The study of A1 Hotels survey on customer satisfaction consists of an extensive data that reviews 200 customers on three essential areas of the operations of the hotel which include the quality of services, the quality of rooms, and the quality of food. The analysis in this report offers comprehensive data which is used to assess the percentage of dissatisfied customers and the test hypothesis carried out. Therefore, the calculations made to arrive at these proportions are presented, as well as their explanations.
Proportions
The calculations for the proportions dissatisfied customers under the three areas - service quality, room quality and food quality are shown below:
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Proportion of all clients who answered “Poor” to Room Quality
P = = 0.21
Proportion of all clients who answered ‘Poor” to Food Quality
P = = 0.24
Proportion of all clients who answered “Poor” to Service Quality
P = = 0.26
Based on the calculations, the proportion of customers dissatisfied with the quality of room is 0.21, which is 21% of the 200 customers surveyed. Therefore, only 79% of the surveyed customers can be said to be satisfied with the room quality. Further, the proportion of customers who are dissatisfied with the quality of food offered at the hotels was calculated as 0.24, which is 24% of the 200 customer’s surveyed. So, only 76% of customers are satisfied with the food quality. Lastly, the proportion of customers dissatisfied with the service quality is 0.26 or 26% of the 200 surveyed customers. This means that 74% of the customers are satisfied with the service quality at the hotels. Generally, the proportion of dissatisfied customers is lower than that of satisfied customers in all areas – service quality, room quality and food quality. However, more customers are dissatisfied with the food quality than room quality and food quality. So, it is crucial for the Hotels to improve on their service quality as a way of enhancing their overall customer satisfaction. Overall, customer satisfaction at the Hotels is good in all areas. For the purpose of graphical displays of the data, a pie chart would be excellent in understanding and explaining the results of the survey.
Confidence Intervals
Evaluating confidence intervals is done to comprise a range of values found to consist of the true population parameter. For A1 Hotels, 92% confidence intervals were calculated using the data values provided. The Confidence Intervals have been calculated as follows:
92% Confidence Interval proportion of all clients who answered “Poor” to Room Quality
92% CI = [0.1596, 0.2604]
The Margin of Error
92% Confidence Interval for Proportion of all the clients who answered “Poor” to Room Quality
92% Confidence Interval for Proportion of all the clients who answered “Poor” to Service Quality
For the overall proportion of dissatisfied customers, the 92% Confidence Interval was calculated as (0.6591, 0.7709). The point estimate of the proportion of all recent clients dissatisfied is 0.715, which suggests a disturbing figure that prompts an immediate action for the Hotels to enhance customer service delivery. Therefore, the point in which the survey continuously samples the customer several times to estimate the intervals contained in the population proportion, the value was found to be within the 92% Confidence Interval of the estimated intervals. In the proportion of the clients who were dissatisfied with the Room Quality, the 92% Confidence Interval was found to comprise (0.1872, 0.2928), and the corresponding margin of error was 0.1008. The proportion of dissatisfied customers with room quality is within the confidence interval, which is significant. On the other hand, the proportion of customers who were dissatisfied with the Food Quality was found to have a 92% Confidence Interval of (0.1825, 0.2875), with a margin error of 0.1057. Similarly, the proportion of dissatisfied customers with room quality is within the confidence interval, and it is statistically significant. Lastly, the proportion of customers who were dissatisfied with Service Quality had a 92% Confidence Interval of (0.2057, 0.3143), with a margin error of 0.1086. The proportion of dissatisfied customers with room quality is within the confidence interval, and it is statistically significant. In general, there are various ways to reduce the margin errors in all the confidence intervals calculated. First, the sample size should be increased. The more the observations, the smaller the interval around the sample statistic. Another way is to use a one-sided CI, which has a smaller margin error.
Hypothesis Testing
The test hypothesis may be calculated by using the tradition proportion of 40% (0.41), of the dissatisfied customers. Thus, the null and alternative hypotheses can be stated as:
H 0 = the proportion of traditional and recent dissatisfaction level are equal, that is, P 0 = P 1 .
H 1 = the proportion of dissatisfaction level for recent clients is higher than tradition level, that is, P 1 > P 0
Where, P 0 = 0.4.
To test the hypothesis at 92% Significance Level z statistic (alpha = 0.08) was used
The sample dissatisfaction proportion, P 1 = = 0.42
The true dissatisfaction proportion, P 0 = 0.42
Therefore, the z-statistic is
The significance level is alpha = 0.08, while the critical value for a right-tailed test is z = 1.405 (the critical value is gotten using z distribution table).
Decision Rule: Reject null hypothesis if
Z-value > Z-critical
The z-statistic = 0.577 < z-critical = 1.405.
Thus, the null hypothesis should not be rejected, which means that there is no significance difference between the two proportions at the significance level of 8%. Overall, a lower significance level followed by a higher significance level would mean that the null hypothesis should be rejected. Other hypothesis tests that could be used to understand the customer satisfaction better are T-test and Chi-Square Test. The advice for A1 Hotels based on the analysis is to take immediate action to enhance customer services delivery, and thus customer satisfaction. This study could be improved by using a larger sample size.
