Customer Intelligence

Customer retention is the maintenance of long-term customer-company relationships through customer satisfaction thereby creating loyalty. Value co-creation is proven to have a significant role in creating customer loyalty, so that customer loyalty becomes actual retention for the company. The role of shared value creation should be considered in customer relationship mechanisms. This study aims to produce an analysis of the role of value co-creation behavior on customer retention. This focus is novelty in research, because no confirmation was found in previous studies that produced a relationship between the two. Customer loyalty is the variable that mediates the relationship between value creation behavior and customer retention. This research produces findings regarding the positive influence of customer involvement through value co-creation behavior on retention as a long-term customer relationship mechanism with the company.  Keywords: value coreation behaviour; customer loyalty...

This thesis examines digital customer experience from a customer perspective. While different companies are at different phases of the digitalization, there have been several digitalization frameworks proposed by academics and the industries based on researching these companies. One key or core element in digitilisation frameworks proposed by these research studies is “UNDERSTANDING” the customer. Companies have therefore substantially invested in infrastructure to collect customer indirect data to understand the customer. However, there is no view or research on customers own perspectives and experiences. For example, how customers feel going through this digital transformation and the impact the availability of digital technologies has on their behaviours , actions and experiences. This thesis examines and review the patterns of these industry frameworks (referred to in this document as the organisational perspective) to validate the different findings in earlier studies. More imp...

Purpose: The purpose of this study is to experimentally test the hypothesized Three-Part Theoretical (TPT) Framework in order to evaluate the impact of the Artificial Intelligence enabled Service Robot, MAYA, among rural banking customers in exploring Customer Loyalty through Customer Satisfaction. The study is based on the Diffusion of Innovation Theory (DOI) and aims to confirm the implementation of such advanced technology in rural banking. Methodology: Multi-Stage Cluster sampling method was adopted to collect the responses from the 385 through Triangulation technique from customers across the rural banking customers across Southern States of India within age group between 21 -50 years. SAS and Smart PLS 4 were used to apply Simple Percentage Analysis, and Structural Equation Modelling to validate the hypothesis. The key constructs are System Feature, Customer Feature, System Encounter feature, Customer Satisfaction & Customer Loyalty. Results: System feature, Customer feature of the Service Robot, MAYA have a direct positive influence on the Customer Satisfaction but System Encounter feature has a direct negative influence on the Customer Satisfaction. Customer Satisfaction has a direct positive influence on Customer Loyalty with higher predictive capacity. Implications: The benefits of using service robots include increased efficiency, improved safety, and reduced labour costs. It offers personalized assistance to customers, guiding them through the banking process and answering their queries. These findings of the study will facilitate banking managers to enhance rural marketing.

Purpose: The purpose of this study is to experimentally test the hypothesized Three-Part Theoretical (TPT) Framework in order to evaluate the impact of the Artificial Intelligence enabled Service Robot, MAYA, among rural banking customers in exploring Customer Loyalty through Customer Satisfaction. The study is based on the Diffusion of Innovation Theory (DOI) and aims to confirm the implementation of such advanced technology in rural banking. Methodology: Multi-Stage Cluster sampling method was adopted to collect the responses from the 385 through Triangulation technique from customers across the rural banking customers across Southern States of India within age group between 21 -50 years. SAS and Smart PLS 4 were used to apply Simple Percentage Analysis, and Structural Equation Modelling to validate the hypothesis. The key constructs are System Feature, Customer Feature, System Encounter feature, Customer Satisfaction & Customer Loyalty. Results: System feature, Customer feature of the Service Robot, MAYA have a direct positive influence on the Customer Satisfaction but System Encounter feature has a direct negative influence on the Customer Satisfaction. Customer Satisfaction has a direct positive influence on Customer Loyalty with higher predictive capacity. Implications: The benefits of using service robots include increased efficiency, improved safety, and reduced labour costs. It offers personalized assistance to customers, guiding them through the banking process and answering their queries. These findings of the study will facilitate banking managers to enhance rural marketing.

Customer Relationship Management (CRM) is a much-used phrase in the current business environment. It is promoted as a strategy to attract and retain profitable customers. The model grew out of the realisation that customer loss and the subsequent attraction of new customers is an ever increasing corporate cost; the need to improve customer retention; and a recognition of the value in increasing the share of each customer's business in organisations. Each of these is relevant to the delivery of information services in University libraries. Taking CRM one step further is the Peppers & Rogers "1:1 enterprise" i model of customer driven service. The traditional aggregate market approach focuses on one product or service at a time, and then tries to find as many customers as possible who want that specific need satisfied, for example reference services in university libraries. This is the manner in which most university libraries have operated. The customer driven approach focuses on one customer at a time, with the aim of satisfying as many of that particular customer's needs as possible. Griffith University Brisbane, Australia is developing 1:1 learning relationships ii between the university's academic staff and Information Services staff to create a new customer service dynamic. Customer-driven competition and 1:1 marketing is more usually regarded as a prerequisite for commercial success. At Griffith our customers and our Information Services staff are together redefining what it means to participate in partnerships and alliances that will ultimately benefit the teaching/learning process, the students, and the whole university as it creates a market position of strength. This paper will demonstrate that the "1:1 relationship" principles can deliver enhanced service partnerships and efficiencies in a University Library and Information Service environment. It will also demonstrate the applicability of a model that was developed for the commercial world to a not-for-profit service environment. Building strong and focussed customer relationships will strengthen the leadership position of academic libraries in the delivery of information services and information technology, and especially in building ongoing relationships for the benefit of the teaching/learning process.

