Field Of Customer Service Research Articles

Contributions of artificial intelligence to the customer service area

Artificial intelligence has gained considerable recognition in recent years, standing out for its ability to transform both industries and society today. Given its importance, many companies have decided to implement this tool in the field of customer service. The objective of this study is to analyze artificial intelligence strategies focused on customer service and retention in the business sector in recent years. In this framework, research was conducted using the PRISMA methodology to explore the various contributions that artificial intelligence brings to customer service areas. A systematic review of the literature in primary sources was carried out. The choice of this methodology made it possible to examine the documented advances of artificial intelligence in the last three years. The results obtained reveal that artificial intelligence contributes significantly to improve efficiency, quality and customer satisfaction, thanks to its wide variety of functions and self-management capabilities.

Business and Customer-Based Chatbot Activities: The Role of Customer Satisfaction in Online Purchase Intention and Intention to Reuse Chatbots

In the online shopping context, brands aim to achieve a high level of profit by providing better customer satisfaction by using various artificial intelligence tools. They try creating a satisfactory customer experience by creating a system that provides never-ending customer support by using dialog-based chatbots, especially in the field of customer service. However, there is a lack of research investigating the impact of business and customer-based chatbot activities together on online purchase intention and the intention to reuse chatbots. This research considers the use of chatbots as a marketing tool from both customer and business perspectives and aims to determine the factors that affect the customers’ intention to purchase online and reuse chatbots. Accordingly, the impact on customer satisfaction with chatbot usage, which is based on chatbots’ communication quality and customers’ motivations to use chatbots, on online purchase intention and intention to reuse chatbots was examined. Through an online questionnaire with two hundred and ten participants, employing structural equation modeling, we revealed that customer satisfaction with chatbot usage has a greater impact on the intention to reuse chatbots than on online purchase intentions. In addition, chatbot communication quality has a greater impact on customer satisfaction with chatbot usage than customers’ motivation to use chatbots. To solidify these findings, confirmatory factor analysis, along with reliability and validity assessments, were implemented within the analytical framework to provide robust support for the study’s hypotheses. These findings not only provide empirical evidence and implications for companies in online shopping but also extend the understanding of AI tools in marketing, highlighting their subtle impact on consumer decision-making in the dynamic digital marketplace.

Development Prospects of Modern Banking

Relevance. The increasing competition between financial institutions and technology companies requires the active implementation of innovative developments in current activities. Artificial intelligence is becoming an everyday fact of presence in communications between business partners and customers, generating new formats of interaction. "Smart" technologies based on artificial intelligence are able to take on certain mechanical functions related to the verification and verification of contract terms, which can significantly speed up formal procedures and reduce the likelihood of operational errors. Innovative solutions for the fulfillment of contractual obligations based on the signing of smart contracts in various business areas contribute to the use of such in banking, where communication is constantly taking place according to standard banking procedures.Purpose. The purpose of the work is to reveal the peculiarity of the use of a smart contract in the banking business for its scaling.Objectives. The following tasks were set and consistently solved in the article: to study the features and nature of the emergence of smart contracts in the business environment, to analyze the existing practice of using this tool, to formulate the principles of transformation of contracting processes with the introduction of "smart" technologies into traditional banking business.Methodology. The methods of generalization, systematization, analogy, graphical and logical analysis, and idea generation were used in the work.Results. The paper examines the properties of an innovative digital banking business contracting tool, highlights its main characteristics and grounds for application, and considers the mechanism of its implementation in the blockchain environment.Conclusions. The article examines the directions of the future development of banking in the domestic banking sector and draws conclusions about the further development of "smart" technologies in the context of increasing competition between banking and technology companies. The expansion of banking business in the online space is impossible without the use of advanced solutions in the field of customer service, which leads to the emergence and development of the practice of intellectualization of traditional contract processes.

