Homework 4: Customer Service For Airlines ✓ Solved
Homework 4: Customer Service for Airlines
For this assignment, we will be working on understanding the customer service experience offered by a hypothetical airline. When support is required, a customer initiates contact with the airline, either over the phone or using an online platform. Once connected, an agent of the airline works with the customer to understand the problem. When the interaction is complete, the agent creates records about the case. This includes the overall category of the issue along with whether the problem was resolved.
The airline would like to better understand the differences between support provided over the phone and online. With different types of interactions, the agents require different kinds of training, and the costs and resources are different in each modality. With this in mind, the airline is quite interested in comparing the quality of each type of service with regard to how well the cases can be resolved. They are also generally interested in improving their customer service and better understanding the experience.
Research Question
The primary research question that will assist the airline is: "What is the difference in resolution rates between customer interactions through phone support and online support?" This question focuses on a measurable quantity that can provide insights into the effectiveness of each support channel.
Research Study Type
The research study that can be conducted with the available data is a comparative analysis study, focusing on quantitative metrics such as resolution rates, waiting times, and customer demeanor across the two support channels.
Drawbacks of the Study
One drawback of this study is the potential for bias in customer demeanor assessments, as these may reflect the subjective perceptions of the agents rather than objective measures of customer satisfaction. Additionally, other external factors influencing both customer behavior and agent performance could skew the results.
Alternative Experiment Design
If I could devise a different experiment, I would implement a randomized controlled trial (RCT) where customers are randomly assigned to either phone or online support. This may provide clearer insights into the causal relationships and minimize selection biases.
Statistical Test
To analyze the relationship between the type of support (independent variable) and the resolution rates (dependent variable), a Chi-Square test could be performed. This would reveal if there are statistically significant differences between the two support channels in terms of resolution rates.
Consideration of Other Variables
Other variables such as waiting time and customer demeanor should be considered as potential confounders that might influence the resolution rate. These factors could be controlled for in the analysis to isolate the effect of the support channel type on case resolution.
Incorporation of Other Variables
A multivariate regression analysis could be the most appropriate way to incorporate these additional variables into the analysis. This would allow for the evaluation of the independent effects of support type, waiting time, and customer demeanor on resolution outcomes.
Creating a Model
A suitable model would be a logistic regression model to estimate the likelihood of case resolution based on the type of support while incorporating waiting time and customer demeanor as covariates. Analyzing this model would yield key estimates and significance measures pertaining to the relationship between independent and dependent variables.
Concerns About Study Design
There might be concerns regarding the external validity, particularly if the sample of customers interacts with the airline during non-peak hours, which may influence the service quality and resolution rates.
Discussing Incorrect Conclusions
If the conclusions drawn from the data analysis were the opposite of the true effect, it could be due to confounding variables that were not properly controlled, sampling bias, or possibly due to random chance leading to misleading statistical significance.
Implementing a Customer Satisfaction Survey
To implement the idea of a survey effectively, it is crucial to ask for feedback immediately after the resolution of the customer's issue through a short follow-up survey, which can be automated via email or SMS.
Survey Topics
Three important survey topics could include:
- Overall satisfaction: To gauge the customer's perspective on the service quality provided.
- Resolution satisfaction: To evaluate if the customer's issue was satisfactorily resolved.
- Customer demeanor: To assess whether the customer felt understood and valued during the interaction.
Designing Survey Questions
For each selected area, the following survey questions could be considered:
- Overall satisfaction: "How satisfied are you with your interaction today?" (1- Very Unsatisfied to 5- Very Satisfied)
- Resolution satisfaction: "Was your issue resolved to your satisfaction?" (Yes/No)
- Customer demeanor: "Did the agent address your concerns effectively?" (1- Strongly Disagree to 5 - Strongly Agree)
Number of Questions
I would recommend asking around 5 questions to keep the survey short and increase response rates while still gathering essential feedback.
Strategy for Gathering Information
My strategy would involve categorizing the questions into essential and optional regarding customer feedback, prioritizing the most crucial questions that directly correlate to service quality.
Advantages of Longer and Shorter Surveys
Longer surveys can provide more detailed insights into customer experiences, while shorter surveys increase completions and reduce respondent fatigue. Both have their merits depending on the goals of the feedback gathering.
Alternatives to Automated Surveys
Alternatives to automated surveys could include follow-up phone calls or interviews conducted by customer service agents for a more personalized touch, potentially yielding richer qualitative data.
Customer Participation Likelihood
Customers who are more likely to have had a positive experience may be more inclined to participate in surveys, while dissatisfied customers might avoid providing additional feedback.
Reliability of Automated Survey Data
The reliability of data from automated surveys can be considered moderate to high, but this is contingent on survey design and response rates; potential bias may still influence the perceived satisfaction levels recorded.
Strategic Recommendations
Recommendations could include implementing regular training for agents based on survey feedback, investing in customer relationship management systems to track interactions and improvements, and conducting ongoing assessments of customer feedback to refine services systematically.
References
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