Missing Value Identification And Correlation

Data Cleansing Completion

Task 1: Cleanse Dataset File A

Missing Value Identification

Replace Missing Values with 0

Data cleansing completion

Task 2 – Justification of the cleansing process

Firstly, the data was required to be cleansed through effective data cleaning operations. The key issue found out in the data was the missing values under the dataset (in the refund time variable) (Azeroual, Saake and Abuosba 2019). Therefore, firstly the missing values are identified in the dataset and then the missing values are replaced by zero (i.e., zero refund time).

Task 3 – Relationship between customer satisfaction, refund time and data privacy concerns 

Correlation

 Summary Statistics

Task 4 – Processes used

Mainly the correlation analysis is used for the analysis that is used to test the association in between a couple of variables. In each case the correlation value represents how one of the couple is correlated or associated with the other. In case of a negative correlation co-efficient it is a negative association and in case of a positive value it indicates a positive association (Zhuang, Yang and 2020). While, the zero value indicates no association.

Task 5 – Explanation of the analyses

The overall analysis of the Winglet is identifying that there are two particular areas of concern regarding the market impact factors for the company. These key areas of concern are the customer satisfaction level and the brand reputation or the brand loyalty in the market of the Winglet. These areas were required to be analyzed for the company in order to understand the market performance and the future marketing strategy of the company. Therefore, the data set available from the market is analyzed based on these concerns regarding the market factors.

Firstly, the overall analysis is showing that the impacts of the key factors on the customer satisfaction has significant effects. The refund time is observed to be having a negative correlation (-0.16379) with the customer satisfaction showing a probable negative impact on the customer satisfaction (Makowski et al. 2020). Further, the data privacy concern is having a negative correlation with the customer satisfaction as well (-0.31036) that is showing the data privacy concerns are negatively impacting the customer satisfaction.

On the other hand, the impacts on the brand reputation is assessed in terms of three particular factors. Firstly, the refund time and data privacy concerns are having negative correlation with the brand loyalty parameter (-0.38815 and -0.12493 respectively). Further, the satisfaction rating is having a positive correlation (0.680808) with the brand loyalty indicating a positive impact on the satisfaction level.

The summary statistics provided in the overall analysis in case of each of the variables are indicating the following understandings:

• Satisfaction rating– the mean rating of customer satisfaction is 4.8 that is moderately high with high median value of 5 (50% percentile – half of the ratings are above this value)
• Refund time- the mean time to refund is 1.14 business days with the median value of 0 indicating very low refund time (Speed, Holmes and Balding 2020)
• Brand loyalty- the mean rating of brand loyalty is 4.5 that is moderately high with high median value of 5
• Data privacy concern- the mean level of concern of data privacy is 4.4 that is moderately high with high median value of 5
• Duration at Hotspot Selling Points Beacon- the mean value is 12.4 with median 0 i.e., showing that mostly low time is required at hotspot selling points beacon
• Duration at information desk beacon- the mean level of concern of data privacy is 0.63 with median 0 which also shows mostly low time is required at hotspot selling points beacon
• Duration in security check-in beacon- the mean level of concern of data privacy is 2.56 with median zero as well indicating a low time at required at hotspot selling points beacon.

Figure-1: Process Flow Diagram

(Source- Created by Author)

Winglet Travel (Winglet) is an existing online travel agency that offers multiple services to the customers acting as passengers and booking their services in a timely manner. The company had been founded in the year 2013, by four IT professionals and objectifies to provide with the best services to all the passengers worldwide. The company mainly carries out all of their business operations through their existing website, which is the main platform offered to the customers for their booking and other relevant services offered (Guan, Wu and Jia 2020). However, the online booking platform has been in use for a long time now, which contains multiple issues that require to be resolved. As a reason, this particular section shall highlight two major issues that are present within the existing Winglet platform and proposes specific solutions to reduce the likely probability of such issues in future for the services offered to the customers.

Correlation Analysis

Issue-1: 

The company mainly allows the customers with an automated flight check-in functionality, which is an enhancement to the existing platform for the services offered to individual passengers on the flight. Following this, the company has also tended to integrate a Google map, which provides the customers with information based on real-time such as information regarding the airport, including the likes of possible delays caused in traffic-time (Ometov et al. 2018). This mainly serves as a specific integration of customer satisfaction related to all the services that are offered.