Persona-Based Segmentation: Customer Data Mapping as the Foundation of Corporate Marketing Strategy (Case Study on Scarlett Whitening)

This research aims to analyze customer segmentation in energy resource companies using the K-Means Clustering method. In the era of increasingly fierce business competition, a deep understanding of customer preferences and behavior is crucial for companies to design effective marketing strategies. Customer data, including purchase frequency, customer service field, company type and geographic location, were collected and analyzed using the K-Means Clustering algorithm. The analysis results showed the formation of homogeneous customer groups, allowing the company to identify the distinctive characteristics of each group. Five main groups were formed from the processed customer data using SPSS. The first group consists of scarlett's facial wash lovers who are dominated by women with an average age of 31 years, earning an average income of Rp15 million per month who live outside Jakarta and work as private employees. This group recognizes the majority of scarlett products from Tiktok. The second group consists of scarlett serum lovers who are dominated by women with an average age of 32 years, earning an average income of IDR 23 million per month who live in South Jakarta and work as private employees. This group also recognizes the majority of scarlett products from Tiktok. The third group consists of scarlett's shower scrub lovers who are dominated by single women with an average age of 31 years, earning an average income of IDR 10 million per month who live in South Jakarta and work other than private employees. This group recognizes scarlett products mostly from Instagram. The fourth group consists of scarlett's body lotion lovers who are dominated by women with an average age of 32 years, earning an average income of IDR 19 million per month who live outside Jakarta and work as private employees. This group recognizes the majority of scarlett products from Instagram. The fifth group consists of scarlett's body scrub lovers who are dominated by women with an average age of 28 years, with an average income of IDR 6.5 million per month who live in South Jakarta and work as entrepreneurs. This group recognizes the majority of scarlett products from Tiktok. The implementation of marketing strategies based on the results of this analysis shows that Scarlett needs to use cluster 2 as its target segment in order to continue to increase its revenue. Because by choosing this cluster, Scarlett will find it easier to design its marketing strategy, namely by increasing social media strategies by involving creative content and collaboration on the Tiktok platform, offering promotions and special offers for customers who buy Serum. Scarlett could present a special bundle offer for the product or provide points that can be redeemed for further discounts or free products after reaching a certain amount and since cluster 2 is predominantly in the South Jakarta area, focus the marketing campaign in that area. Scarlett's value proposition lies in the use of brand ambassadors, digital marketing, product quality and brand trust. Thus, this study concludes that customer segmentation analysis using K-Means Clustering brings strategic benefits to scarlett sellers. A deeper understanding of customers enables sellers to improve the relevance of marketing strategies, achieve better customer satisfaction, and remain responsive to changes in the business environment.

Understanding users’ responses to disclosed vs. undisclosed customer service chatbots: a mixed methods study

AbstractDue to huge advancements in natural language processing (NLP) and machine learning, chatbots are gaining significance in the field of customer service. For users, it may be hard to distinguish whether they are communicating with a human or a chatbot. This brings ethical issues, as users have the right to know who or what they are interacting with (European Commission in Regulatory framework proposal on artificial intelligence. https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai, 2022). One of the solutions is to include a disclosure at the start of the interaction (e.g., “this is a chatbot”). However, companies are reluctant to use disclosures, as consumers may perceive artificial agents as less knowledgeable and empathetic than their human counterparts (Luo et al. in Market Sci 38(6):937–947, 2019). The current mixed methods study, combining qualitative interviews (n = 8) and a quantitative experiment (n = 194), delves into users’ responses to a disclosed vs. undisclosed customer service chatbot, focusing on source orientation, anthropomorphism, and social presence. The qualitative interviews reveal that it is the willingness to help the customer and the friendly tone of voice that matters to the users, regardless of the artificial status of the customer care representative. The experiment did not show significant effects of the disclosure (vs. non-disclosure). Implications for research, legislators and businesses are discussed.

