit
Between Groups0.1838640.0459650.187510.9448722.393438
Within Groups101.73044150.245134
Total101.9143419

Interpretation

In the results above, the value of F-calculated is less than the F-critical. Besides, the p-value is greater than alpha (5%). Therefore, the null hypothesis will not be rejected at the 95% confidence level. This implies that there are no differences in gender composition across the five age groups.

Is there any difference in customer satisfaction based upon ‘response times in the CompleteCare division’ and the ‘loyalty rewards program’?

Hypothesis

H0: Customer satisfaction based upon response times in the CompleteCare division = the customer satisfaction based upon loyalty reward program.

H1: Customer satisfaction based upon response times in the CompleteCare division ≠ the customer satisfaction based upon loyalty reward program.

Statistical technique

In this case, a paired sample t-test will be used to test the hypothesis.

Justification

A paired sample t-test is the most suitable for testing hypothesis that compared the mean of two related variables (Verbeek, 2008).

Results of the test

t-Test: Paired Two Sample for Means
Response timeLoyalty reward program
Mean3.2428571435.645238095
Variance4.2225025577.842817366
Observations420420
Pearson Correlation-0.011950135
Hypothesized Mean Difference0
Df419
t Stat-14.09404771
P(T<=t) one-tail1.69112E-37
t Critical one-tail1.64849841
P(T<=t) two-tail3.38224E-37
t Critical two-tail1.965641842

Interpretation

The results show that t-calculated is greater than t-critical. Also, the p-value is less than alpha (5%). Therefore, the null hypothesis will be rejected at the 95% confidence level. This implies that there are differences in customer satisfaction based upon response times in the CompleteCare division and the loyalty rewards program.

Are any of the initiatives proposed by management related to the overall satisfaction of Computers R Us customers?

Hypothesis

H0: The initiatives proposed by the management are determinants of the overall satisfaction of Computer R Us customers.

H1: The initiatives proposed by the management are not determinants of the overall satisfaction of Computer R Us customers

Statistical technique

In this case, a multiple regression analysis will be used.

Justification

Multiple regression analysis is used to model the relationship between one dependent variable and other explanatory variables.

Results of the test

SUMMARY OUTPUT
Regression Statistics
Multiple R0.965602191
R Square0.932387592
Adjusted R Square0.931735906
Standard Error0.613066164
Observations420
ANOVA
DfSSMSFSignificance F
Regression42150.962676537.74071430.7323.3062E-241
Residual415155.97780060.37585
Total4192306.940476
CoefficientsStandard Errort-StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0%
Intercept0.8965612980.1038837918.6304251.32E-160.692357271.100765330.692357271.100765326
Response time0.864717840.0383673722.537854.92E-740.7892992270.940136450.7892992270.940136454
Level of advice0.2710373160.0411459326.587221.36E-100.1901568920.351917740.1901568920.351917739
Level of communication-0.017753450.021480889-0.826480.409009-0.059978370.02447146-0.059978360.024471457
Loyalty reward program0.0079739030.0106963590.7454780.456405-0.013051890.0289997-0.013051890.0289997

Interpretation

The F-test will be used to test the overall significance of the regression model. The p-value for the F – test is less than alpha (0.05). Therefore, reject the null hypothesis and conclude that the four determinants are significant determinants of the overall customer satisfaction. Further, the p-value for response time and level of advice are greater than alpha (0.05). This implies that they are significant determinants of overall customer satisfaction of the company.

Analysis

The first test show that the overall satisfaction is statistically different from 6 out of 10. The calculated mean is 4.4881 and it is less than the goal. The result of the second question shows that the overall satisfaction of female customers is higher than that of male customers.

Therefore, there is a need to improve the level of satisfaction of the male customers. The results of the third question indicate that there is no difference in the level of satisfaction across the different age groups. Further, tests on question five shows that there is no difference in gender composition across the five age groups.

The fifth test reveals that customers tend to be more satisfied with the loyalty rewards program than response times in the CompleteCare division. Therefore, the management needs to improve the response time in the division. The final test shows that all the four initiatives have a potential of improving customer satisfaction.

Further, response time of the CompleteCare division and level of advice CompleteCare staff provides on Computers R Us products have more impact than the other two initiatives (Baltagi, 2011).

Recommendations

The results of hypothesis testing show that the management did not achieve their goal. For the company to achieve the target of 6 out of 10, the management needs to consider the recommendations listed below.

  • Decrease the response time of the CompleteCare division. This can be achieved by increasing the number of well trained personnel and equipment that can facilitate service delivery at the division. The company should introduce a rating system that can be used by customers continuously.
  • The management should also focus on improving the level of satisfaction of the male customers.
  • The management should train the CompleteCare staff on a continuous basis. This will improve the quality of advice they give clients.

References

Baltagi, G. (2011). Econometrics. New York: Springer Publisher

Kothari, J. (2004). Research methodology: methods and techniques. New Delhi: New Age International (P) Limited Publishers.

Verbeek, M. (2008). A guide to modern econometrics. England: John Wiley & Sons.

Zikmund, W., Babin, B., Carr, J., Griffin, M. (2012). Business research methods. USA: Cengage Learning.

More related papers Related Essay Examples
Cite This paper
You're welcome to use this sample in your assignment. Be sure to cite it correctly

Reference

IvyPanda. (2019, June 24). Computer R Us Company: Initiatives for Improving Customer Satisfaction. https://ivypanda.com/essays/computer-r-us-company/

Work Cited

"Computer R Us Company: Initiatives for Improving Customer Satisfaction." IvyPanda, 24 June 2019, ivypanda.com/essays/computer-r-us-company/.

References

IvyPanda. (2019) 'Computer R Us Company: Initiatives for Improving Customer Satisfaction'. 24 June.

References

IvyPanda. 2019. "Computer R Us Company: Initiatives for Improving Customer Satisfaction." June 24, 2019. https://ivypanda.com/essays/computer-r-us-company/.

1. IvyPanda. "Computer R Us Company: Initiatives for Improving Customer Satisfaction." June 24, 2019. https://ivypanda.com/essays/computer-r-us-company/.


Bibliography


IvyPanda. "Computer R Us Company: Initiatives for Improving Customer Satisfaction." June 24, 2019. https://ivypanda.com/essays/computer-r-us-company/.

If, for any reason, you believe that this content should not be published on our website, please request its removal.
Updated:
This academic paper example has been carefully picked, checked and refined by our editorial team.
No AI was involved: only quilified experts contributed.
You are free to use it for the following purposes:
  • To find inspiration for your paper and overcome writer’s block
  • As a source of information (ensure proper referencing)
  • As a template for you assignment
1 / 1