Customer education is one type of customer engagement. Through the active involvement of customers in the value creation process, customer education can give a business a competitive advantage. Using social network analysis (SNA) and text analysis, this study examines user interaction and information sharing about two Indonesian e-commerce sites on Twitter in relation to customer engagement and customer education. Text data was scraped from Twitter from November 1 to December 31, 2022 and processed using Gephi and Orange software. This study found that the data successfully shows that both official accounts of two Indonesia e-commerce become the most influential accounts that share information about products and services and also play a role in educating their customers regarding the buying process, promotions, and solutions on their social networks. SNA and text analytics can be used as tools to see customer engagement and improve customer education strategies for e-commerce to reach a competitive advantage. For further research, it is recommended to examine the same or different objects but use data sources from different social media, such as from Instagram and Facebook.

In this paper, a novel K-means clustering algorithm is proposed. Before running the traditional Kmeans, the cluster centers should be randomly selected, which would influence the time cost and accuracy. To solve this problem, we utilize density distribution analysis in the traditional K-means. For a reasonable cluster, it should have a dense inside structure which means the points in the same cluster should tightly surround the center, while separated away from other cluster canters. Based on this assumption, two quantities are firstly introduced: the local density of cluster center ρi and its desperation degree δi, then some reasonable cluster centers candidates are selected from the original data. We performed our algorithm on three synthetic data and a real bank business data to evaluate its accuracy and efficiency. Comparing with Traditional K-means and K-means++, the results demonstrated that the improved method performs better.

The hardest part of making the transition to a customer-based organization is the first few steps. This paper shows how to:  Identify internal and external customers.  Identify metrics to measure performance within the organization.  Use transactions to ease the path to the new paradigm.  Use transactions to minimize the resistance to change.  View an organization as having two sets of internal customers, namely: o Vertical - the traditional reporting path in which the customer is the supervisor. o Horizontal - the production process path in which the customer is the next link in the production process. This customer may be internal or external.  Set up evaluation criteria to measure the effectiveness of the person in dealing with their customers.  Set up a reward and recognition system to reinforce the new paradigm  Identify and eliminate non-value added transactions.

Persaingan bisnis yang semakin kuat dan banyaknya perusahaan distributor ban di setiap daerah, membuat para pemilik usaha berusaha memberikan layanan jasa dan harga yang murah untuk mempertahankan pelanggan. Hal ini dikarenakan bahwa mempertahankan pelanggan jauh lebih sulit dibandingkan dengan mencari pelanggan baru, namun terdapat beberapa permasalahan terkait pengolahan data pelanggan dimana perusahaan kesulitan mengatur data pelanggan, penyebaran informasi promo dan kontak pelanggan tidak lengkap maka permasalahan inilah yang membuat perusahaan kesulitan dalam mempertahankan pelanggan yang potensial bagi perusahaan. Sistem yang dapat mengelola, menyajikan data pelanggan dan promosi sehingga perusahaan mengetahui pelanggan tersebut termasuk pelanggan potensial bagi penjualan atau tidak, menjadi hal yang diperlukan saat ini. Data pelanggan yang terorganisasi dengan baik dan dapat menampilkan peluang di setiap penjualan menjadi tujuan penelitian ini, sehingga dirancanglah sistem Analytical Electronic Customer Relationship Management (CRM) untuk lebih mempermudah, mencatat dan memilih data selama proses penjualan serta membantu dalam membina hubungan dan kepuasan pelanggan. Hasil penelitian ini adalah rancangan sistem Analytical e-CRM yang diimplementasikan dalam sebuah aplikasi.

PT Dirgantara Indonesia (PTDI) bergerak di bidang rekayasa, manufaktur produksi untuk kepentingan komersial dan militer yang berhubungan dengan kedirgantaraan, termasuk  perawatan peralatan barang. Seiring dengan perkembangannya, PTDI tidak hanya memproduksi berbagai pesawat tetapi juga helikopter, menyediakan pelatihan dan jasa pemeliharaan (maintenance service) untuk mesin-mesin pesawat dan peralatan lainnya. PTDI juga pernah menjadi rekanan sub-kontraktor untuk industri-industri pesawat terbang besar di dunia seperti Boeing, Airbus, General Dynamic, Fokker dan lain sebagainya. Metrology merupakan bagian yang bertugas dalam melakukan pelayanan dan service  dalam perbaikan dan pemeliharaan mesin atau peralatan barang yang sering digunakan dalam proses pembuatan pesawat tersebut. Metrology pada saat ini dirasa belum  dapat memaksimalkan strategi dalam menangani aktivitas yang berhubungan dengan pelanggan dimana sistem yang membantu perusahaan khususnya pada bagian metrology  dalam m...