ФІНАНСОВІ ТЕХНОЛОГІЇ В СИСТЕМІ РОЗВИТКУ БАНКІВСЬКОГО СЕКТОРА

The article is devoted to the role of financial technologies in the development of the banking sector. The article analyzes financial technologies as a driving force for the development of the banking sector, a tool for competition in the financial services market, and a measure of globalization innovations in the financial sector. It is established that the high development of competition in the financial services market in Ukraine leads to the intensification of financial institutions. New methods are recognized and studied to improve the efficiency of functioning, especially through the introduction of financial and information technologies in the field of customer service, the release of new products and services. Financial technologies are used in all functions of the financial sector, from payment to savings, lending, risk management, and advice. Fintech is becoming an integral part of society, and fintech solutions are becoming more and more relevant. The majority of fintech companies come from the United States of America and China, and these two countries were also the home for 8 of the 10 largest fintech companies in the world in January 2024. It is determined that the fintech industry's revenues are increasing annually. The most intensive development is shown in the Asia-Pacific region, and the European fintech industry developing at a slower pace. As of January 2024, the Americas (North America, South America, Central America, and the Caribbean) was the region with the largest number of fintech companies in the world. In 2022, investment activity slowed significantly, particularly in the America, most likely due to the economic decrease caused by the COVID-19 pandemic. It is determined that fintech companies are going to become a key driving force in the development of the Ukrainian financial market in the future, as well as the improvement of the Ukrainian financial system, so their development is supported by the National Bank as the state regulator of the financial sector, and the experience of leading countries shows the inevitability of implementing financial innovations in times of high turbulence in financial markets.

An enhanced method for dialect transcription via error‐correcting thesaurus

AbstractAutomatic speech recognition (ASR) has been widely used in the field of customer service, but the performance of general ASR in dialect transcription is not satisfactory, especially in Guangdong Province. Targeted training of ASR transcription engine will produce effect, but the training cost is high, and it is not suitable for small‐scale training with multiple dialects and frequencies. The complaint problems in the customer service field have obvious clustering and are suitable for few‐shot and multi‐frequency training. In view of this, in the actual engineering application, the method of ASR transcribed into the dialect error correction thesaurus is tried to be used to replace the wrong words, and have achieved good results. The optimization technology after automatic speech transcription proposed in this study can improve the recognition accuracy of general ASR by 13.75% for dialect words.

Chatbot Improves the Customer Service in Four Important Industries

Chatbot was first introduced in 1966. With the development of Artificial Intelligence for decades, the function and usage of Chatbot have been enhanced to a very high level. In this paper, we are going to talk about how the use of Chatbot improves the customer service in four industries: healthcare, advisory, commercial, and education. They are the four important social fields, and they all have very large demands and uncountable customers every day. The human agents are facing tons of customers from various backgrounds. They need the help from artificial intelligence. Apart from that, we will also discuss some special advantages of AI-based chatbots which them work so effectively in customer service. These three advantages are automation, trust, and productivity. With the combination of these advantages, chatbot can be highly supportive in the field of customer service and improve the quality of customer service. Eventually, we will talk about some challenges the chatbots are facing now, and how to make it function better in customer service to meet more users’ expectations.

Образовательный и профессиональный выбор рабочей молодежи сервисных отраслей

The relationship between education, profession and social status in the modern global world is not obvious. A high level of education does not guarantee a professional career. The discrepancy between professional education and occupation is especially acute in the field of customer service. On the one hand, it reduces the quality of services provided and, on the other hand, causes tension among workers of this industry. The aim of the research is to study educational values, the choice of an educational trajectory and professional self-determination of modern working-class youth in the service industry. The article is based on the materials of an empirical study using quantitative and qualitative sociological methods: a mass survey of working-class youth in the Ural Federal District and a biographical interview, the informants of which are employed in the real sector of the economy and the service sector. The contradictory attitude of young service workers to education was revealed: not seeing the connection between the level and quality of education and the characteristics of their own life, young people are confident in the value of education and maintain a respectful attitude towards educated people. The personal significance of education for the new generation of working-class youth is small; the social prestige of education does not in any way affect personal life plans, including the professional choice. The established relationships between the educational and professional choice of working-class youth - the basic layer of the social structure of any society - can be used to organize vocational guidance work in secondary school, and can be in demand by the state and regional authorities of vocational education.

