GBM5REM Research Methods Assignment Sample

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1.0 Introduction

1.1 Research topic

The impact of AI (artificial intelligence)-powered tools on improving customer service and customer satisfaction levels in the UK retail industry.

1.2 Research background

In modern world, artificial intelligence (AI) technology has become progressively important because of its several applications and advantages. Artificial intelligence refers to the ability of computational systems to carry out tasks and activities usually related with the human intelligence. AI technology is quickly transforming the business operations and provide assistance to perform complex tasks with minimal or no errors. This technology extremely utilised by the industries including retail sector to offer better customer service and improve satisfaction of the consumer (Cao, 2021). The retailers of the UK are utilising the AI to forecast trends, making strategies related to inventory, handle supply chain operations and offer excellent services to customers that ultimately help to enhance customer satisfaction. Advance technology helps the retailers to boost its performance and productivity, leading to increased profit margins. The current study is going to assess the impact of AI on refining delivery customer service as well as satisfaction of consumers. Further, the report will shed light on opportunities and issued experienced by retailers while adoption and implementation of technology. The research will make use of relevant research methods such as; qualitative, inductive and interpretivism to collect data and information. The research would help to understand the AI in customer satisfaction in better way and would discover the new insights and understandings and lead to further evaluation..

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1.3 Research rationale

From past several years, advance technologies are using by the retail industry in excessive manner and AI is one of them which is integrating by companies to perform everyday business operations. The major reason behind using AI in retail companies is that it helps to offer excellent customer service and meet the unique needs of customers. Artificial intelligence has capability to boost the satisfaction level of consumers which is not possible by the traditional methods (Har et al, 2022). The study will highlight how AI-powered tools are reforming consumer experiences and overall efficiency of organisations. However, the technology involves some challenges that can impact the business operations negatively. The research highlight the challenges posed by AI while implementing it in business. Further, the research study discusses the certain facts which supports the contribution of AI-generated tools in the retail industry of the United Kingdom.

1.4 Research aim

The present study aims to evaluate the influence of AI related tools on boosting customer service delivery and enhancing customer satisfaction levels in the UK retail sector.

1.5 Research objectives

• To examine different AI-powered tools being applied currently for customer service operations in the retail sector of UK.
• To analyse the influence of these AI tools on effectiveness and quality of the customer service delivery within UK retail.
• To evaluate the opportunities along with challenges faced by retailers of UK in adoption and application of AI in customer service related operations.

1.6 Research questions

1. 1 What are the different AI associated tools presently being integrated for customer service activities across retail sector of UK?
2. 2 What are the various impacts of AI tools on customer service delivery efficacy and quality within UK retail?
3. 3 What are the various opportunities and challenges encountered by UK retailers in embracing and effective application of artificial intelligence in customer service functions?

1.7 Research gap

Although, past studies have significantly discuss the impact of AI on retail industry in terms of customer service delivery and their satisfaction. While the previous research presents a relation between artificial intelligence technology and customer service delivery, but there is a limited research on influence on AI tools on consumer satisfaction. Past studies also do not focus on at what level AI impacted customer’s satisfaction. This research will analyse the at what extent AI tools influences the consumer contentment and experiences (Rane, 2023). The study will use secondary data collection methods and excellent methodologies to carry out the research effectively that will further help to address research issue efficiently. The research will pay attention on positive and negative sides of artificial intelligence that help to fill the gap research gaps.

1.8 Research benefits

The research majorly focus on use of AI in customer service delivery and improving consumer satisfaction. The research will help analyst in future to perform further studies. The study will also utilised by the other researchers and scholars in their studies. The analysis and findings of the research will help the retail firms of the UK to improve own technical abilities. Retail organisations will know about the different types of AI tools that can be utilised in the customer service operations (Pillarisetty and Mishra, 2022). The retail companies of the UK, particularly small and medium firms can know the impact of AI tools on delivering customer services. By gaining enough knowledge, the retailers will offer excellent services and grab attention of more customers. The study will benefit the retail organisations to know the various challenges associated with this technology. When retail companies will integrate the AI tools, then they will consider its related risks and make mitigation strategies and leverage AI tools effectively.