The research focuses on the impact of customer engagement on overall sales and efficiency via the role of sales personnel which act as a variable in the study. The overall efficiency of stores and vendors in the apparel industry is mostly impacted by their consumer's loyalty and their brand image. The research presents multiple initial hypotheses which firstly include whether the actions of sales personnel have an impact on customer loyalty and customer involvement via customer engagement. Secondly, overall business sales are positively influenced by customer loyalty. And third, customer engagement has a dependent relation on customer involvement and customer participation. The methodology of the undertaken study is based on on-site surveys which include individuals from the industry including both vendors and the consumers through a questionnaire based on general information and opinionated queries regarding the experience of consumers and the impact vendors feel. The obtained results were filtered for processable entries and processed through SPSS to obtain a statistical end-result which determined the validity of the studied hypotheses.

PurposeThe purpose of this paper is to examine how, taking customer relationships as the unit of analysis, the heterogeneity of customer relationship performance influences the heterogeneity of firm performance, and how firms can balance the heterogeneity of customers, customer relationships, and customer portfolios by differentiated business models.Design/methodology/approachThe approach to the topic is one of theoretical analysis and conceptual development.FindingsValue capture is defined as the discounted present value of all future economic profit from the relationship. Three sources of value capture heterogeneity are identified: the customer, the relationship with the customer, and the interdependence between customers in a customer base. Relationship performance can be improved by investing in business model differentiation, in order to facilitate controlled adaptation to specific customer relationships and/or customer portfolios. Firms have to manage parallel business models ...

Start your The GOJEK is an application that can be operated through supporting facilities, namely smartphones. The existence of several quality applications that are perceived by these customers is expected to provide a satisfaction to customers, so that customers will remain loyal to use the GOJEK application. This study aims to analyze the satisfaction of GOJEK application users. This study uses a systematic review through:1) search using an indexing site (google scholar) with the specified keyword, 2) the literature obtained through indexing site then limited with certain categories, 3) the literature then selected with certain inclusion and exclusion criteria. Based on the results of analysis, it was found that service quality and trust affect user satisfaction of the GOJEK application. Service quality includes ease of use of the application because it is easy to learn, easy to understand, simple and easy to operate. In addition, it is very quickly accessed, so this is very beneficial for customers. Besides, the price and the product also affects the satisfaction such as the ease in the transaction process and the fulfillment of consumer needs and desires. GOJEK application development companies need to pay attention to quality, trust, price and product factors in creating customer satisfaction.

The online purchase intention is very critical and fascinating in today’s e-environment. It has direct involvement in customer decision making in terms of purchase. Thus, corporations use various marketing tools to seize customer attention for product purchase decision. This study provides the model of customer experience and purchase intention in e-environment. A total of 326 internet users were requested to provide the data through distributed questionnaire using non-probability e-convenience sampling technique. Further, Analysis of Moment Structure was employed and Structural Equation Model was used to measure the model of customer experience and online purchase intention with customer experience sub-dimension i.e. online hedonic elements, online aesthetics and online functional elements. The result of the study clearly indicates that customer with tremendous experience tends to purchase frequently in an online environment. In other words, customer online experience is directly p...

The main aim of the study is to examine the role of artificial intelligence (AI) on Enhancing Customer Experience in Palestine through different industries, such as banks and telecommunication companies. Interviews and a structured questionnaire were the primary data of this study. The results of the study revealed that there is a positive significant relationship between AI and Customer Experience. AI explained 26.4% of the variance of the customer experience (R²=0.264, F (1,89)=28.634, P < 0.05). Customer Experience has two dimensions; Customer service and after-sale support, the study shows that AI predicted 22.9% of the variance of customer service, whereas it predicted 7% of After-Sale Support. Moreover, providing Personalized Customer Service throughout the customer's buying journey has a great impact on customer experience. The study recommends enterprises to offer more personalized services for customers which it influences their overall experience with the enterprise. Likewise, it's highly recommended to employ AI in call centers and the other after-sales support services to shortening the customers waiting time.

Today, technology helps retailers integrate various In-Store techniques to understand their customers better. In-Store Analytics has been in use in the retail industry for a long time, where retailers administer their Customer Analytics manually. The purpose of this study is to carry out a detailed review of existing literature on concepts of customer experience (CX) and In-Store Analytics. The authors used secondary sources of collecting data obtained from existing researches, and articles published on In-Store Analytics. This study reported that the implementation of In-Store Analytics should meet organization needs such as insight creation, market optimization, CX improvement, category and pricing optimization, performance management, and sales improvement.