Analysis of Customer Satisfaction with the Quality of Energy Market Services in Poland

Environmental protection, sustainable development, quality, and value have become the goals of societal development in the twenty-first century. As the core of environmental protection, the new energy sector has become a widespread trend. In this article, we will look at how well and how satisfied customers are with the energy market’s service. A literature review of energy sector quality and value issues was conducted. The survey was conducted in 2021 in Poland with over 2404 respondents by the CAWI survey. Additionally, it was given a qualitative analysis. In the next step, we applied selected quality management methods and tools. The results of the study clearly show that the respondents expect energy companies to become more involved in building customer–enterprise relationships. Research shows that employees of energy companies should be trained more often in the field of customer service, especially in terms of an individual approach to the customer, which has value for the customer. The authors propose ways to build an arrow diagram to increase customer satisfaction levels. A model of elements determining quality as well as value for clients in the energy market was built.

Pengaruh Strategi Penjualan Buku melalui Akad Khiyar terhadap Kepuasan Konsumen (Studi Kasus pada Toko Buku H. Minan Babat Lamongan)

In an effort to improve good customer service, sellers must have the ability and must be able to create a sense of responsibility to consumers in order to create good expertise in the field of customer service. By holding a khiyar contract, consumers will feel satisfied because they can choose the desired product and do not feel disadvantaged. The method used in this study is a quantitative experiment with the formulation of the problem "How is the implementation of the book selling strategy on consumer satisfaction?" Then the second problem formulation is "How does the strategy of selling books through the khiyar contract affect consumer satisfaction?" As for the results of the research: first, that the H. Minan bookstore always provides good service to its consumers by giving time to choose the desired items. Second, that the influence of the book selling strategy through the Khiyar contract is quite large on consumer satisfaction at the H. Minan Babat Lamongan store. Because based on simple regression analysis Y = 3.236 + 0.824 X. The value of 4.06 is the constant value (a). The value of 0.824 is a regression coefficient, which means that any addition of 1. large enough to customer satisfaction.

The methodology and methods of sociological monitoring of communities of working youth in social networks

The article is devoted to the generalization of the experience accumulated by our research group in the research of virtual communities of the working youth (2019-2021). The purpose of the article is to construct a comprehensive methodology for the socio-logical monitoring of social networks of the working youth. The main research objectives were: to analyze modern approaches to conducting monitoring research (including on the Internet); based on the methodology of discourse analysis, to consider the use of methods of frequent and infrequent content analysis for processing the collected information in monitoring mode; to present the stages of monitoring communities of the working youth in social networks, using the example of research conducted within the framework of the project Life strategies of young people referring to the new working class in modern Russia. As a part of the empirical data analysis, the results of a study of virtual communities and social networks groups of the Russian working youth in the field of customer service in the VKontakte social network, carried out in 2021 (6 virtual communities, 133 text posts and the most popular memes) are presented in detail. The stability of thematic categories of virtual group communication in comparison with previous studies and the presence of group identity among Russian working youth referring to the custom service sphere. Conclusions are made regarding the preference of a non-automated approach to the collection and analysis of social network content; about the validity of using the methodology of discourse analysis and content analysis methods for the research of youth social networks in the mode of sociological monitoring.

ТРУДОВЫЕ ОТНОШЕНИЯ РОССИЙСКОЙ РАБОЧЕЙ МОЛОДЕЖИ КЛИЕНТСКОГО СЕРВИСА

The object of the research is the shift of the theoretical accents of the main focus of the analysis from the consideration of an integral system of labor relations in the field of industrial production to the analysis of "deformed" labor relations in the field of customer service, which has occurred in the last decade. The thesis on the prospects of turning to a new interdisciplinary approach, synthesizing the provisions of neo-Marxist (conflict) and cultural approaches in the analysis of labor relations in organizations in the field of customer service is considered. This article aims to consider the specifics of the content of labor relations in the field of customer service, based on empirical studies carried out with the participation of the author within the framework of the project “Life strategies of young people – the new working class in modern Russia” in 2018-2021. The author uses general scientific and special research methods, including sociological analysis of quantitative (mass questionnaire-based survey) and qualitative (focus group and biographical interview) data. The data obtained in customer service organizations allow us to draw conclusions about the informal nature of labor relations, the absence of trade unions, collective bargaining and solidarity among service sector workers, practices of irregular working hours due to the presence or absence of customers and strict control of emotions and labor operations of working personnel by the employer. With the beginning of the pandemic period in 2020, the risks associated with their dismissal, unpaid leave, shorter working hours, etc., have significantly increased for young workers employed in customer service organizations. The results of the study may be useful to public authorities for the development of a socio-economic program to support employment and the effective use of labor resources in the field of customer service.