2.0 LITERATURE REVIEW

2.1 Introduction

Literature review refers to a comprehensive evaluation and review of already published literature which relates to a specific research topic or research questions being studies. The current study concerns with undertaking a detailed analysis of the research topic through considering and involving different point of views of various authors. Therefore, an effective and in-depth understanding could be developed by literature review in the research area. The section will conduct literature review and different kinds of tools related to artificial intelligence will be also discussed. Influence of artificial intelligence on customer services and boosting satisfaction of individuals would be also evaluated. Critical evaluation will be performed and the section will include both positive and negative aspects regarding use of artificial intelligence. Further, the opportunities as well as challenges experienced by the enterprises when they adopt and implement the technology in customer service activities will be also analysed here.

2.2 Main body: thematic

Theme 1: AI-powered tools utilised for customer service operations in UK retail sector

According to, Joshi, Kulshreshtha and Jain, (2024), nowadays, artificial intelligence is increasingly becoming popular among business organisations. There are different AI tools that used by the organisations to deliver high quality services to target audience and fulfil their individual needs. Chatbots is one of most useful AI tools that helps the company to through managing basic inquires of customers, offering quick responses and helping with tasks like order tracking. Recommendations regarding product and troubleshooting. However, chatbots are not capable to understand the emotions of the customers. Raj et al, (2024) analysed that automated checkout or cashier-less tool is amazing technology that allow the customers to make payment faster and make in-store check easier. Customers are also choosing the company that offer cashless services while shopping. Nevertheless, there is a high risk of data breaches. If the company offers online payment services without strong security system, then hackers can easily hack the confidential information of customers.

It is stated by, Kang and Choi, (2024), the retail industry is using the various AI-powered tools to connect with the customers more efficiently and offer excellent services so that they feel satisfied after purchasing. The companies are now using the predictive analytics tools to collect the valuable insights related to customer needs, buying patterns and demands. However, some ethical concerns are associated with the predictive analytics. Behera et al, (2024) said that there are several content generation AI tools that allow the company to create engaging and attractive content. The content generation tools prepare the content that can be easily understand by the people and solve the queries of customers within a minute. The major drawback of AI tools is that it can replace the human employees in customer service team which can lead to higher levels of unemployment.

Theme 2: Impact of AI tools on quality & efficiency of customer service in UK retail 270

In accordance with, Guha et al, (2021), artificial intelligence is considered as one of the beneficial technologies, especially in terms of improving customer experiences and offering great services. Chatbots as well as virtual assistants which are powered by the AI technology tackle the large amount customer queries and offer quick responses. The tools solve the basic problems of the customers which helps the company in reducing wait times and increasing trust of customers towards the company. However, they are not able to solve the complex issues and understand the human emotions. Oosthuizen et al, (2021), evaluated that AI tools related to predictive analytics easily evaluate the large amount of information of customers, including, their needs, demands, past purchases and issues. Through using these information, predictive tools provide more significant product regarding suggestions that increase the customer experience. Conversely, predictive analytics highly depends on data they and if the data is partial then prediction will be faulty. It is crucial for the retail firms to address this issue to take benefits of AI.

Yeo et al, (2022) stated that by using AI tools like chatbots, the customers can ask queries anytime which means the company can offer support to the consumers even after business hours. This makes sure that consumers can take help whenever they require, which in turn improved overall satisfaction. Through utilising AI tools, the retail companies can communicate with the customers in different languages which is helpful when a company is operating in all over the world. Sometimes, AI can also do mistakes in comprehending intent of customer and give wrong solutions to problems that can harm the trust of the customers towards the particular company and lead to adverse experiences.

Theme 3: Opportunities and challenges faced while embracing and applying AI 270

According to, Brill, Munoz and Miller, (2022), in the United Kingdom, the retailers experiences a combination of opportunities and risks when they adopt and apply the artificial intelligence for providing exceptional customer service. AI offers an opportunity of enhancing experiences and satisfaction of the consumers to the companies. Through adopting AI-generated virtual assistant technology, the retailers immediately offer solutions and suggestions to customers that ultimately help in boost consumer’s satisfaction level. Nguyen et al, (2022) researched that when a retail company applies artificial intelligence, it gives opportunity of reducing cost and save money for many other business operations. Through automating consumer service, the companies can possibly reduce recruitment and staffing costs and enhance resource allocation. The organisations have chance to tailor interactions and inform about the offers through using AI in customer services.