With the increasing competition in the market today, the customers have a variety of options to choose from. The biggest challenge faced today by any business is to understand and deliver the exact requirements of the customers to retain the existing customer base and acquire new customers. The key to this is meeting and surpassing customer expectations leading to the goal of customer satisfaction through enhanced customer experiences. Upcoming technologies like Artificial Intelligence provide widespread opportunities to understand dynamic customer behavior and trends. However, not much exploration is done in academic research as to what factors primarily impact customer experience and the emerging significance of AI in this domain. Hence, the objective of this study is to understand the impact of artificial intelligence on customer experience. The paper adopts a quantitative approach wherein a survey was conducted across 207 participants to understand the impact of AI-enabled chatb...

Banks play a vital role in the socio-economic development of our country. Banks offer several facilities to enhance the standard of living of our citizens. In the past, owing to lack of information and proper guidance, the general public could not avail the full benefits from the banking industries to improve their standard of living. It is now undeniable that the face of the Indian consumer is changing. This is reflected in the change in the income pattern of the urban household. The direct fallout of such a change will be the consumption patterns and hence, the banking habits of Indians, which will now be skewed towards retail-products. At the same time, India compares pretty poorly with the other economies of the world that are now becoming comparable in terms of spending patterns with the opening up of our economy. Customer service management is a key component of business today. The concept is very crucial as it incorporates customer, customer service, customer satisfaction, customer value, customer loyalty, customer retention, etc. In one word, it is linked to Customer Relationship Management (CRM) and Customer Experience Management (CEM). So far as jargons are concerned, more or less relationship Marketing, CRM and customer service management are interchangeably used. Relationship Marketing attracts maintains and enhances customer relationship

Data mining is a useful and powerful tool for any organization especially for marketing people. Data mining is used in managing relationships with customers. New trends in customer relationship management -CRMhave growth. One of them is social customer relationship management -sCRM-. The major problem here is data accessibility. If the research process is not started from inside the organization, the researchers cannot have access to customer's data. In this research paper, the research creates a survey to find out available customer's data sets that can be used in academic research. In addition, the research reviews basic concepts of CRM and Data Mining Techniques. Finally, the research focuses on current challenges of mining customer's data from business perspective and analytical customer relationship management -aCRM-.

This study aims to examine the impact of Corporate Social Responsibility (CSR) image on customer satisfaction in the context of the banking sector of Pakistan. Further, the intervening role of customer trust and customer loyalty in the relationship between CSR image and customer satisfaction is also examined. Design/Methodology/Approach: Present research is quantitative in nature and collects the data through structured questionnaires. By employing the Smart PLS technique to test the proposed hypothesis. Findings: This study reveals the following salient findings: 1) the response of CSR image to customer satisfaction is positive (p<0.01); 2) customer trust and customer loyalty both significantly mediates the impact of CSR image on customer satisfaction. Implications/Originality/Value: Based on novel findings, the current study will help the organizations to realize the significance of CSR practices to enhance the customers' satisfaction level.

In today’s digitally connected world, understanding consumer sentiment has become critical for brands aiming to cultivate loyalty and inspire advocacy. With the exponential growth of user-generated content across social media and online platforms, traditional methods of gauging customer satisfaction and engagement have become insufficient. This paper explores the role of AI-driven sentiment analysis as a strategic tool for predicting and enhancing consumer brand loyalty and advocacy. By leveraging natural language processing (NLP), machine learning, and deep learning techniques, sentiment analysis allows businesses to extract emotional insights from large volumes of unstructured data. The study examines how this technology enables organizations to identify patterns in consumer behavior, detect early indicators of brand loyalty, and pinpoint potential brand advocates. Through a review of existing literature, case studies, and industry applications, the research highlights the practical implications of integrating sentiment analysis into brand management strategies. Findings suggest that AI-powered sentiment tools not only improve the accuracy of consumer insights but also enable real-time responsiveness, fostering stronger customer-brand relationships. Additionally, the paper discusses ethical considerations, challenges in sentiment interpretation, and the need for contextual sensitivity in AI models. Ultimately, this research contributes to the growing field of AI in marketing by demonstrating how sentiment analysis can serve as a predictive mechanism for long-term brand success.

By considering the intense competitiveness and prevalent challenges in the current business environment, organizations can’t survive just focusing on attracting and capturing new customer but they have to choose the strategy that help in retaining the existing customers and enhanced their loyalty to the organization. So, in the customer service based industry, satisfied customers are no longer suitable, and the businesses have to explore the new ways to flourish and promote the loyalty of customers. The current study hypothesize that customer loyalty is significantly affected by the customer satisfaction and trust of the customers. Whereas, perceived value and service quality is important determinants to create the customer satisfaction and trust. The data was collected from different customers of various banks and the hypothesize links are tested. Results indicate that there is a significant relationship between customer satisfaction and trust with customer loyalty. It is also conf...