Justice and solidarity in the perceptions of working-class youth in service industries

The modern approaches to the concepts of solidarity and justice that are basic for society have been examined in the article. In the Russian intellectual tradition, solidarity practices were considered within a moral and axiological dimension. The purpose of the article is to demonstrate the specifics in the perceptions of new working-class youth involved in service sector of the economy of social justice and solidarity, interconnection of class self-awareness and corporate solidarity practices. The article contains an analysis of the original empirical material obtained by the implementation of qualitative sociological research tools. The object of the study was the working-class youth employed in the service sector of the economy, both in the field of customer service and in the infrastructure field of industrial production. Novelty of the article lies within generalization of this youth’s perceptions of justice, types and forms of solidarity. The research yielded such conclusion that the most significant and recognized issues of justice and solidarity for the working-class youth are in the field of industrial relations. As it was revealed during the research, the youth of the service sector is objectively vulnerable to the highest precarity of industrial relations. However, its actual dangers have not yet gained enough recognition of public consciousness and are not studied by Russian sociologists. Issues of the first employment of the youth, discrepancy between professional qualifications and labor markets, intergenerational crisis in industrial relations remain the most acute problems of justice. The respondents view solidarity as relations in a particular workforce, usually in a passive manner; the awareness of class solidarity is virtually nonexistent. The working-class youth demonstrates indifference towards political forms of solidarity and to political life.

Key technologies of artificial intelligence in electric power customer service

As the demand for customer service continues to increase, more companies are attempting to apply artificial intelligence technology in the field of customer service, enabling intelligent customer service, reducing customer service pressure, and reducing operating costs. Currently, the existing intelligent customer service has a limited degree of intelligence and can only answer simple user questions, and complex user expressions are difficult to understand. To solve the problem of low accuracy of multi-round dialogue semantic understanding, this paper proposes a semantic understanding model based on the fusion of a convolutional neural network (CNN) and attention. The model builds an “intention-slot” joint model based on the “encoding–decoding” framework and uses hidden semantic information that combines intent recognition and slot filling, avoiding the problem of information loss in traditional isolated tasks, and achieving end-to-end semantic understanding. Additionally, an improved attention mechanism based on CNNs is introduced in the decoding process to reduce the interference of redundant information in the original text, thereby increasing the accuracy of semantic understanding. Finally, by applying the model to electric power intelligent customer service, we verified through an experimental comparison that the proposed fusion model improves the performance of intent recognition and slot filling and can improve the user experience of electric power intelligent customer services.

Power Intelligent Customer Service Robot Based on Artificial Intelligence

With the rapid development of speech recognition technology, voice chat robot has become a breakthrough of artificial intelligence. Voice chat robot should be a typical application field of customer service, providing customers with efficient and convenient service all day. The traditional customer service center is mainly based on telephone service, facing the problems of large number of customers, high maintenance cost, slow knowledge update, limited service time, low training cost and so on. So, at the same time, the use habits of customers have also changed fundamentally. The vast majority of services and transactions can be carried out through the Internet, such as Taobao and Jingdong. However, the quality and cost of voice services can be greatly reduced through the interaction between robots and channelization voice service centers. Through the research and development of natural language technology, an intelligent and centralized mobile communication service application platform is constructed by using we-chat platform. Through natural language processing, machine learning, big data computing and other technological innovation, we focus on the use of online robot recognition to understand customer problems and timely feedback customer needs. The results show that in the statistics of customer service machine problems, the highest proportion of consumers’ problems about payment is 37%, and the lowest is 29%.