As per the opinion of, Jain et al, (2023), though artificial intelligence offers numerous benefits but it also create some problems for retailers. Integrating AI-powered tools is quite costly which make it difficult for the companies, especially small and medium retailers to invest in AI. There is high risk data breaching which not only impact customer’s trust but also influence business itself. In the absence of robust security system, anyone can access to customer’s confidential information. Stanciu and Rîndaşu, (2021) argued that the retail companies may face the failure to adopt and apply technology if their staff members are not familiar with advance technology. Due to lack of knowledge about AI, employees are not able to use the technology in an appropriate manner and cannot perform tasks and activities accurately.

2.3 Conclusion and Literature Gap

The above section has discussed about the different AI tools like cashier-less checkout, predictive analytic, Chatbots etc. that used by the retail firms in their customer service functions. It has identified that AI-powered tools enhance customer experience and fulfil their expectations but it also created problems for business like data privacy, biasedness, transparency issues etc. In this research, limited websites has been used due to restricted access. Though different articles, books and journals has been utilised to collect relevant information and facts and complete report accurately. The study has been not considered quantitative approach because of budget issues. However, qualitative approach has been applied that helped to address the research questions properly. Moreover, secondary data collection method utilised instead of primary due to budget constraints but reliable and authentic sources has been utilised to gain the accurate information. It is most important for the retail organisations to offer the training before applying the technology so that employees can easily use it in their job.

3.0 RESEARCH METHODOLOGY

3.1 Brief introduction of methodology & research onion

Research methodology refers to the systematic and methodical approach to carry out research, involving overall strategy, approaches, methods and processes that are utilised by the researcher to collect, evaluate and interpret data. The section is going to explain about the different research methods which will be utilised to address research questions appropriately. The Research onion model developed by the Saunders explains the various decisions a researcher will require to make while developing or creating research methodology. The onion is consist of six layers such as; research philosophy, research strategy, research approach, choices, time horizon and techniques and processes.

3.2 Gantt Chart Diagram

Task Mode	Task Name	Duration	Start	Finish	Predecessors
Auto Scheduled	Initiation	11 days	Fri 11-07-25	Fri 25-07-25
Auto Scheduled	Choosing topic	4 days	Fri 11-07-25	Wed 16-07-25
Auto Scheduled	Drafting briefing document	7 days	Thu 17-07-25	Fri 25-07-25	2
Auto Scheduled	Planning	11 days	Mon 28-07-25	Mon 11-08-25
Auto Scheduled	Setting up research aims, objective and question	4 days	Mon 28-07-25	Thu 31-07-25	3
Auto Scheduled	Identifying and arranging required resources	7 days	Mon 28-07-25	Tue 05-08-25	3
Auto Scheduled	Research method selection	4 days	Wed 06-08-25	Mon 11-08-25	3,6
Auto Scheduled	Execution	53 days	Tue 12-08-25	Thu 23-10-25
Auto Scheduled	Exploring diverse data sets	18 days	Tue 12-08-25	Thu 04-09-25	7
Auto Scheduled	Arranging collected data	12 days	Fri 05-09-25	Mon 22-09-25	9
Auto Scheduled	Evaluating & interpreted data	9 days	Tue 23-09-25	Fri 03-10-25	10
Auto Scheduled	Writing down findings and recommendations	8 days	Mon 06-10-25	Wed 15-10-25	11
Auto Scheduled	Undertaking formatting	6 days	Thu 16-10-25	Thu 23-10-25	12
Auto Scheduled	Monitoring	4 days	Fri 24-10-25	Wed 29-10-25
Auto Scheduled	Receiving tutor’s feedback	4 days	Fri 24-10-25	Wed 29-10-25	13
Auto Scheduled	Closures	2 days	Thu 30-10-25	Fri 31-10-25
Auto Scheduled	Undertaking modification and final submission	2 days	Thu 30-10-25	Fri 31-10-25	15

3.3 Research structure

Research approach is plan that guides the manner in which data will be collected, analysis and interpreted (Mulisa, 2022). Research philosophy includes various assumptions that are formulated whole conducted study. In this line, inductive approach and interpretivism philosophy will be used to explore diverse impact on AI powered tools on overall customer services. Inductive approach offers holistic view of issue based on which new hypothesis is formulated. In addition to this, interpretivism philosophy assists in exploring hidden reason behind multifaceted and complex social processes. Further, current study is based on qualitative method which could be best initiated through inductive and interpretivism approach.