Customer eXperience is a blue print of customer requirements. In this era of heightened competition and volatile global economy, delivering services originating from diverse sources, without satisfying thorough customer experience practices may increase customer dissatisfaction, and churn rate. In order to guarantee rich customer experience, the service delivery mechanism should shift towards customer experience centric approach. This shift from service to experience brings customer in the driving seat, whose intentions and needs trigger service delivery. This paper introduces ontological model for customer experience, intended for use in run time environments by policy based management systems, to initiate and enable service delivery based on customer experience. The work presented here can have valuable implications for future studies of customer experience based service delivery approach.

This research evaluates the effect of customer relationship management (CRM) on customer knowledge and customer satisfaction. An analysis of archival data for a cross-section of U.S. firms shows that the use of CRM applications is positively associated with improved customer knowledge and improved customer satisfaction. This article also shows that gains in customer knowledge are enhanced when firms share their customer-related information with their supply chain partners.

Objectives: This research aimed to identify the factors that influence the effective adoption of supply chain management systems, specifically focusing on customer satisfaction in the context of Saudi Arabia. Methods: Data was collected through convenience sampling, targeting a proposed sample size of 1000 individuals representing diverse nationalities and areas. A total of 629 valid responses were obtained. Path analysis was conducted using the Structural Equation Modeling (SEM) method and the AMOS 21 analytical tool. Findings: The results of the analysis showed a reasonably good fit between the model and the data, as indicated by the following statistics: Chi-square (2701.069), Chi-square / DF (5.204), RMSEA (0.042), PCFI (0.757), and TLI (0.848). The findings confirmed all hypothesized relationships, except for the relationships between customer expectations and customer satisfaction, as well as perceived quality and customer satisfaction, which lacked significant statistical associations. Additionally, the study revealed that customer expectations strongly predict perceived performance, perceived performance strongly predicts customer satisfaction, and customer satisfaction strongly predicts customer retention. Novelty: The research provides novel insights into the factors influencing the adoption of supply chain management systems and their impact on customer satisfaction and retention in the Saudi Arabian market. The study also highlights the relationships between customer expectations, perceived performance, customer satisfaction, and customer retention, contributing to the existing body of knowledge in this field. Implications: These findings have practical implications for decision-makers, offering guidance for enhancing the successful implementation of supply chain management systems. By improving customer satisfaction and retention, businesses can refine their product and service quality, ultimately leading to customer referrals and potential client acquisition. Overall, the study emphasizes the importance of adopting efficient supply chain management systems in achieving customer

Objectives: This research aimed to identify the factors that influence the effective adoption of supply chain management systems, specifically focusing on customer satisfaction in the context of Saudi Arabia. Methods: Data was collected through convenience sampling, targeting a proposed sample size of 1000 individuals representing diverse nationalities and areas. A total of 629 valid responses were obtained. Path analysis was conducted using the Structural Equation Modeling (SEM) method and the AMOS 21 analytical tool. Findings: The results of the analysis showed a reasonably good fit between the model and the data, as indicated by the following statistics: Chi-square (2701.069), Chi-square / DF (5.204), RMSEA (0.042), PCFI (0.757), and TLI (0.848). The findings confirmed all hypothesized relationships, except for the relationships between customer expectations and customer satisfaction, as well as perceived quality and customer satisfaction, which lacked significant statistical associations. Additionally, the study revealed that customer expectations strongly predict perceived performance, perceived performance strongly predicts customer satisfaction, and customer satisfaction strongly predicts customer retention. Novelty: The research provides novel insights into the factors influencing the adoption of supply chain management systems and their impact on customer satisfaction and retention in the Saudi Arabian market. The study also highlights the relationships between customer expectations, perceived performance, customer satisfaction, and customer retention, contributing to the existing body of knowledge in this field. Implications: These findings have practical implications for decision-makers, offering guidance for enhancing the successful implementation of supply chain management systems. By improving customer satisfaction and retention, businesses can refine their product and service quality, ultimately leading to customer referrals and potential client acquisition. Overall, the study emphasizes the importance of adopting efficient supply chain management systems in achieving customer

Google Play Store is where a wide variety of applications are available, whether paid or not. Google Play Store page is a place for application users to express opinions, reviews and ratings. Ruang Guru, Zenius and Quipper are available on the platform. Analysis was carried out using sentiment analysis and SVM algorithm. Data was obtained using data scraping techniques, using help of google-play-scraper library. Web scraping process is divided into 3 stages namely Fetching, Extraction, and Transformation. Data collected is 30,000 data which is divided into 10,000 data for each application. Research begins with data preprocessing stage which includes normalization, case folding, cleaning, tokenizing, and stopwords. then data is divided into 90% training data and 10% test data. Training data is labeled with values 1, 0, and -1. Value 1 means positive, value 0 means neutral and -1 means negative. Results of classification sentiment using SVM show that Ruang Guru has highest positive value compared to Zenius and Quipper. However, user response equally gives a positive value for application. Accuracy value of research shows that sentiment classification data with SVM has an average accuracy for Ruang Guru of 99%, Zenius of 96%, and Quipper of 82%.