Retrieval Based Chatbot on Tarumanagara University With Multilayer Perceptron

Natural Language Processing or NLP is a branch of Artificial Intelligence that focuses on processing language. One of the implementation of NLP is in the field of customer service in the form of chatbots. Tarumanagara University itself already has a customer service called Admission Tarumanagara. Admission can be contacted by telephone or sending an e-mail message. Making Chatbot will add ways to get information about Tarumanagara University. Chatbot is a computer program based on artificial intelligence that can simulate conversations between people. The system created is a Retrieval Based Chatbot system that can recognize user questions and answer user questions directly. Making a chatbot system will use a model with the Multilayer Perceptron method. The process for the system will go through two stages, namely the preprocessing stage and the introduction stage. The preprocessing stage consists of case lowering, tokenizing, and stemming. After that the model is made and the introduction phase of the trained model is carried out. Chatbot that has been made can be accessed using the LINE application via LINE ID @764vvcfm.

Implementasi Maqashid Syariah Dalam Pelayanan Custumer Service Bank Syariah (Studi Pada BNI Syariah KC Medan)

AbstractMaqashid al-sharia consists of two, namely maqaṣid and sharia. Maqashid means intention or purpose. The purpose (maqashid) can be achieved by means of taklif, and its implementation depends on the ability to understand the main sources of law, both Al-Qur'an and hadith.The purpose of this research with the title the implementation of maqhasid sharia in services at Bank Negara Indonesia Syariah Medan Branch is to see the implementation of services in Islamic banking in the field of customer service. The research was conducted at BNI Syariah Medan. This type of research is descriptive qualitative. Data collection methods in the research are using library research, observation and interviews. The sampling technique used random sampling. The types of data used in this study are primary and secondary data. The data analysis used in this study was descriptive by using literature studies in the form of muamalah fiqh books.The results showed that the implementation of maqashid sharia in services at Bank Negara Indonesia Syariah Medan Branch is appropriate, based on the indicators of educating the individuals (Tahzibul Fardh), upholding justice (Iqamah al-adl), and achieving prosperity (Maslahah).Keywords: Service, Maqashid sharia, Customer Service

Generating and Analyzing Chatbot Responses using Natural Language Processing

Customer support has become one of the most important communication tools used by companies to provide before and after-sale services to customers. This includes communicating through websites, phones, and social media platforms such as Twitter. The connection becomes much faster and easier with the support of today's technologies. In the field of customer service, companies use virtual agents (Chatbot) to provide customer assistance through desktop interfaces. In this research, the main focus will be on the automatic generation of conversation “Chat” between a computer and a human by developing an interactive artificial intelligent agent through the use of natural language processing and deep learning techniques such as Long Short-Term Memory, Gated Recurrent Units and Convolution Neural Network to predict a suitable and automatic response to customers’ queries. Based on the nature of this project, we need to apply sequence-to-sequence learning, which means mapping a sequence of words representing the query to another sequence of words representing the response. Moreover, computational techniques for learning, understanding, and producing human language content are needed. In order to achieve this goal, this paper discusses efforts towards data preparation. Then, explain the model design, generate responses, and apply evaluation metrics such as Bilingual Evaluation Understudy and cosine similarity. The experimental results on the three models are very promising, especially with Long Short-Term Memory and Gated Recurrent Units. They are useful in responses to emotional queries and can provide general, meaningful responses suitable for customer query. LSTM has been chosen to be the final model because it gets the best results in all evaluation metrics.

Logistics customer service in retail trade enterprises large format

The article discusses the process of logistic customer service in large-scale retail businesses. It presents its purpose, stages and tasks, applied criteria and documents, as well as the responsible persons and contractors for particular tasks. The implementation of the adopted topic took place through: determining the current state of knowledge in the field of logistic customer service, the characteristics of the logistics system in the surveyed commercial units, and the identification and description of the activities carried out there in the field of customer service. The applied research method was a critical review of the subject literature and direct observation.