3.4 Research strategy

Research strategy implies for the plans and scheme through which information related to topic is collected. There are three significant type of research strategy which includes qualitative, quantitative and mixed strategy (Taherdoost, 2022). In the contest of determining AI impact on customer satisfaction, research will utilize qualitative method which offers nuanced understanding of respondent belief and perception. It also offers deeper insight of the real- world problem based on which accurate conclusions are drafted. Further, influence of AI powered tools on customer satisfaction could not be recorded in numerical stances because of which qualitative method will be utilized.

3.5 Method to use

It refers to diverse techniques, strategies and processes which are used for collecting and analysing data for uncovering better information related to topic. There are four major types of research methods that are Correlation, Experimental, Descriptive and causal- comparative (Kamper, 2020). Descriptive method will be used to explore impact of AI powered tool on satisfaction of customers. It is significant method which offers optimum information related to behaviour and characteristic of phenomena and thereby gaining deeper insight. Moreover, present study is based on qualitative data which could be best accompanied through descriptive method.

3.6 Time scale

Activities /weeks	1	2	3	4	5	6	7	8	9	10	11	12
Selecting topic & drafting outline
Formulating aims and objectives
Arranging all relevant resources
Evaluating & selecting optimum research method
Collecting secondary data
Organising raw data
Analysing & interpreting data
Recommendation & conclusion
Initiating formatting
Taking supervisor feedback
Initiating modification & final submission

3.7 Data collection methods

There are majorly two types of data collection methods such as; primary and secondary. In primary, researcher conducts survey or interview on customers to get real and valuable insights (Mishra and Alok, 2022). Under secondary method, an analyst uses already published articles and books. Secondary data collection will be used in this research to gather latest information and facts related to AI in customer services. Different articles, academic books and research papers will be used to collect the information.

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3.8 Data analysis methods

Data analysis is defined as procedure of inspecting, transforming and modelling data to inform conclusion. There are two kinds of data analysis which are SPSS and thematic. The research will utilise the thematic analysis as it is highly appropriate for the qualitative data (Dubey and Kothari, 2022). In this study, various themes will be created as well as research questions will be discussed. It is flexible method and enable analyst to examine the data closely and make relevant conclusion.

3.9 Ethics

Ethical considerations can be explained as set of rules and standards that help to conduct research in ethical and truthful way. Thus, an analyst will follow relevant rules, regulations and principles throughout the research (Kumari et al, 2023). While carrying out study, privacy and confidentiality of people who are involved in the research will be upheld. Appropriate referencing will be done and proper credit will be given to the authors. Academic integrity will also followed during the research so that plagiarism free report will be made.

3.10 Conclusion

In this particular research study, qualitative method, descriptive and inductive approach and secondary research has been utilised to carry out the research appropriately. Qualitative method helped to gain the in-depth understanding regarding impact of AI on customer’s satisfaction. In secondary research, researcher utilised relevant books which were published in recent years. This helped in making authentic and valid research.