The purpose of this paper is to conduct a critical study to examine strategies and effects of sensory and experiential marketing on consumer behavior and increasing company’s sales, together with future prospect of sensory and experiential marketing as new-fangled marketing strategy replacing the traditional strategies. The study is entirely based on secondary research, where literature relating to the subject is reviewed. The findings of the paper conclude that sensory marketing is an innovative marketing tool of the recognition of sensation and perception of the consumers in the forms of perception cognition, emotion, learning, preference, choice, or evaluation. Truly the scope of experience and sensory marketing is rising in the light of transforming socio-cultural environment and developing taking place in the area of technological advancement. Furthermore, experiential marketing is found highly effective in influencing consumer behavior for companies, particularly in terms of r...

Market deregulation and globalization have caused competitive situations across a range of industries to constantly change, which has resulted in a rise in customer attrition. In order to maintain business development and keep their client base, organizations must effectively anticipate and mitigation of customer churns. This study explores the use of machine learning techniques in the Power Bi tool to anticipate client turnover. Emphasis is placed on the incorporation of these features, while focusing on well-known industries like telecommunication, employee churn for developing a predictive model, and features capturing customer social interaction and communications graphs and customer feedback are highlighted in the review. The findings encourage the use of profit-based evaluation criteria to increase profitability, improve customer retention, and support decision-making. Additionally, they draw attention to the dearth of studies on the profitability aspect of churn prediction models. In order to promote further advancements, the research concludes with recommendations that support the usage of ensembles, machine learning techniques, interaction visualization data utilizing Power BI, and explainable methodology. Churn prediction, which identifies customers who are likely to leave for a rival, has become the most important Business Intelligence (BI) application as a result. The purpose of this study is to provide widely used data mining approaches for identifying potential churning customers. These techniques look for patterns in past data that may point to potential churners.

The explosive rise of e-commerce has largely changed shopping habits around the world, and university students are one of the biggest groups to have changed their ways of shopping. In Bangladesh, the change from conventional to digital shopping has been visible with the help of mobile technology, the impact of social media, and also due to the ease of online shopping. The study identifies the drivers of online shopping acceptance among university students in Bangladesh through the lens of theoretical framework based on TAM, UTAUT and TPB. Quantitative method was employed, and the data were collected using simple random sampling from 384 students, determined based on 95% confidence level and 5% margin of error, from three different universities in Bangladesh. The results suggest that the convenience, quickness, and the assortment of the product are the key motivations that drive students to online shopping. Besides, social media networks, mainly Facebook and Instagram, play an incredibly significant role in deciding to buy the students. However, issues like the delay in delivery, high delivery charges, and the question of products' authenticity have proven to be the barriers to the online shopping experience. The research advocates that a reduction in delivery fees, better logistics operations, and providing student discounts will lead to an increase in adoption of e-commerce in Bangladesh. Besides, it is essential to instill customer trust in e-commerce platforms by using secure payment systems and trustworthy products and delivery services.

In the age of technology, continuous innovation is the ultimate motto of the financial sector to attract customers. Firms in the financial sector must be innovative in terms of service quality and operational performance to obtain customer loyalty and gain financial stability. A dearth of studies on customer loyalty and financial performance of Islamic Banks motivated the authors to examine the relationship between customer loyalty and financial performance. The study also explores whether the service qualities have any impact on customer loyalty. The study uses both primary and secondary data to conclude the research objectives. A survey of 356 questionnaires was carried out among the customers of the selected Islamic banks of Bangladesh to gather information regarding customer service quality and customer loyalty, while financial performance data were attained from the annual reports. Moreover, the study follows the SERVQUAL model's five dimensions (tangibles, empathy, assurance, reliability, and responsiveness) to determine the service quality of Bangladeshi Islamic Banks. Rigorous statistical techniques, including exploratory factor analysis, reliability testing, and regression analysis were used to investigate the hypothesis. The study empirically documents a positively significant impact of service quality (tangibles, empathy, reliability, and responsiveness) on customer loyalty, while assurance shows an insignificant relationship. Furthermore, the study does not find any significant relationship between customer loyalty and the financial performance of Bangladeshi Islamic Banks. The findings of the study profoundly denote that the financial performance of Bangladeshi Islamic Banks mostly depends on many other financial and non-financial factors, rather than customer loyalty.