However, one particular issue that has been found is the security over customer sensitive information, which has not been undertaken as a serious cause. Individual passengers all across the world have been using this application for their travelling that mainly requires them to register to the application and successfully book flight tickets as well as obtain other additional services offered by Winglet. However, there is no specific security integrated into the existing online platform that is primarily based upon protecting the privacy and integrity of such travelling passengers. As a reason, the platform being an online one, there is a likely possibility of online hackers tending to pose a specific threat upon the user accounts. Such online criminals upon obtaining the passwords to individual customer accounts can get past the login page and successful steal sensitive information (Das et al. 2019). This has a direct impact upon the associated integrity of the customers belonging to Winglet and specifically hampers the likely privacy of them in terms of their personal data. Hence, this has been considered as one specific issue within the online booking platform, which needs to be resolved in the proposed application with the integration of an enhanced security feature.

Proposed solution to Issue-1: 

In particular, the proposed solution is mainly based upon increasing the associated security over the application and customer data by adding an extra form of security during the login procedure (Ometov et al. 2019). Every individual customer is required to provide their mobile numbers during registration to receive updates on their bookings, flights, tickets and additional offers from Winglet. Hence, addition of their personal calling number is a prime necessity when registering on the application.

However, the extra security feature that has been proposed as a solution to the rising issue of online hacks is that after providing their required credentials on the application to login to their accounts, another screen is followed by the login screen. This screen requires the customer to input their mobile number, which then sends a One-Time Password (OTP) to the customer registered mobile number (Sajjad et al. 2019). A space for entering the sent OTP is already present on the page, which requires them to enter the OTP and successfully login to their registered accounts.

This acts as a specific enhancement to the security over customer sensitive data present within their registered accounts on the Winglet application. This works when external unauthorized access obtains the password to a respective passenger on the application and tries to login. However, they would fail to login to their registered Winglet account as soon as the OTP screen pops up. This will notify the respective customer regarding an attempt to login to their account has been made and on the other hand, will prevent the online hacker to access the account of the particular user and steal sensitive information readily available inside that respective Winglet account.

Impact on Customer Satisfaction

Issue-2: 

This section clearly describes another issue, which is already existent within the online booking platform that is currently used at Winglet and by the present customers of the application. This issue is mainly based upon the customer satisfaction that is offered to individual customers upon successfully obtaining all the offered services in particular (Jacomme and Kremer 2021). This issue is mainly dependent upon the customer assistance that is offered to individual customers through the online booking platform that is presently offered to them for booking flights and relative services offered to the customers. This issue has been prevailing for a long time now, and has been causing distress among the individual customers at Winglet.

This is when the customers need to efficiently contact the customer assistance services of the company in case a problem in faced during flight booking or any other relative services or functionalities that are offered to the individual customers at Winglet. Issues in the customer assistance directly has an impact upon the customer satisfaction leading to a specific dissatisfaction (Maciej and Kurkowski 2019). This also might create a negative image in terms of customer support for Winglet among all the customers existing worldwide. As a reason, a solution has been proposed in the following section to mitigate this particular issue that has been highlighted and has been impacting the likely business integrity at Winglet.

Proposed solution to Issue-2: 

The proposed solution that has been provided to be implemented on the application for Winglet is to integrate a chatbot with the help of techniques related to Artificial Intelligence (AI). The chatbot shall be acting as a pop-up on every individual page of the developed application for Winglet, and asking questions to the customer if they need any specific help during their process of flight booking or relative services offered by the company (Assiouras et al. 2019). The chatbot will be functioning 24/7 tending to resolve the issues by any of the customer existing worldwide. A database shall be connected to the chatbot present on individual pages of the application, which is supposed to contain answers already stored to frequently asked questions (FAQs) for the customers to obtain an instant answer to any of the questions that have been asked in a virtual manner.

This is followed by the chatbot to learn from the questions that are newly asked to it by any of the customers based on the services offered to them by Winglet during any point of the day irrespective of the time zone the respective customer belongs to (Chung et al. 2020). However, in exceptional cases where the associated customer is likely to ask a specific question, to which the answer is not present on the database connected to the chatbot for the online booking system, a scheduled sessions with one of the customer assistance executives at Winglet shall be taking place.

The customer assistance support provides the individual customers with two options, either to communicate through the chatbot application present on the online platform or to arrange a direct over the phone communication with the respective customer to resolve the identified issue. Such answers to newer questions are again stored into the database integrated with the online chatbot application present on the online booking system used at Winglet (Mahaboob Basha et al. 2020). Hence, this specifically has a direct impact upon a significant increase of customer satisfaction that directly deals with the likely understanding of customer problems and resolve them in an immediate manner without further delay.