REFERENCES

Books and Journals

• Behera, R.K., Bala, P.K., Rana, N.P., Algharabat, R.S. and Kumar, K., 2024. Transforming customer engagement with artificial intelligence E-marketing: an E-retailer perspective in the era of retail 4.0.Marketing Intelligence & Planning,42(7), pp.1141-1168.
• Brill, T.M., Munoz, L. and Miller, R.J., 2022. Siri, Alexa, and other digital assistants: a study of customer satisfaction with artificial intelligence applications. InThe role of smart technologies in decision making(pp. 35-70). Routledge.
• Cao, L., 2021. Artificial intelligence in retail: applications and value creation logics.International Journal of Retail & Distribution Management,49(7), pp.958-976.
• Dubey, U.K.B. and Kothari, D.P., 2022.Research methodology: Techniques and trends. Chapman and Hall/CRC.
• Guha, A., Grewal, D., Kopalle, P.K., Haenlein, M., Schneider, M.J., Jung, H., Moustafa, R., Hegde, D.R. and Hawkins, G., 2021. How artificial intelligence will affect the future of retailing.Journal of Retailing,97(1), pp.28-41.
• Gupta, A. and Gupta, N., 2022.Research methodology. SBPD publications.
• Har, L.L., Rashid, U.K., Te Chuan, L., Sen, S.C. and Xia, L.Y., 2022. Revolution of retail industry: from perspective of retail 1.0 to 4.0.Procedia Computer Science,200, pp.1615-1625.
• Jain, V., Sheth, J.N., Mogaji, E. and Ambika, A., 2023. Artificial intelligence in customer service: An introduction to the next frontier to personalized engagement. InArtificial Intelligence in Customer Service: The Next Frontier for Personalized Engagement(pp. 1-11). Cham: Springer International Publishing.
• Joshi, N.K., Kulshreshtha, K. and Jain, U., 2024. THE ROLE OF AI IN ENHANCING CUSTOMER SERVICE IN THE RETAIL SECTOR.Journal of Data Acquisition and Processing,39(1), pp.1270-1277.
• Kamper, S.J., 2020. Types of research questions: descriptive, predictive, or causal.Journal of Orthopaedic & Sports Physical Therapy,50(8), pp.468-469.
• Kang, J.Y.M. and Choi, D., 2024. Artificial intelligence-powered digital solutions in the fashion industry: a mixed-methods study on AI-based customer services.International Journal of Fashion Design, Technology and Education,17(2), pp.162-176.
• Kumari, S.K.V., Lavanya, K., Vidhya, V., Premila, G.A.D.J.S. and Lawrence, B., 2023.Research methodology(Vol. 1). Darshan Publishers.
• Mishra, S.B. and Alok, S., 2022.Handbook of research methodology. Educreation publishing.
• Mulisa, F., 2022. When Does a Researcher Choose a Quantitative, Qualitative, or Mixed Research Approach?.Interchange,53(1), pp.113-131.
• Nguyen, M., Chen, Y., Nguyen, T.H., Habashi, S.S., Quach, S. and Thaichon, P., 2022. Artificial intelligence (AI)-driven services: communication support, assistance for decision-making, and enhanced customer experience service. InArtificial Intelligence for Marketing Management(pp. 76-95). Routledge.
• Oosthuizen, K., Botha, E., Robertson, J. and Montecchi, M., 2021. Artificial intelligence in retail: The AI-enabled value chain.Australasian Marketing Journal,29(3), pp.264-273.
• Pillarisetty, R. and Mishra, P., 2022. A review of AI (artificial intelligence) tools and customer experience in online fashion retail.International Journal of E-Business Research (IJEBR),18(2), pp.1-12.
• Raj, K., Fredrick, D.P., Kurahattidesai, C. and Hegde, C.S., 2024. Artificial Intelligence Driven Customer Relationship Management: Harnessing the power of technology to improve business efficiency.International Journal of Communication Networks and Information Security,16(4), pp.58-65.
• Rane, N., 2023. ChatGPT and similar generative artificial intelligence (AI) for smart industry: role, challenges and opportunities for industry 4.0, industry 5.0 and society 5.0.Challenges and Opportunities for Industry,4.
• Stanciu, V. and Rîndaşu, S.M., 2021. Artificial intelligence in retail: Benefits and risks associated with mobile shopping applications.Amfiteatru Economic,23(56), pp.46-64.
• Taherdoost, H., 2022. What are different research approaches? Comprehensive Review of Qualitative, quantitative, and mixed method research, their applications, types, and limitations.Journal of Management Science & Engineering Research,5(1), pp.53-63.
• Yeo, S.F., Tan, C.L., Kumar, A., Tan, K.H. and Wong, J.K., 2022. Investigating the impact of AI-powered technologies on Instagrammers’ purchase decisions in digitalization era–A study of the fashion and apparel industry.Technological Forecasting and Social Change,177, p.121551.