PurposeThe motivation for this study comes from decision making related to strategic marketing orientations in international markets. The authors examine if customer orientation and customer relationship orientation perform as two distinct constructs in driving firm innovativeness, and how together they support business growth among export firms. This study aims to suggest a customer-centric strategy for export firms that drive innovativeness and growth.Design/methodology/approachAn international corporation specialized in company information services provided a list of the contact information of Italian companies. The authors sent an email request to respond to an online survey and received 416 effective responses from firms operating in export markets. The authors propose and empirically test a model in which customer orientation, customer relationship orientation and innovativeness predict business growth. This model controls for the effects of firm size, industry and customer ty...

Creating value and generating a total customer experience (T CE ) is important for E -Commerce in order to attract customers. However, with increasing competition in the marketplace, it is becoming increasingly difficult to retain customers. E -Commerce, therefore, should focus on continuously providing value to the customers to build long-term relationships and reduce customer defections. We have evaluated five E -B anking sites from the UK finance industry and have shown that an organisation whose Web site is usable in HCI terms (that satisfies the Web Design heuristics / E -Commerce guidelines) might not always generate a T CE . It is important that along with usability heuristics, customer relationship management (CR M) strategies are integrated into the design of E -Commerce sites. In this paper, we have applied the service quality (SE R V QUA L ) framework from the relationship marketing literature for deriving customer relationship enhancing heuristics which can be integrated into the design of E -Commerce environments.

The approach of designing for experience has been developed in interaction design and adopted for product design in the recent years. There are scattered efforts on bringing the approach of designing for experience (or user experience design) to the field of industrial goods. There are few companies and research institutions exploring this field. Recent research and practice focused on exploring different approaches and models of designing for experience. One particular approach of Hassenzahl and colleagues stresses the fulfilment of specific basic human needs in order to provoke positive experiences. There is a number of examples applying specific methods for evaluating or measuring product experiences. We report on current research on the transfer and adoption of particular evaluation methods to the field of industrial goods. Industrial goods development is a usually a long-term complex process with many different stakeholders. In this paper we present findings from a series of ex...

This research aims to identify the relationship between customer experience, customer satisfaction, customer trust, and customer loyalty on loyalty tourism destination in Banten Province, Indonesia. This research was conducted using a quantitative approach through an online survey with 299 respondents, with SEM Amos to analyze the data. The results show that customer experience has a positive influence on consume trust, customer satisfaction a positive influence on consumer trust, customer experience has a positive effect on customer loyalty, customer satisfaction a positive effect on customer loyalty and customer trust a positive effect on customer loyalty.

This research aimed to analyze the direct and indirect influence of customer relationship management and brand image on customer loyalty in the marine export department of DSV Transport Indonesia through customer satisfaction. Customer Relationship Management in goods delivery was one of the essential variables to improve company service to satisfy its customers and impact their loyalty. Research with a quantitative approach uses the Path Analysis statistical tool. This research used quantitative methods with a sample of 199 companies. The key findings of this research stated that customer relationship management has a negative and insignificant effect on the satisfaction and loyalty of marine export customers of DSV Transport Indonesia. Thus, the changes occurring in the application of Customer Relationship Management in marine exports would not affect the satisfaction and loyalty of marine export customers of DSV Transport Indonesia. Based on the results of this research, it was s...

The paper reports results of theoretical research aimed at devising methods for representation of experience in computer systems for the purpose of implementing Customer Experience Management (CEM) systems. The paper introduces a novel architecture for modelling customer experience with respect to company, brand, product and its relation to consumer decisions. A process for customer experience approximation is proposed and links to customer decision making are mapped. Experience gaining by a customer has been modelled as a learning process which opens up the way for applying various machine learning algorithms to customer experience emulation. Each customer is represented as an intelligent agent, which reflects the distributed nature of the problem and allows for autonomy of its elements. It is shown how the architecture can be utilised with existing resources e.g. Customer Relationship Management systems as a source of data for CEM.

PurposeThe purpose of this paper is to examine the effect of explanation on customer satisfaction in the service failure stage. It seeks to better understand the dynamics of consumer repurchase intention through a mediating effect of customer satisfaction.Design/methodology/approachA structured questionnaire was e-mailed to collect the primary data. With three reminders, this study managed to obtain 322 responses from customers who complained about their internet service in Malaysia. Structural equation modelling techniques were applied to examine both direct and mediating effects between variables.FindingsResults reveal that all four dimensions of explanation have significant partial mediating effect on repurchase intention through customer satisfaction. Results also disclose that there is no significant relationship between excuse and customer satisfaction in service failure. Among all dimensions, reference and apology have higher influence on repurchase intention through customer...