Impact on Brand Loyalty

This particular solution has also been aimed at increasing the communicational gap between the employees at Winglet and the customers existing worldwide, where the primary objective is to enhance the quality of services offered to the customers through the online booking system aimed at successfully increasing the customer satisfaction at all times (Adamopoulou and Moussiades 2020). The proposed solution might also tend to increase the communication, where upon over the phone communication between a customer assistance executive might tend to provide with a feedback form to the individual customer at Winglet, asking them to fill the same and provide feedback based on the conversation carried out between them along with the grading based on the resolution of the faced issues provided by the respective executive at Winglet.

This will provide with a helping hand in efficiently integrating better services within the online booking platform designed for online flight booking at Winglet as well as enhance the likely experience of dealing with the application and obtaining services by all the customers associated to the offered services (Przegalinska et al. 2019). As a reason, the communication between individual customers and the customer support department at Winglet has a beneficial impact upon multiple things in particular.

References

Adamopoulou, E. and Moussiades, L., 2020, June. An overview of chatbot technology. In IFIP International Conference on Artificial Intelligence Applications and Innovations (pp. 373-383). Springer, Cham.

Assiouras, I., Skourtis, G., Giannopoulos, A., Buhalis, D. and Koniordos, M., 2019. Value co-creation and customer citizenship behavior. Annals of Tourism Research, 78, p.102742.

Azeroual, O., Saake, G. and Abuosba, M., 2019. Data quality measures and data cleansing for research information systems. arXiv preprint arXiv:1901.06208.

Chung, M., Ko, E., Joung, H. and Kim, S.J., 2020. Chatbot e-service and customer satisfaction regarding luxury brands. Journal of Business Research, 117, pp.587-595.

Das, S., Wang, B., Tingle, Z. and Camp, L.J., 2019. Evaluating user perception of multi-factor authentication: a systematic review. arXiv preprint arXiv:1908.05901.

Guan, Y., Wu, B. and Jia, J., 2020. Does online ticket booking system make people better off? An empirical study on railway service. Transportation Research Part F: Traffic Psychology and Behaviour, 73, pp.143-154.

Jacomme, C. and Kremer, S., 2021. An extensive formal analysis of multi-factor authentication protocols. ACM Transactions on Privacy and Security (TOPS), 24(2), pp.1-34.

Maciej, B. and Kurkowski, M., 2019. Multifactor authentication protocol in a mobile environment. IEEE Access, 7, pp.157185-157199.

Mahaboob Basha, S., Aakash, M., Dilipkumar, M.N., Aravindh, K., Pavaiyarkarasi, R. and Navin Sankar, J., 2020. Customer assistance using artficial intelligence based chat bots. European Journal of Molecular and Clinical Medicine, pp.2206-2213.

Makowski, D., Ben-Shachar, M.S., Patil, I. and Lüdecke, D., 2020. Methods and algorithms for correlation analysis in R. Journal of Open Source Software, 5(51), p.2306.

Ometov, A., Bezzateev, S., Mäkitalo, N., Andreev, S., Mikkonen, T. and Koucheryavy, Y., 2018. Multi-factor authentication: A survey. Cryptography, 2(1), p.1.

Ometov, A., Petrov, V., Bezzateev, S., Andreev, S., Koucheryavy, Y. and Gerla, M., 2019. Challenges of multi-factor authentication for securing advanced IoT applications. IEEE Network, 33(2), pp.82-88.

Przegalinska, A., Ciechanowski, L., Stroz, A., Gloor, P. and Mazurek, G., 2019. In bot we trust: A new methodology of chatbot performance measures. Business Horizons, 62(6), pp.785-797.

Sajjad, M., Khan, S., Hussain, T., Muhammad, K., Sangaiah, A.K., Castiglione, A., Esposito, C. and Baik, S.W., 2019. CNN-based anti-spoofing two-tier multi-factor authentication system. Pattern Recognition Letters, 126, pp.123-131.

Speed, D., Holmes, J. and Balding, D.J., 2020. Evaluating and improving heritability models using summary statistics. Nature Genetics, 52(4), pp.458-462.

Zhuang, X., Yang, Z. and Cordes, D., 2020. A technical review of canonical correlation analysis for neuroscience applications. Human Brain Mapping, 41(13), pp.3807-3833.

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