Nowadays, web shopping is more than selling product. Many web shopping have basic analytics system to analyze customer data, transaction data including demographics, age and gender. They add many features in web shopping to maintain customer loyalty. In this research, we made a web shopping that can analyze customer shopping behavior. We used FM (Frequency and monetary) analysis based on a "transaction" data set. We categorize the customer based on how often they buy, how much they buy and how much the value of purchased item. We use K-Means algorithm to cluster the customer based on their transaction. Analyzing and understanding customers' buying behavior can help the store to know what they are looking for. Therefore, at every customer web page that is in the same cluster will appear recommended products accordance with the transaction that has been done. Recommendation Products are presented is the prediction of the type of goods that may be chosen by the customer. So that the recommendation products that appear on web pages between customers will be different. The data used for this test is "Istana Accessories" store data from January to June 2014. The results show that recommendation product from K-Means algorithm successfully obtained and displayed on the customer page.

Preventing customer churn and trying to retain customers is the main object of customer churn management. This paper proposes a model to measure churn probability and introduces a policy to retain customers. Using existing datasets of customers, we calculated CLV and used the C5.0 technique to predict churn probability for each customer. We also used process mining to find a policy to retain each customer separately. The model was simulated using a super market chain (Refah) and the results show the model is performing much better than previous proposed models. A computer result is shown.

The main problem of this research was that Shopee Express, one of the companies operating in a delivery service provided by an e-commerce platform, faced a significant challenge in keeping its existence and showed a decreased performance. This research empirically examined the influence of service quality and punctual delivery on customer loyalty through customer decision as the intervening variable in the logistic company Shopee Express case study. The sample of this research was the customers of Shopee Express, with as many as 203 respondents using the path analysis method. From the discussion, it was known that there was a significant influence of service quality and punctual delivery simultaneously on customer loyalty through customer decision, and there was a significant influence of customer decisions on customer loyalty. The implication of this research was the importance of Shopee Express Indonesia continuously improving its service quality and punctual delivery to enhance customer decisions and customer loyalty. The key finding of this research could give valuable insight to the company management in developing its strategy to improve customer satisfaction and loyalty.

The insurance market and particularly French Health-Insurers are affected by changes. That require from traditional actors to transform their Customer Experience management. Our paper, which relies on the third French mutual health-insurer, explores Customer Experience Analytics issues. We observed these issues throughout workshops focused on designing Customer Experience. Our observations show analytics based on Customer Journey Application which make use of decontextualized interactions. We approach the fact these analytics must apply the concept of trajectory as primary focus for user engagement. In order to articulate information system and human activity trajectories, we develop the "Contextualizing Artifact". It is grounded on the Context-System-Trajectory theory (CST). That new theory is mandatory to grasp Customer Experience beyond its marketing dimension. As first step of our artifact development we explain how to improve Customer Journey application with a combination of contextual dataset and classification techniques. This proposal relies on Service Interaction pattern (NISPARO) and provides new qualitative analytics.

CRM are practices, strategies and technologies that companies use to manage and analyze customer interactions and data throughout the customer lifecycle. The better a business can manage its relationships with its customers, the better the business will be. CRM can be used as an important strategy to learn more about your customers' needs and behaviors, as well as to develop stronger relationships with them. The study focuses on understanding the need of customer relation in the present-day scenario.

The competitive business landscape surrounding the tourism industry inevitably requires significant attention to be placed on maximising the customer base towards establishing a competitive advantage. In this vein, the use of customer accounting has emerged to be a source of crucial information about the customers, which they could assist the management in decision making, managing, and controlling the operation and in turn improve the organisational performance. Considering that, this study aims to articulate and examine the relationships between customer accounting, customer knowledge, and performance. Based on a survey administered to 112 hotel managers, the practice information was collected and analysed using partial least square (PLS). Findings show that among the four dimensions of Customer Accounting, Customer Profitability Analysis, Valuation of Customer as Assets, and Customer Equity Analysis relate significantly to Customer Knowledge, except for the Lifetime Customer Profitability Analysis. Subsequently, only Customer Profitability Analysis and Valuation of Customer as Assets significantly influenced performance. The finding suggests that the adoption of Customer Accounting consisting of combined data about customers may assist the hotels in making decisions to improve their performance. Given that, this study highlighted an accounting technique, that is, Customer Accounting which should be practised by the operators of Malaysian hotels to allow them to manage their customers better, and which is the determinant toward ensuring business success and sustainability.

Aim/Purpose: This study aims to create customer segmentation who use Online Travel Agent (OTA) mobile applications in Indonesia throughout their hotel booking journey. Background: In the context of mobile hotel booking applications, research analyzing the customer experience at each customer journey stage is scarce. However, literature increasingly acknowledges the significance of this stage in comprehending customer behavior and revenue streams. Methodology: This study employs a mixed-method and exploratory approach by doing in-depth interviews with 20 participants and questionnaires from 207 participants. Interview data are analyzed using thematic analysis, while the questionnaires are analyzed using descriptive statistics. Contribution: This study enriches knowledge in understanding customer behavior that considers the usage of mobile apps as a segmentation criterion in the hotel booking journey. Findings: We developed four user personas (no sweat player, spotless seeker, social ...